National Academies Press: OpenBook

Expanding the Vision of Sensor Materials (1995)

Chapter: APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY

« Previous: APPENDIX B: SENSOR TECHNOLOGY GLOSSARY -- DEFINITIONS AND EXPLANATIONS . . .
Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×

APPENDIX C
AN ILLUSTRATIVE SENSOR TAXONOMY

The discussion of a taxonomy for sensors that was presented in Chapter 1 was necessarily brief. This appendix applies those somewhat theoretical concepts to specific examples drawn from past reports of the National Research Council's National Materials Advisory Board that addressed various sensor applications (NRC, 1986a,b,c, 1987, 1989a,b, 1992). For example, Figure C-1, based on a 1989 report (NRC, 1989a) graphically depicts the classification, presented in Chapter 1, in which sensors are classified on the basis of the energy form in which signals are received and generated (mechanical, thermal, electrical, magnetic, radiant, or chemical) and by the nature of the transduction effect (self-generating or modulating).

Figure C-2 applies the example taxonomy to a thermocouple. The figure indicates that in the general case, both input and output signals can be in any one of these six forms of energy, giving rise to a six-by-six matrix of primary (input) and secondary (output) signals, as summarized in Table 1-3. Following the approach of Middlehoek and Noorlag (1982), self-generating and modulating signals may be treated as fundamental transduction principles, creating a third dimension to the six-by-six matrix. As discussed in Chapter 1, some confusion then arises from the use of the terms "passive" and "active" for modulating sensors. For this reason, the designations "self-generating" and "modulating" are preferred to describe, respectively, sensors that do and do not require an auxiliary energy source to produce an output signal. For example, as shown in Figure C-2, a thermocouple is a self-generating transducer, since a change in temperature is converted directly into an electrical signal that can be measured. In contrast, the mechanical energy input to a strain gauge is modulated or converted to an electrical signal (Figure C-3) through the use of a piezoresistive element made of wire or metal foil. Deformation of this element as a result of a tensile or compressive force results in a change in electrical resistance. The various signal energies that are used in modulating transducers include photoconductive, magnetoresistive, thermoresistive, electrically conductive, or piezoresistive ones.

Figure C-4 illustrates the correlation between the form of the sensor signal and sensor sensitivity,

FIGURE C-1   Basic sensor taxonomy.

Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×

FIGURE C-2  Example of thermocouple transducer.

based on the magnitude of the energy change to be detected. For example, the detection of chemical signals is generally less than the measurement of chemical bonding or binding energies, which are likely to be in the range of 0.025 volt. In contrast, the energies associated with thermal signals are significantly greater, corresponding to wavelengths and intensities in the thermal energy spectrum. Similarly, sensing of radiant, electrical, and magnetic signals requires the detection of energies in the relevant parts of the electromagnetic spectrum. For example, the long-wavelength infrared detectors discussed in Chapter 5 depend upon the use of semiconductor materials that can efficiently absorb radiation in the wavelength band of 8 to 14 microns; this requirement necessitates the use of sensor materials with band gaps less than about 130 MeV.

Figure C-5 shows that sensitivity requirements for sensors used in materials processing depend not only upon the signal energy magnitude and form, as discussed above, but also on the scale of the material property to be measured. In the case of metal processing, the properties of interest can range from nanostructural features, such as point defects and dislocation densities, through microstructural features (phase transformations, grain size) to millistructural and macrostructural properties such as tensile strength. The selection and design of an appropriate sensor depends upon an understanding of the scale of measurement and sensitivity required for the proposed application. The communication tool presented in Chapter 2 offers an effective means for matching the measurement scale of the application with the capabilities of candidate sensor technologies. In the polymer matrix composite processing example discussed in Chapter 3, sensing requirements to determine part quality are based on the determination of bulk properties. In contrast, the in situ diagnostic techniques under development to monitor the fabrication of band-structure-engineered semiconductor materials depend on the determination of materials properties at nanostructural and microstructural scales.

Figure C-6 illustrates some of the practical constraints associated with sensor applications for materials processing. These constraints apply regardless of the signal form or transduction type. For example, there is frequently a requirement for sensing

Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×

FIGURE C-3   Example of strain gauge transducer.

to be conducted in a noninvasive fashion such that the presence of a sensor does not perturb the fabrication process. Applications of this type are discussed in Chapter 3 in the context of intelligent processing of polymer matrix composites, and the requirement for noninvasive monitoring of composite cure is identified as a major driver for the development of new sensor types. The use of optical sensing technologies is particularly promising for such noninvasive sensing applications.

Another important constraint for sensing applications is the availability of reliable, low-cost sensors. As noted in Part II of the report, the availability of such sensors is critical in order to accelerate the incorporation of advanced sensors in practical applications, including materials and component manufacture. Low-cost, reliable sensors are also needed for structural control and health monitoring and for environmental sensing applications, such as personal health monitoring. In the case of structural health monitoring, practical requirements for long-term reliability may be far more challenging than those associated with materials manufacture.

The issue of measurement time and sensor response time (Figure C-6) is considered in Chapter 3 in the context of intelligent processing of structural polymer matrix composites. It is noted that, in practical applications, sensors with short time constants are required in order to detect very rapid, localized changes in the matrix resin system during composite cure or to detect large gradients in material

Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×

FIGURE C-4  Correlation between transducer energy form and sensitivity.

FIGURE C-5  Correlation of sensor sensitivity with property measurement scale.

Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×

FIGURE C-6   Illustration of typical constraints on sensor applications.

properties over a processing time of several hours. Thus, the sensor response time must be short enough to provide an accurate and "instantaneous" representation of the material during processing, thereby permitting modifications to be made to the composite cure parameters in real time in order to optimize the process for final material quality and efficient use of processing facilities. If the sensor response time is long compared with the process response time, changes to the material processing parameters cannot be achieved effectively on-line, and intelligent processing is not feasible.

A further constraint on sensors for materials processing arises from the hostile manufacturing environment in which such sensors must operate. Processing is frequently performed at elevated temperatures (up to 900 °F or 480 °C for advanced thermosetting polymer matrix composites), and the chemical environment associated with processing may tend to attack the material of the sensor (exposure to polymer resins and their precursors may result in degradation of sensor performance). Thus, the sensors used to monitor process changes must be robust and capable of performing reliably under elevated temperature and chemically aggressive conditions. In addition, sensors must be insensitive to electromagnetic interference effects, for example, in an autoclave during processing. Some of the major constraints associated with monitoring the temperature of polymer-matrix composite resin during cure are summarized in Appendix D, Table D-1.

REFERENCES

Middlehoek, S., and D.J.W. Noorlag. 1982. Three-dimensional representation of input and output transducers. Sensors and Actuators 2(1):29–41.


NRC (National Research Council). 1986a. Bioprocessing for the Energy-Efficient Production of Chemicals. NMAB-428. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

NRC (National Research Council). 1986b. New Horizons in Electrochemical Science and Technology. NMAB-438-1. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

NRC (National Research Council). 1986c. Automated Nondestructive Characterization and Evaluation in Metal and Ceramic Powder Production. NMAB-442. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×

NRC (National Research Council). 1987. Control of Welding Processes. NMAB-421. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

NRC (National Research Council). 1989a. On-Line Control of Metals Processing. NMAB-444. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

NRC (National Research Council). 1989b. Intelligent Process Control Systems for Materials Heat Treatment. NMAB-457. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

NRC (National Research Council). 1992. Opportunities in Attaining Fully-Integrated Processing Systems. NMAB-461. National Materials Advisory Board, NRC. Washington, D.C.: National Academy Press.

Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×
Page 108
Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×
Page 109
Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×
Page 110
Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×
Page 111
Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×
Page 112
Suggested Citation:"APPENDIX C: AN ILLUSTRATIVE SENSOR TAXONOMY." National Research Council. 1995. Expanding the Vision of Sensor Materials. Washington, DC: The National Academies Press. doi: 10.17226/4782.
×
Page 113
Next: APPENDIX D: SENSOR TECHNOLOGY FOR MONITORING POLYMER CURING »
Expanding the Vision of Sensor Materials Get This Book
×
Buy Paperback | $48.00 Buy Ebook | $38.99
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

Advances in materials science and engineering have paved the way for the development of new and more capable sensors. Drawing upon case studies from manufacturing and structural monitoring and involving chemical and long wave-length infrared sensors, this book suggests an approach that frames the relevant technical issues in such a way as to expedite the consideration of new and novel sensor materials. It enables a multidisciplinary approach for identifying opportunities and making realistic assessments of technical risk and could be used to guide relevant research and development in sensor technologies.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    Switch between the Original Pages, where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

    « Back Next »
  6. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  7. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  8. ×

    View our suggested citation for this chapter.

    « Back Next »
  9. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!