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1 Introduction Worldwide, sensor development is a fast growing discipline. Today’s sensor market offers thousands of sensor types, for almost every measurable quantity, for a broad area of applications, and with a wide diversity in quality. Many research groups are active in the sensor field, exploring new technologies, investigating new principles and structures, aiming at reduced size and price, at the same or even better performance. System engineers have to select the proper sensors for their design, from an overwhelming volume of sensor devices and associated equipment. A well moti- vated choice requires thorough knowledge of what is available on the market, and a good insight in current sensor research to be able to anticipate forthcoming sensor solutions. This introductory chapter gives a general view on sensors their functionality, the nomenclature and global properties as a prelude to a more in-depth discussion about sensor performance and operation principles. 1.1 Sensors in Mechatronics 1.1.1 Definitions A transducer is an essential part of any information processing system that operates in more than one physical domain. These domains are characterized by the type of quantity that provides the carrier of the relevant information. Examples are the optical, electrical, magnetic, thermal and mechanical domains. A transducer is that part of a measurement system that converts information about a measurand from one domain to another, ideally without information loss. A transducer has at least one input and one output. In measuring instruments, where information processing is performed by electrical signals, either the output or the input is of electrical nature (voltage, current, resistance, capacitance and so on), whereas the other is a non-electrical signal (displacement, temperature, elastic- ity and so on). A transducer with a non-electrical input is an input transducer, intended to convert a non-electrical quantity into an electrical signal in order to measure that quantity. A transducer with a non-electrical output is called an output Sensors for Mechatronics. DOI: 10.1016/B978-0-12-391497-2.00001-7 © 2012 Elsevier Inc. All rights reserved.
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2 Sensors for Mechatronics Non-electrical in Electrical out Figure 1.1 Sensors and Sensor actuators. Electrical in Non-electrical out Actuator transducer, intended to convert an electrical signal into a non-electrical quantity in order to control that quantity. So, a more explicit definition of a transducer is an electrical device that converts one form of energy into another, with the intention of preserving information. According to common terminology, these transducers are also called sensor and actuator, respectively (Figure 1.1). So, a sensor is an input transducer and an actua- tor is an output transducer. It should be noted, however, that this terminology is not standardized. In literature other definitions are found. Some authors make an explicit difference between a sensor and a (input) transducer, stressing a distinction between the element that performs the physical conversion and the complete device for instance, a strain gauge (the transducer) and a load cell (the sensor) with one or more strain gauges and an elastic element. Attempts to standardize terminology in the field of metrology have resulted in the Vocabulaire International de Me´trologie (VIM) [1]. According to this docu- ment a transducer is a device, used in measurement, that provides an output quan- tity having a specified relation to the input quantity. The same document defines a sensor as the element of a measuring system that is directly affected by a phenome- non, body or substance carrying a quantity to be measured. Modern sensors not only contain the converting element but also part of the sig- nal processing (analogue processing such as amplification and filtering, AD conver- sion and even some digital electronics). Many of such sensors have the electronics integrated with the transducer part onto a single chip. Present-day sensors may have a bus-compatible output, implying full signal conditioning on board. There is a trend to also include transmission electronics within the device, for instance for biomedical applications. Signal conditioning may be included: to protect the sensor from being loaded or to reduce loading errors; to match the sensor output range to the input range of the ADC; to enhance the S/N (signal-to-noise ratio) prior to further signal processing; to generate a digital, bus-compatible electrical output; or to transmit measurement data for wireless applications. In conclusion, the boundaries between sensor and transducer as proclaimed in many sensor textbooks are disappearing or losing their usefulness: the user buys and applies the sensor system as a single device, with a non-electrical input and an electrical (e.g. analogue, digital and bus compatible) output.
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Introduction 3 1.1.2 Sensor Development Sensors provide the essential information about the state of a (mechatronic) system and its environment. This information is used to execute prescribed tasks, to adapt the system properties or operation to the (changing) environment or to increase the accuracy of the actions to be performed. Sensors play an important role not only in mechatronics but also in many other areas. They are widely applied nowadays in all kind of industrial products and sys- tems. A few examples are as follows: Consumer electronics Household products Public transport, automotive Process industry Manufacturing, production Agriculture and breeding industry Medical instruments and many other areas where the introduction of sensors has increased dramatically the performance of instruments, machines and products. The world sensor market is still growing substantially. The worldwide sensor market offers over 100,000 different types of sensors. This figure not only illus- trates the wide range of sensor use but also the fact that selecting the right sensor for a particular application is not a trivial task. Reasons for the increasing interest in sensors are as follows: Reduced prices: the price of sensors not only depends on the technology but also on pro- duction volume. Today, the price of a sensor runs from several ten thousands of euros for single pieces down to a few eurocents for a 100 million volume. Miniaturization: the IC-compatible technology and progress in micromachining technol- ogy are responsible for this trend [24]. Pressure sensors belong to the first candidates for realization in silicon (early 1960s). Micro-ElectroMechanical Systems (MEMS) are gradually taking over many traditionally designed mechanical sensors [57]. Nowadays, solid-state sensors (in silicon or compatible technology) for almost every quantity are available, and there is still room for innovation in this area [8,9]. Smart sensing: the same technology allows the integration of signal processing and sensing functions on a single chip. Special technology permits the processing of both analogue and digital signals (‘mixed signals’), resulting in sensor modules with (bus compatible) digital output. Popular MEMS sensors are accelerometers and gyroscopes. A MEMS acceler- ometer can be made completely out of silicon, using micromachining technology. The seismic mass is connected to the substrate by thin, flexible beams, acting as a spring. The movement of the mass can be measured by, for instance, integrated piezoresistors positioned on the beam at a location with maximum deformation (Chapter 4) or by a capacitive method (Chapter 5). In mechatronics, mainly sensors for the measurement of mechanical quantities are encountered. The most frequent sensors are for displacement (position) and
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4 Sensors for Mechatronics force (pressure), but many other sensor types can be found in a mechatronic system. Many sensors are commercially available and can be added to or integrated into a mechatronic system. This approach is preferred for systems with relatively simple tasks and operating in a well-defined environment, as commonly encountered in industrial applications. However, for more versatile tasks and specific applications, dedicated sensor systems are required, which are often not available. Special designs, further development or even research are needed to fulfil specific require- ments, for instance with respect to dimensions, weight, temperature range and radi- ation hardness. 1.1.3 Sensor Nomenclature In this book, we follow a strict categorization of sensors according to their main physical principle. The reason for this choice is that sensor performance is mainly determined by the physics of the underlying principle of operation. For example, a position sensor can be realized using resistive, capacitive, inductive, acoustic and optical methods. The sensor characteristics are strongly related to the respective physical transduction processes. However, a magnetic sensor of a particular type could be applied as, for instance, a displacement sensor, a velocity sensor or a tac- tile sensor. For all these applications the performance is limited by the physics of this magnetic sensor. Apparently, position and movement lead the list of measurement quantities. Common parlance contains many other words for position parameters. Often, trans- ducers are named after these words. Here is a short description of some of these transducers. Distance sensor Measures the length of the straight line between two defined points Position sensor Measures the co-ordinates of a specified point of an object in a specified reference system Displacement Measures the change of position relative to a reference point sensor Range sensor Measures in a 3D space the shortest distance from a reference point (the observer) to various points of object boundaries in order to determine their position and orientation relative to the observer or to get an image of these objects Proximity (a) Determines the sign (positive or negative) of the linear distance sensor between an object point and a fixed reference point; also called a switch (b) A contact-free displacement or distance sensor for short distances (down to zero) Level sensor Measures the distance of the top level of a liquid or granular substance in a container with respect to a specified horizontal reference plane Angular sensor Measures the angle of rotation relative to a reference position Encoder Displacement sensor (linear or angular) containing a binary coded ruler or disk
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Introduction 5 Tilt sensor Measures the angle relative to the earth’s normal Tachometer Measures rotational speed Vibration Measures the motion of a vibrating object in terms of displacement, sensor velocity or acceleration Accelerometer Measures acceleration Transducers for the measurement of force and related quantities are as follows: Pressure sensor Measures pressure difference, relative to either vacuum (absolute pressure), a reference pressure or ambient pressure Force sensor Measures the (normal and/or shear) force exerted on the active point of the transducer Torque sensor Measures torque (moment) Forcetorque Measures both forces and torques (up to six components) sensor Load cell Force or pressure sensor, for measuring weight Strain gauge Measures linear relative elongation (positive or negative) of an object, caused by compressive or tensile stress Touch sensor Detects the presence or (combined with a displacement sensor) the position of an object by making mechanical contact Tactile sensor Measures 3D shape of an object by the act of touch, either sequentially using an exploring touch sensor or instantaneously by a matrix of force sensors Many transducers have been given names according to their operating principle, construction or a particular property. Examples are as follows: Hall sensor Measures magnetic field based on the Hall effect, after the American physicist Edwin Hall (18551938) Coriolis mass flow Measures mass flow of a fluid by exploiting the Coriolis force sensor exerted on a rotating or vibrating channel with that fluid; after Gustave-Gaspard de Coriolis, French scientist (17921843) Gyroscope, A device for measuring angle or angular velocity, based on the gyrometer gyroscopic effect occurring in rotating or vibrating structures Eddy current Measures short range distances between the sensor front and a sensor conductive object using currents induced in that object due to an applied AC magnetic field; also used for defect detection LVDT or Linear Variable Displacement Transformer, a device that is basically a voltage transformer, with linearly movable core NTC Short for temperature sensor (especially thermistor) with Negative Temperature Coefficient Some sensors use a concatenation of transduction steps. A displacement sensor, combined with a spring, can act as a force sensor. In combination with a calibrated mass, a displacement sensor can serve as an accelerometer. The performance of such transducers not only depends on the primary sensor but also on the added
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6 Sensors for Mechatronics components: in the examples above the spring compliance and the seismic mass, respectively. Information about a particular quantity can also be obtained by calculation using relations between quantities. The accuracy of the result depends not only on the errors in the quantities that are measured directly but also on the accuracy of the parameters in the model that describes the relation between the quantities involved. For instance, in an acoustic distance measurement the distance is calculated from the measured time-of-flight (ToF; with associated errors) and the sound velocity. An accurate measurement result requires knowledge of the acoustic velocity of the medium at the prevailing temperature. Some variables can be derived from others by electronic signal processing. Speed and acceleration can be measured using a displacement sensor, by differenti- ating its output signal once or twice, respectively. Conversely, by integrating the output signal of an accelerometer a velocity signal is obtained and, by a second integration, a position signal. Obviously, the performance of the final result depends on the quality of the signal processing. The main problem with differentia- tion is the increased noise level (in particular in the higher frequency range), and integration may result in large drift due to the integration of offset. 1.1.4 Sensors and Information According to the amount of information a sensor or sensing system offers, three groups of sensors can be distinguished: binary sensors, analogue sensors and image sensors. Binary sensors give only one bit of information but are very useful in mechatronics. They are utilized as end stops, as event detectors and as safety devices. Depending on their output (0 or 1), processes can be started, terminated or interrupted. The binary nature of the output makes them highly insensitive to elec- trical interference. Analogue sensors are used for the acquisition of metric information with respect to quantities related to distance (e.g. relative position, linear and angular velocity and acceleration), force (e.g. pressure, gripping force and bending) or others (e.g. thermal, optical, mechanical, electrical or magnetic properties of an object). A wide variety of industrial sensors for these purposes are available. The third category comprises image sensors, intended for the acquisition of information related to structures and shapes. Depending on the application, the sen- sor data refer to one-, two- or three-dimensional images. The accuracy require- ments are less severe compared to the sensors from the preceding category, but the information content of their output is much larger. As a consequence, the data acquisition and processing for such sensors are more complex and more time consuming. The next sections present some general aspects of sensors, following the catego- rization in binary, analogue and image sensors as introduced before. Actually, the section serves as a general overview of the sensors and sensing systems which are discussed in more detail in subsequent chapters. Details on physical background, specifications and typical applications are left for those chapters. Here, the
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Introduction 7 y y Uncertainly margin 1 1 Tolerance Tolerance margin margin 0 0 xt x xt1 xt2 x xmin xmax xmin xmax Active range Hysteresis range (A) Input range (B) Input range Figure 1.2 Characteristic of a binary sensor (A) without hysteresis, (B) with imposed hysteresis. differences in approach are highlighted and their consequences for the applicability in mechatronic systems are emphasized. Binary Sensors A binary sensor has an analogue input and a two-state output (0 or 1). It converts the (analogue) input quantity to an one-bit output signal. These sensors are also referred to as switches or detectors. They have a fixed or an adjustable threshold level xt (Figure 1.2A). In fact, there are essentially two levels, marking the hystere- sis interval (Figure 1.2B). Any analogue sensor can be converted to a binary sensor by adding a Schmitt trigger (comparator with hysteresis, Appendix C.5). Although hysteresis lowers the accuracy of the threshold detection (down to the hysteresis interval), it may help reduce unwanted bouncing due to noise in the input signal. Most binary sensors measure position. Binary displacement sensors are also referred to as proximity sensors. They react when a system part or a moving object has reached a specified position. Two major types are the mechanically and the magnetically controlled switches. Mechanically controlled switches are actually touch sensors. They are available in a large variety of sizes and constructions; for special conditions there are water- proof and explosion-proof types; for precision measurements there are switches with an inaccuracy less than 61 μm and a hysteresis interval in the same order, guaranteed over a temperature range from 220C to 75C. Another important parameter of a switch is the reliability, expressed in the minimum number of com- mutations. Mechanical switches have a reliability of about 106. A reed switch is a magnetically controlled switch: two magnetizable tongues or reeds in a hermetically closed encapsulation filled with an inert gas. The switch is normally off; it can be switched on mechanically by a permanent magnet approach- ing the sensor. Reed switches have good reliability: over 107 commutations at a switching frequency of 50 Hz. A disadvantage is the bouncing effect, the chattering of the contacts during a transition of state. Reed switches are applied in various
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8 Sensors for Mechatronics Table 1.1 Typical Specifications of Commercial Binary Sensors Type Working Range Response Time Reproducibility Mechanical 0 (contact) 61 μm Reed switch 02 cm 0.1 ms (on) Optical 02/10/35 m 500 Hz/1 ms 10 cm Inductive 050 cm 1 ms 1 cm Capacitive 040 mm 1 ms 1 mm Magnetic 0100 mm 10 μm Reflection from object/reflector/direct mode. commercial systems, from cars (monitoring broken lights, level indicators) to elec- tronic organs (playing contacts), to telecommunication devices and testing and measurement equipments. In mechatronic systems they act as end-of-motion detec- tors, touch sensors and other safety devices. The technical aspects are described in Chapter 6 on inductive and magnetic sensors. The drawbacks of all mechanical switches are a relatively large switch-on time (for reed switches typically 0.2 ms) and wear. This explains the growing popularity of electronic switches, such as optically controlled semiconductors and Hall plates. There is a wide range of binary displacement sensors on the market, for a variety of distances and performance. Table 1.1 presents a concise overview of specifications. All but the mechanical switch operate essentially contact free. Obviously, the optical types have the widest distance range. The optical, inductive and capacitive types are essentially analogue sensors, with adjustable threshold levels. The specifi- cations include interface and read-out electronics. In particular, the response time of the sensor itself may be much better than the value listed in the table. Accuracy data include hysteresis and apply for the whole temperature range (maximum oper- ating temperature range 70C typical). Analogue Sensors There is an overwhelming number of analogue sensors on the market, for almost any physical quantity, and operating according to a diversity of physical principles. In mechatronics, the major measurement quantities of interest are linear and angu- lar displacement, their time derivatives (velocity and acceleration) and force (including torque and pressure). These and many other sensors will be discussed in more detail in later chapters. Image Sensors Imaging is a powerful method to obtain information about geometrical parameters of objects with a complex shape. The 3D object or a complete scene is transformed to a set of data points representing the geometrical parameters that describe
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Introduction 9 Scan points Figure 1.3 Imaging techniques: (A) 2D Scan lines point scanning, (B) 1D line scanning and (C) projection on 2D matrix sensor. Rotating sensor (A) (2 DOF) Scene (2D) Scan area Scan lines Rotating line (B) Scene (2D) Scan area sensor (1 DOF) Scan area Matrix sensor (C) Scene (2D) particular characteristics of the object, for instance its pose (position and orienta- tion in space), dimensions, shape or identity. An essential condition in imaging is the preservation of the required information. This is certainly not trivial: photo- graphic and camera pictures are 2D representations of a 3D world, and hence much information is lost by the imaging process. Three basic concepts for image acquisition are depicted schematically in Figure 1.3. In the first method the scene to be imaged is scanned point by point by some mechanical means (e.g. a mirror on a stepping motor) or electronically (for instance with phased arrays). Such an imaging system is often referred to as a range finder: it yields distance information over an angular range determined by the limits of the scanning mechanism. The output is a sequential data stream con- taining 3D information about the scene: depth data from the scanning sensor and angular data from the scanning mechanism. Although the data points are three dimensional, information is obtained only about the surface boundary range and only that part of the surface that is connected to the sensor system by a line of direct sight. Therefore, range data are sometimes called 2.5D data. In Figure 1.3A, the sensor and scanning mechanism are presented as a single device. Most scanning systems consist of several parts, for instance a fixed transmitter and receiver and
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10 Sensors for Mechatronics one or more rotating mirrors or reflectors. Sometimes the transmitter, the receiver or both are mounted on the scanning device. Although the scanning method is slow, it requires only a single sensor which can therefore be of high quality. In the second method (Figure 1.3B) the scene is scanned line by line, again using some mechanical scanning device. Each line is projected onto an array of sensors (in the optical domain for instance a diode array). The sensor array may include electronic scanning to process the data in a proper way. Nevertheless, the mechanical scanning mechanism operates in only one direction, which increases the speed of image formation and lowers construction complexity as compared to point-wise scanning. The third method (Figure 1.3C) involves the projection of the unknown image on a 2D matrix of point sensors. This matrix is electronically scanned for serial processing of the data. Since all scanning is performed in the electronic domain, the acquisition time is short. The best known imaging device is the CCD matrix camera (Charge Coupled Device). It has the highest spatial resolution of all matrix imagers. Considering the nature of the various possible information carriers, there are at least three candidates for image acquisition: light, (ultra)sound and contact force. All three are being used in both scanning and projection mode. Most popular is the CCD camera as imager for exploring and analyzing the work space of a mechatro- nic system or a robot’s environment. However, in numerous applications the cam- era is certainly not the best choice. The acquisition of an image is just the first step in getting the required informa- tion; data processing is another important item. There is a striking difference between (camera based) vision and non-vision data processing. The main problem of the CCD camera is the provision of superfluous data. The first step in image pro- cessing is, therefore, to get rid of all irrelevant data in the image. For instance, a mere contour might be sufficient for proper object identification; the point is how to find the right contour. However, most non-vision imagers suffer from a too-low resolution. Here the main problem is the extraction of information from the low- resolution image and in the case of scanning systems from other sensors. In all cases, model-driven data processing is required to be able to arrive at proper conclusions about features of the objects or the scene under test. Optical Imaging Most optical imaging systems applied in mechatronics and robotics use a camera (CCD-type or CMOS) and a proper illumination of the scene. The image (or a pair of images or even a sequence when 3D information is required) is analyzed by some image-processing algorithm applied to the intensity and colour distribution in the image. Particular object features are extracted from particular patterns in light inten- sity in the image. Position information is derived from the position of features in the image, together with camera parameters (position and orientation, focal length). Specified conditions for getting a proper image must be fulfilled: an illumination that yields adequate contrast and no disturbing shadows and a camera set-up with a
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Introduction 11 full view on the object or the scene and with a camera that has a sufficiently high resolution, so as not to lose relevant details. Obviously, a 2D image shows only a certain prospect of the object, never a complete view (self-occlusion). In case of more than one object, some of them could be (partially) hidden behind others (occlusion), a situation that makes the identification much more difficult. Even in the most favourable situation, the image alone does not reveal enough information for the specified task. Besides a proper model of the object, we need a model of the imaging process: position and orientation of the camera(s) and camera parameters like focal length and position of the light source(s) with respect to the object and camera. All of these items determine the quality of the image from which features are to be extracted. The pose of the object in the scene can be derived from the available information and knowledge of the imaging system. Many algorithms have been developed to extract useful features from an image that is built up of thousands of samples (in space and time) described by colour parameters, grey-tone values or just bits for black and white images. The image is searched for particular combinations of adjacent pixels such as edges, from which region boundaries are derived. Noise in the image may disturb this process, and special algorithms have been developed to reduce its influence. The result is an image that reveals at least some characteristics of the object. For further informa- tion on feature extraction the reader is referred to the literature on computer vision and image processing. Acoustic Imaging The interest in acoustic waves for imaging is steadily growing, mainly because of the low cost and simple construction of acoustic transducers. The suitability of acoustic imaging has been proved in medical, geological and submarine applica- tions. Applications in mechatronics have, however, some severe limitations going back to ultrasonic wave propagation in air (where most mechatronic systems oper- ate). Despite these limitations, detailed in Chapter 9, many attempts are being made to improve the accuracy and applicability of acoustic measurement systems, in particular as they are applied to distance measurement and range finding. The most striking drawback of acoustic imaging is the low spatial resolution, due to the diverging beam of acoustic transducers. The directivity of the transdu- cers can be improved by increasing the ratio between the diameter and the wave length. Even at medium frequencies (i.e. 40 kHz), this results in rather large devices. An alternative method is the use of an array of simultaneously active acoustic elements. Due to interference, the main beam (in the direction of the acoustic axis) is narrowed. Further, the direction of this beam can be electronically controlled by variation of the phase shift or time delay between the elements of the array. This technique, known as phased arrays, applies to transmitters as well as receivers. The recognition of shapes requires a set of distance sensors or scanning with a single sensor, according to one of the principles in Figure 1.3. The shape follows from a series of numerical calculations (see for instance [10,11]).
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12 Sensors for Mechatronics Generator Interface Echo pattern Transmitter Receiver Stimulus Response Object Base plate Figure 1.4 Object recognition using acoustic signature technique; left: system set-up; right top: echo of base plate only; bottom: echo of object on base plate. Instead of geometric models for use in object recognition, other models may be used. An example of such a different approach is shown schematically in Figure 1.4. An acoustic signal (the stimulus) is transmitted towards the object. The shape of the echo pattern (the response) is determined by the object’s shape and orientation. In a learning phase, echo patterns of all possible objects are stored in computer memory. They can be considered acoustic signatures of the objects. The echo pattern from a test object belonging to the trained set is matched to each of the stored signatures. Using a minimum distance criterion reveals the best candi- date [12]. Evidently, the test conditions should be the same as during the learning phase: a fixed geometry and a stable stimulus are required. The comparison process may be performed either in the frequency domain or in the time domain. With this simple technique, it is possible to distinguish between objects whose shapes or orientations (normal versus upside-down position) are quite different. With an adaptive stimulus and a suitable algorithm, even small defects in an object can be detected by ultrasonic techniques. Under certain condi- tions, very small object differences can be detected, for instance between sides of a coin [13]. Tactile Imaging In contrast to optical and acoustic imaging, tactile imaging is performed by mechanical contact between sensor and object. Making contact has advantages as well as disadvantages. Disadvantages are the mechanical load of the object (it may move or be pressed) and the necessity of moving the sensor actively towards the object. Advantages of tactile imaging include the possibility of acquiring force- related information (for instance touching force and torque) and mechanical proper- ties of the object (e.g. elasticity, resilience and surface texture). Another advantage over optical imaging is the insensitivity to environmental conditions. This
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Introduction 13 versatility of a tactile sensor makes it very attractive for control purposes, espe- cially in assembly processes. Moreover, tactile and vision data can be fused, to ben- efit from both modalities. In robotics, tactile imaging is mostly combined with the gripping action. For in- line control the tactile sensor should be incorporated into the gripper of the robot, allowing simultaneous force distribution and position measurements during the motion of the gripper. This permits continuous force control as well as position correction. In inspection systems (like coordinate measuring machines), the object under test is scanned mechanically by a motion mechanism, with a touch sensor as the end effector. The machine is controlled to follow a path along the object, while keeping the touch force at a constant value. Position data follow from back trans- formation of the tip (sensor) co-ordinates to world co-ordinates. The scanning is slow but can be very accurate, down to 10 nm in three dimensions. 1.2 Selection of Sensors Choosing a proper sensor is certainly not a trivial task. First of all, the task that is to be supported by one or more sensors needs to be thoroughly analyzed and all possible strategies to be reviewed. Potential sensors should be precisely specified, including environmental conditions and mechanical and electrical constraints. If commercial sensors can be found that satisfy the requirements, purchase is recom- mended. Special attention should be given to interface electronics (in general avail- able as separate units, but rarely adequate for newly developed mechatronic systems). If the market does not offer the right sensor system, such a system may be assembled from commercial sensor components and electronics. This book gives some physical background for most sensors, to help understand their operation, to assist in making a justified choice, or to provide knowledge for assembling particu- lar sensing systems. Sensor selection is based on satisfying requirements; however, these require- ments are often not known precisely or in detail, in particular when the designer of the system and its user are different persons. The first task of the designer, there- fore, is to get as much information as possible about the future applications of the system, all possible conditions of operation, the environmental factors and the specifications, with respect to quality, physical dimensions and costs. The list of demands should be exhaustive. Even when not all items are relevant, they must be indicated as such. This will leave more room to the designer and minimizes the risk of having to start all over again. The list should be made in a way that enables unambiguous comparison with the final specifications of the designed system. Once the designer has a complete idea about the future use of the system, the phase of the conceptual design can start. Before thinking about sensors, the measurement principle first has to be consid- ered. For the instrumentation of each measurement principle, the designer has a
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14 Sensors for Mechatronics F Figure 1.5 Measuring tank contents. C E D B F A multitude of sensing methods at his disposal. For the realization of a particular sen- sor method, the designer has to choose the optimal sensor component and sensor type from a vast collection of sensors offered by numerous sensor manufacturers. This design process is illustrated by an example of a measurement for just a sin- gle, static quantity: the amount of fluid in a container (for instance, a drink dis- penser). The first question to be answered is, in what units the amount should be expressed: volume or mass? This may influence the final selection of the sensor. Figure 1.5 shows various measurement principles in a schematic way: A: the tank is placed on a balance, to measure its total weight; B: a pressure gauge on the bottom of the tank; C: a gauging-rule from top to bottom with electronic read-out; D: level detector on the bottom, measuring the column height; E: level detector from the top of the tank, measuring the height of the empty part; F: (mass or volume) flow meters at both inlet and outlet. Obviously, many more principles can be found to measure a quantity that is related to the amount of fluid in the reservoir. In the conceptive phase of the design as many principles as possible should be considered, even unconventional ones. Based on the list of demands it should be possible to find a proper candidate principle from this list, or at least to delete many of the principles, on an argued base. For instance, if the tank contains a cor- rosive fluid, a non-contact measurement principle is preferred, putting principles B, C and D on a lower position in the list. Further, for very large tanks, method A can possibly be eliminated because of high costs. The conceptual design ends up with a set of principles with pros and cons, ranked according to the prospects of success. After having specified a list of candidate principles, the next step is to find a suitable sensing method for each of them. In the example of Figure 1.5 we will fur- ther investigate principle E, a level detector placed at the top of the tank. It should be noted that from level alone the amount of liquid cannot be determined: the
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Introduction 15 shape of the container should also be taken into account. Again, a list of the various possible sensor methods is made, as follows: E1: a float, connected to an electronic read-out system; E2: optical ToF measurement; E3: optical range measurement; E4: electromagnetic distance measurement (radar); E5: acoustic ToF measurement and so on. As in the conceptual phase, these methods are evaluated using the list of demands, so not only the characteristics of the sensing method but also the proper- ties of the measurement object (e.g. kind of liquid and shape of tank) and the envi- ronment should be taken into account. For the tank system, the acoustic ToF method could be an excellent candidate because of its being contact free. In this phase it is also important to consider methods to reduce such environmental factors as temperature. Ultimately, this phase concludes with a list of candidate sensing methods and their merits and demerits with respect to the requirements. The final step is the selection of the components that make up the sensing sys- tem. Here a decision must be made between the purchase of a commercially avail- able system and the development of a dedicated system. The major criteria are costs and time: both are often underestimated when development by one’s own is considered. In this phase of the selection process, sensor specifications become important. Sensor providers publish specifications in data sheets or on the Internet. However, the accessibility of such data is still poor, making this part of the selection process critical and time consuming, in particular for non-specialists in the sensor field. Evidently, the example of the level sensor is highly simplified, whereas the selection process is usually not that straightforward. Since the sensor is often just one element in the design of a complex mechatronic system, close and frequent interaction with other design disciplines as well as the customer is recommended. References to Cited Literature [1] International Vocabulary of Metrology Basic and general concepts and associated terms (VIM); Document produced by Working Group 2 of the Joint Committee for Guides in Metrology (JCGM/WG 2), JCGM 200: 2008. [2] K.E. Petersen: Silicon as a mechanical material, Proc. IEEE, 70(5) (1982), 420457. [3] S. Middelhoek, S.A. Audet: Silicon sensors; Academic Press, London, San Diego, New York, Berkeley, Boston, Sydney, Tokyo, Toronto, 1989; ISBN 0-12-495051-5. [4] J.W. Gardner: Microsensors principles and applications; Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 1994; ISBN 0-471-94135-2/94136-0. [5] R.F. Wolffenbuttel (ed.): Silicon sensors and circuits; on-chip compatibility; Chapman & Hall, London, Glasgow, Weinheim, New York, Tokyo, Melbourne, Madras, 1996; ISBN 0-412-70970-8.
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16 Sensors for Mechatronics [6] M.-H. Bao: Micro mechanical transducers pressure sensors, accelerometers and gyroscopes; Elsevier, Amsterdam, Lausanne, New York, Oxford, Shannon, Singapore, Tokyo, 2000; ISBN 0-444-50558-X. [7] M. Elwenspoek, R. Wiegerink: Mechanical microsensors; Springer-Verlag, Berlin, Heidelberg, New York, (Barcelona, Hong Kong, London, Milan, Paris, Singapore, Tokyo), 2001; ISBN 3-540-67582-5. [8] Proceedings of various conferences, for instance ‘Transducers’, ‘Eurosensors’, ‘IEEE Int. Conf. on Micro Electro Mechanical Systems’ and many more. [9] Various international journals, for instance ‘Sens. Actuators A’ (Elsevier), ‘IEEE Sens. J.’ (IEEE). [10] P. Mattila, J. Siirtola, R. Suoranta: Two-dimensional object detection in air using ultra- sonic transducer array and non-linear digital L-filter, Sens. Actuators A, 55 (1996), 107113. [11] A.D. Armitage, N.R. Scales, P.J. Hicks, P.A. Payne, Q.X. Chen, J.V. Hatfield: An inte- grated array transducer receiver for ultrasound imaging, Sens. Actuators A, 4647 (1995), 542546. [12] C. Cai, P.P.L. Regtien: A smart sonar object recognition system for robots, Meas. Sci. Technol., 4 (1993), 95100. [13] J.M. Martı´n Abreu, T. Freire Bastos, L. Caldero´n: Ultrasonic echoes from complex sur- faces: an application to object recognition, Sens. Actuators A, 31 (1992), 182187. Literature for Further Reading Introductory Books on Sensors and Mechatronics [1] P. Ripka, A. Tipek (eds.): Modern sensors handbook; Wiley-ISTE, London; Newport Beach, CA, 2007; ISBN 978-1-905209-66-8. [2] T.G. Beckwith, R.D. Marangoni, J.H. Lienhard V: Mechanical measurements; Pearson Prentice Hall, Upper Saddle River, NJ, 2007; ISBN 0-201-84765-5. [3] R.S. Figliola, D.E. Beasley: Theory and design for mechanical measurements; Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 2006; ISBN 0-471- 44593-2. [4] A. Preumont: Mechatronics dynamics of electromechanical and piezoelectric sys- tems; Springer, Berlin, Heidelberg, New York, (etc.) 2006; ISBN 1-4020-4695-2. [5] R.S. Figliola, D.E. Beasley: Theory and design for mechanical measurements; Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 2006; ISBN 0-471- 44593-2. [6] H.K. To¨nshoff, I. Inasaki (eds.): Sensors in manufacturing; Wiley-VCH Verlag GmbH, Weinheim, FRG, 2001; ISBN 3-527-29558-5. [7] R. Pallas-Areny, J.G. Webster: Sensors and signal conditioning; 2nd edition, Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 2001; ISBN 0-471- 33232-1. [8] G. Dudek, M. Jenkin: Computational principles of mobile robotics; Cambridge University Press, Cambridge, 2000; ISBN 0-521-56876-5. [9] I.J. Busch-Vishniac: Electromechanical sensors and actuators; Springer-Verlag, Berlin, Heidelberg, New York, (etc.) 1999; ISBN 0-387-98495-X. [10] P. Hauptmann: Sensors principles and applications; Hanser, Munich; Prentice Hall, Hemel Hempstead, Engelwood Cliffs NJ, 1993; ISBN 0-13-805-789-3P.
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Introduction 17 Books on Semiconductor Sensors [1] G.C.M. Meijer (ed.): Smart sensor systems; Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 2008; ISBN 9780470866917. [2] S.Y. Yurish, M.T.S.R. Gomes (eds.): Smart sensors and MEMS; Springer-Verlag, Berlin, Heidelberg, New York, (etc.) 2005; ISBN 1-402-02927-6. [3] A.J. Wheeler, A.R. Ganji: Introduction to engineering experimentation; Pearson, Upper Saddle River NJ, 2004; ISBN 0-13-065844-8. [4] M. Elwenspoek, R. Wiegerink: Mechanical microsensors; Springer-Verlag, Berlin, Heidelberg, New York, (etc.) 2001; ISBN 3-540-67582-5. [5] M.-H. Bao: Micro mechanical transducers; Elsevier, Amsterdam, Lausanne, New York, Oxford, Shannon, Singapore, Tokyo, 2000; ISBN 0-444-50558-X. [6] R.F. Wolffenbuttel (ed.): Silicon sensors and circuits; on-chip compatibility; Chapman & Hall, London, Glasgow, Weinheim, New York, Tokyo, Melbourne, Madras, 1996; ISBN 0-412-70970-8. [7] S.M. Sze (ed.): Semiconductor sensors; Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 1994; ISBN 0-471-54609-7. [8] J.W. Gardner: Microsensors principles and applications; Wiley, New York, Chichester, Weinheim, Brisbane, Singapore, Toronto, 1994; ISBN 0-471-94135-2/ 94136-0. [9] L. Ristic: Sensor technology and devices; Artech House Publishers, Boston, London, 1994; ISBN 0-89006-532-2. [10] S. Middelhoek, S.A. Audet: Silicon sensors; Academic Press, London, San Diego, New York, Berkeley, Boston, Sydney, Tokyo, Toronto, 1989; ISBN 0-12-495051-5.
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2 Sensor Fundamentals A sensor performs the exchange of information (hence energy) from one domain to another and as such it operates at the interface between different physical domains. In this chapter we first introduce a notation system for the quantities used in this book. To avoid confusion with notations, we define unambiguous symbols for each quantity. For example, in the electrical domain the symbol ε usually stands for dielectric constant, whereas it means strain in the mechanical domain. In this book we use ε for dielectric constant only; strain is denoted by S. Several frameworks have been developed for a systematic description of sensors. Various approaches are presented in this chapter. Further, a formal description of relations between quantities, based on energy considerations, is introduced from which particular physical effects are derived serving for specific groups of sensors that are discussed in later chapters. 2.1 Physical Quantities 2.1.1 Classification of Quantities Various attempts have been made to set up a consistent framework of quantities. Physical quantities can be divided into subgroups according to various criteria. This leads to subgroups with different characteristics. With respect to direction: a quantity having a direction is called a vector (e.g. velocity); a quantity that does not have a direction is a scalar (e.g. temperature). With respect to time behaviour: a state variable describes a static property; a rate variable describes a dynamic property. Within one domain state and rate variables are related as follows: ð d _ Xrate 5 Xstate 5Xstate or Xstate 5 Xrate dt ð2:1Þ dt Sensors for Mechatronics. DOI: 10.1016/B978-0-12-391497-2.00002-9 © 2012 Elsevier Inc. All rights reserved.
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20 Sensors for Mechatronics Examples The electrical domain ð d I 5 Q or Q5 Idt ð2:2Þ dt The mechanical (translation) domain ð d v5 x or x5 vdt ð2:3Þ dt With respect to energy: a quantity that is associated with an energetic phenomenon: often called a variable (e.g. electric current and pressure); a quantity that is not associated with energy or only with latent energy: often called a (material) property (e.g. length). Sometimes a property is also called a constant, but the value of most properties is not constant at all, so we will not use this term. With respect to dependency on mass or size: a quantity which value is independent of the dimensions or the amount of matter is called an intensive quantity (e.g. temperature is an intensive variable and resistivity is an intensive property); a quantity which value depends on the amount of mass or volume (its extension) is called an extensive quantity (e.g. charge is an extensive variable and resistance is an extensive property). Resistivity ρ (Ωm) is a pure material property, whereas the resistance R (Ω) depends on the material as well as the dimensions of the resistor body. In general, the relation between an intensive and extensive quantity within one domain is given by Ae 5GAi, with Ae and Ai, general extensive and intensive quantities, and G, a geometrical parameter, representing for instance the dimension of a sensor. In most cases the value of a material property is orientation dependent. This dependency is expressed by subscripts added to the symbols (Appendix A). Extensive variables are state variables; their time derivatives are rate variables or flows. Intensive variables are identical to efforts. Flow and effort variables are discussed when conjugated pairs of variables are introduced. With respect to the end points of a lumped element: To explain this classification, we first introduce the term lumped element. A lumped ele- ment symbolizes a particular property of a physical component. That property is thought to be concentrated in that element between its two end points or nodes. Exchange of energy or information occurs only through these terminals. In this sense we distinguish: an across-variable, defined by the difference of its value between the two terminals of a lumped element (e.g. voltage and velocity); a through-variable, a variable that has the same value at both terminals of the lumped element (e.g. electric current and force). Through-variables are also called generalized I-variables; across-variables are called gen- eralized V-variables. However, this is just a matter of viewpoint. It is perfectly justified to call them generalized forces and displacements. We will use these types of variables in Section 2.1.2 where relations between quantities are discussed.
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Sensor Fundamentals 21 Table 2.1 Power Conjugate Variables for Various Domains Domain Effort Unit Flow Unit Mechanical (translation) Force N Velocity m/s Mechanical (rotation) Torque Nm Angular velocity rad/s Pneumatic, hydraulic Pressure Pa Volume flow m3/s Electrical Voltage V Current A5C/s Magnetic Current A Voltage V5Wb/s Thermal Temperature K Entropy flow J/K/s Thermal Temperature K Heat flow W With respect to cause and effect: Output variables are related to input variables according to the physics of the system. Input variables can bring a system into a particular state which is represented by its out- put variables. So output variables depend on the input variables: independent variables are applied from an external source to the system; dependent variables are responses of the system to the input variables. Obviously, a variable can be dependent or independent, according to its function in the system. For instance the resistance value of a resistor can be determined by applying a voltage across its terminals and measuring the current through the device or just the other way round. In the former case the voltage is the independent variable, and it is the dependent variable in the latter. The relation between independent and dependent vari- ables is governed by physical effects, by material properties or by a particular system layout. It either acts within one physical domain or crosses domain boundaries. Such relations are the fundamental operation of sensors. This is further discussed in Section 2.1.2. With respect to power conjugation: Within a single energy domain, pairs of variables can be defined in such a way that their product is power. They are called power conjugated variables. The members of such a pair are called effort variable and flow variable. Table 2.1 lists these variables for various domains. Note that the dimension of each product is power (W). The magnetic quantity ‘current’ stems from the definition of magnetic field strength, where the number of ampere-turns (or MMF, magnetomotive force) determines the field strength (see Chapter 6). Its power conjugate variable ‘voltage’ is actually the rate of change in magnetic flux, with unit Wb/s, but this is equal to the induction voltage. For practical reasons, heat flow (W) is often taken as the thermal flow variable rather than an entropy-related quantity which is not measurable in a straightfor- ward way. The domain is therefore sometimes called pseudothermal (see last row of Table 2.1). Table 2.2 summarizes various relations between rate, state, effort and flow vari- ables for the mechanical, electrical, magnetic and thermal domains. With respect to energy conjugation: Another way to define pairs of variables is based on the property that their product equals energy per unit volume (J/m3). Table 2.3 lists these pairs for the major domains.
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