Distributed Functionalities

Most machines/systems have a lumped characteristic in that they possess sensor actuators and controllers at discrete locations. It is desirable for machines/systems to have distributed characteristics that would allow them to obtain the necessary information distributed spatially and generate necessary actions according to this distributed configuration.

Embedding sensors and actuators into some delicate parts or structures of a machine or system is one way of monitoring and controlling its dynamic state.

In Figure 1.44, a smart structure or skin is shown, which can easily be embedded into systems. Here, the optical sensor layers provide some information needed to generate an action by actuators that are also embedded into the structure with sensors, controllers, and electronic components. Optical tactile sensors embedded in the fingers of a robot and so-called “smart structures” such as aircraft and concrete infrastructure are typical examples, as indicated in the figure [Rogers, 1995].

FIGURE 1.42 Omni-directional vision for assembly.

FIGURE 1.43 Fine track searching for optical disk.

1.6.6 Miniaturization

Inspection or measurement of very small closed areas is often very difficult due to the dimension problem of the sensing and actuating units. Micro sizing of such machines or systems can be achieved with the aid of inherent optical sensing. A micromachine that inspects the inner surface of tubes in complex piping systems such as power plants is shown in Figure 1.45 [Tsuruta, 1999]. The machine consists mainly of a micro-CCD camera (10 mm in diameter) for visual inspection, a piezoelectric driving actuator, and microwave-based energy supply and data transmission devices. It can travel in a straight and curved metal tube with a minimum diameter of 10 mm.

1.7 Summary

In recent years, integration of optical elements into mechatronic systems has been accelerated because it produces a synergistic effect, creating new functionalities for the systems or enhancing the performance of the systems. This trend will certainly be the future direction of mechatronic technology and will contribute to the advent of a new technological paradigm.

This chapter has focused on helping readers understand mechatronic technology and opto-mechatronic systems, in which optical, mechanical electrical/electronics, and information engineering tech-nologies are integrated. In particular, the definition and fundamental concepts of the technology were established. Using these concepts, it was possible to identify different types of opto-mechatronic systems, depending on how their component technologies were integrated and organized together to produce their FIGURE 1.44 Smart skin or structures.

FIGURE 1.45 Micromachine for pipe inspection. (From Tsuruta, K. et al., Sensor Rev., 19, 37–42, 1999. With permission.)

basic functions. The fundamental functions that can be created by the integration were described by defining and illustrating them from a number of practical systems currently being used. A total of 17 functions were identified. Finally, the synergistic effects that can be achieved because of the integration were identified to be:

1. Creating new functionalities, thus adding them to the existing one 2. Increasing the level of autonomy and intelligence

3. Achieving high performance 4. Enhancing the level of functionality

5. Achieving a variety of features such as precision, low cost, robustness, distributed aspect, minia-turization, etc.

Future developments of technologies such as mechatronics, instrumentation and control, MEMS, and biosystems as well as information processing and storage and communication aim at achieving these characteristic effects. Therefore, opto-mechatronics is becoming a prime moving technological element that will dictate the future direction of various technologies.

Defining Terms

distributed function: System function that is generated in a spatially distributed fashion (e.g., smart structure, image acquisition of a CCD camera, etc.).

MOEMS: Micro-optical electron mechanical system.

ODD: Optical device drive.

optical pattern recognition: Optical means of processing optical images and then recognizing patterns or objects based on the processed results.

optical polarization: An optical process that makes the orientation of the electric field of light depen-dent only on spatial coordinates, although its magnitude and sign vary in time.

optical switch: Optical device that can direct light from one fiber to another.

opto-mechatronic technology: Technology that creates a synergistic integration of optical elements with mechatronic ones.

opto-mechatronically-fused system: System in which optical or mechatronic elements are not separa-ble from the system to achieve a certain function.

sensor fusion: A fusion technique that can fuse the information obtained by multiple sensors.

tunable laser: Laser whose wavelength can be tuned.

References

Anderson, S. G., Smart cars take the high-tech road, Laser Focus World, 32(6), 117–123, 1996.

Andonovic, I. and Uttamchandani, D., Principles of Modern Optical Systems, Artech House, Norwood, MA, 1989.

Backmutsky, V. and Vaisman, G., Theoretical and experimental investigation of new mechatronic scanners, in Proc. IEEE 19th Convention Electrical Electron. Engineers Israel, Israel, 1996, pp. 363–366.

Borenstein, J., Experimental evaluation of a fiber optics gyroscope for improving dead-reckoning accuracy in mobile robots, in Proc. IEEE Int. Conf. Robotics Automation, Vol. 4, Leuven, Belgium, 1998, pp. 3456–3461.

Butler, C. and Yang, Q., A fibre-optic three-dimensional analog probe for component scanning on coordinate-measuring machines, Sensor Actuator A, 37–38, 473–479, 1993.

Cannon Co., http://www.canon.com, 2002.

Chen, M. and Hollis, R., Vision-guided precision assembly, http://www-2.cs.cmu.edu/afs/cs/project/msl/

www/tia/tia_desc.html, 1999.

Cho, H. S. and Park, W. S., Determining optimal parameters for stereo-lithography process via genetic algorithm, Manuf. Sys. J., 19(1), 18–27, 2000.

Ebisawa, Y., Ohtani, M., and Sugioka, A., Proposal of a zoom and focus control method using an ultrasonic distance-meter for video-based eye-gaze detection under free-head conditions, 18th Annu. Conf.

IEEE Eng. Med. Biol. Soc., Amsterdam, the Netherlands, 2, 1996.

Fukuda, T., Hattori, S., Arai, F., Matsuura, H., Hiramatsu, T., Ikeda, Y., and Maekawa, A., Characteristics of optical actuator-servomechanisms using bimorph optical piezo-electric actuator, Proc. IEEE Int.

Conf. Robotics Automation, 2, 618–623, 1993.

Geppert, L., Semiconductor lithography for the next millennium, IEEE Spectrum, 33–38, April 1996.

Han, K., Kim, S., Kim Y., and Kim, J., Internet control architecture for internet-based personal robot, Autonomous Robots, 10, 135–147, 2001.

Haran, F. M., Hand, D. P., Peters, C., and Jones, J. D. C., Real-time focus control in laser welding, Measurement Sci. Technol., 7, 1095–1098, 1996.

Higgins, T. V., Optical storage lights the multimedia future, Laser Focus World, 31(9), 103–111, 1995a.

Higgins, T. V., Computing with photons at the speed of light, Laser Focus World, 31(12), 72–77, 1995b.

Ishi, T., Future trends in mechatronics, JSME Int. J., 33(1), 1–6, 1990.

Jeong, H. M., Choi, J. J., Kim, K. Y., Lee, K. B., Jeon, J. U., and Pak, Y. E., Milli-scale mirror actuator with bulk micromachined vertical combs, Proc. Transducer, Sendai, Japan, 1999, pp. 1006–1009.

Kamiya, M., Ikeda, H., and Shinohara, S., Data collection and transmission system for vibration test, Proc.

Ind. Appl. Conf., 3, 1679–1685, 1998.

Kayanak, M. O., The age of mechatronics, IEEE Trans. Ind. Electron., 43(1), 2–3, 1996.

Kim, W. S. and Cho, H. S., A novel sensing device for obtaining an omnidirectional image of three-dimensional objects, Mechatronics, 10, 717–740, 2000.

Kim, J. S. and Cho, H. S., A robust visual seam tracking system for robotic arc welding, Mechatronics, 6(2), 141–163, 1996

Kim, W. S. and Cho, H. S., A novel omnidirectional image sensing sytem for assembling parts with arbitrary cross-sectional shapes, IEEE/ASME Tran. Mechatronics, 3(4), 275–292, 1998.

Ko, K. W., Cho, H. S., Kim, J. H., and Kong, W. I., A bead shape classification method using neural network in high frequency electric resistance weld, Proc. World Automation Congr., Anchorage, Alaska, 1998.

Krupa, T. J., Optical R&D in the army research laboratory, Optics Photonics News, 16–39, June 2000.

Larson, M. C., Tunable optoelectronic devices, http://www-snow.stanford.edu/~larson/research.html, 2000.

Larson, M. C. and Harris, J. S., Wide and continuous wavelength tuning in a vertical cavity surface emitting laser using a micromachined deformable membrane mirror, Appl. Phys. Lett., 68, 893, 1996.

Lim, T. G. and Cho, H. S., Estimation of weld pool sizes in GMA welding process using neural networks, Proc. Inst. Mech. Engineers, 207, 15–26, 1993.

Mahr Co., Multiscope 250/400, http://www.mahr.com/en/content/products/mess/mms/ms250.html, 2001.

McCarthy, D. C., Hands on the wheel, cameras on the road, Photonics Spectra, 78–82, April 2001.

McDonald, T. G. and Yoder, L. A., Digital micromirror devices make projection displays. Imaging Hand-book, supplement to Laser Focus World, 33(8), 55–58, 1997.

McKee, G., Robotics and machine perception, SPIE Int. Tech. Group Newslett., 9(2), 1–11, 2000.

Mitutoyo Co., Quick Vision, http://www.mitcat.com/e-02.htm, 2001.

Park, I. O., Cho, H. S., and Gweon, D. G., Development of programmable bowl feeder using a fiber optic sensor, 10th Int. Conf. Assembly Automation, Tokyo, Japan, 1989.

Park, W. S., Cho, H. S., Byun, Y. K., Park, N. Y., and Jung, D. K., Measurement of three-dimensional position and orientation of rigid bodies using a 3-facet mirror, SPIE Int. Symp. Intelligent Sys.

Advanced Manuf., Boston, MA, 1999, Vol. 3835, pp. 2–13.

Pugh, A., Robot Sensors, Vol. 2, Tactile and Non-Vision, Springer-Verlag, Berlin, 1986.

Robinson, S. D., MEMS technology—micromachines enabling the “all optical network,” Electron. Com-ponents Technol. Conf., Orlando, FL, June 2001, pp. 423–428.

Rogers, C. A., Intelligent materials, Sci. Am., 122–127, September 1995.

Roh, Y. J., Cho, H. S., and Kim, J. H., Three-dimensional volume reconstruction of an object from x-ray images, Conf. SPIE Opto-Mechatronic Syst., part of Intelligent Systems Advanced Manuf., Boston, MA, 2000, Vol. 4190, pp. 181–191.

Shin, S. H. and Javidi, B., Three-dimensional object recognition by use of a photorefractive volume holographic processor, Optics Lett., 26(15), 1161–1163, 2001.

Shiraishi, M., In-process control of workpiece dimension in turning, Ann. CIRP, 28(1), 333–337, 1979.

Takamasu, K., Development of a nano-probe system, Q. Mag. Micromachine, 35, 6, May 2001.

Toshiyoshi, H., Su, J. G., LaCosse, J., and Wu, M. C., Micromechanical lens scanners for fiber optic switches, Proc. 3rd Int. Conf. Micro Opto Electro Mechanical Sys., MOEMS ’99, August, Mainz, Germany, 1999, pp. 165–170.

Tsuruta, K., Mikuriya, Y., and Ishikawa, Y., Micro sensor developments in Japan, Sensor Rev., 19, 37–42, 1999.

Veeco Co., http://www.tmmicro.com/tech/modes/contact.htm, 2000.

Wakami, N., Nomura, H., and Araki, S., Fuzzy logic for home appliances, in Fuzzy Logic and Neural Networks, McGraw-Hill, New York, 1996, pp. 21.1–21.23.

Wilson, A., Machine vision speeds robot productivity, Vision Systems Design, October 2001.

Woo, H. G. and Cho, H. S., Estimation of hardened layer dimensions in laser surface hardening processes with variations of coating thickness, Surface Coatings Technol., 102(3), 205–217, 1998.

Zankowsky, D., Applications dictate choice of scanner, Laser Focus World, 32(12), 99–105, 1996.

Zhang, J. H. and Cai, L., An autofocusing measurement system with a piezoelectric translator, IEEE/ASME Trans. Mechatronics, 2(3), 213–216, 1997.

Zhou, Y., Nelson, B. J., and Vikramaditya, B., Integrating optical force sensing with visual servoing for microassembly, J. Intelligent Robotic Sys., 28, 259–276, 2000.

2.2 Traditional vs. Opto-Mechatronic Designs

2.3 Opto-Mechatronic Design Process

Identification of Need and Design Specifications • Concept Generation and Evaluation • Detail Development and Evaluation

2.4 Opto-Mechatronic Technologies

Optical Transducers

2.5 Applications of Opto-Mechatronic Systems

Automatic Camera • Intelligent Washing Machine • Optical Implementation of a SISO Rule-Based Controller

2.6 Conclusions

2.1 Introduction

As an engineering discipline, mechatronics strives to optimally integrate mechanical, electronic, and computer technologies in order to create innovative products and processes. Optical sensors and actuators are being incorporated at an accelerated rate into mechatronic systems because these lightwave technologies provide components for high precision, rapid data processing, flexible circuits, and circuit miniaturization.

Opto-mechatronics, a subset of mechatronic system design, focuses on the tools and technologies needed to create intelligent systems from optical transducers and embedded control systems.

At first glance the concept of opto-mechatronics may appear to duplicate the goals of the more established area of opto-mechanics, but this is a false impression. The role of opto-mechanical design is to maintain the proper shapes and positions of the various optical components that comprise precision instruments such as telescopes, microscopes, metrology instruments, and eyeglasses [Ahmed, 1997].

By contrast, opto-mechatronics stresses technology integration for enhanced system performance.

Starting with a clear problem definition and continuing through to product manufacture, the opto-mechatronic design process works toward the efficient utilization of available technologies to produce quality systems in a timely manner with features the customer wants. In essence, it is not a specific technology but rather a design philosophy that promotes the creation of high-quality “smart” products and process.

The difference between an opto-mechatronic approach and a more traditional systems engineering approach to design is not the constituent parts that embody the solution; rather, it is the method in which the various components are developed. Most complex systems are created using sequential design practice, where the roles of the various engineering disciplines are well defined and, often, narrow in George K. Knopf

University of Western Ontario London, Ontario, Canada

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