Networking of Sensors and Control Systems in Manufacturing in Software

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Networking of Sensors and Control Systems in Manufacturing
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FIGURE 4.1
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Flexible machining cell.
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After the data have been distilled into information, the deductive process begins, leading finally to the fault diagnosis. Expert systems have been used effectively for diagnostic efforts, with the diagnostic system presenting either a single diagnosis or a set of possibilities with their respective probabilities, based on the a priori and a posteriori information.
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4.7.2 Resonance and Vibration Analysis
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Resonance and vibration analysis is a proven method for diagnosing deteriorating machine elements in steady-state process equipment such as turbomachinery and fans. The effectiveness of resonance and vibration analysis in diagnosing faults in machinery operating at variable speed is not proven, but additional study has indicated good potential for its application in robots. One difficulty with resonance and vibration analysis is the attenuation of the signal as it travels through a structure on the way to the sensors and transducers. Moreover, all motion of the machine contributes to the motion measured by the sensors and transducers, so sensors and transducers must be located as close as possible to the component of concern to maximize the signal-to-noise ratio.
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Sensing Motor Current for Signature Analysis
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Electric motors generate back electromotive force (emf) when subjected to mechanical load. This property makes a motor a transducer
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for measuring load vibrations via current fluctuations. Motor current signature analysis uses many of the same techniques as vibration analysis for interpreting the signals. But motor current signature analysis is nonintrusive because motor current can be measured anywhere along the motor power cables, whereas a vibration sensor or transducer must be mounted close to the machine element of interest. The limited bandwidth of the signals associated with motor drive signature analysis, however, may restrict its applicability.
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4.7.4 Acoustics
A qualified operator can tell from the machine-generated noise that a fault is developing. Consequently, It is natural to extend this concept to automatic diagnosis. The operator has access to subtle innate pattern recognition techniques, and thus is able to discern sounds from myriad background noises. Any diagnostic system based on sound would have to be able to identify damage-related sounds and separate the information from the ambient noise. Acoustic sensing (looking for sounds that indicate faults) is a nonlocal noncontact inspection method. Any acoustic technique is subject to outside disturbances, but is potentially a very powerful tool, provided that operating conditions are acoustically repeatable and that the diagnostic system can effectively recognize acoustic patterns.
4.7.5 Temperature
Using temperature as a measurement parameter is common, particularly for equipment running at high speed, where faults cause enough waste heat to raise temperature significantly. This method is generally best for indicating that a fault has occurred, rather than the precise nature of the fault.
Sensors for Diagnostic Systems
Assuming an automated diagnostic system is required, the necessary sensors are normally mounted permanently at their monitoring sites. This works well if data are required continuously, or if there are only a few monitoring locations. However, for those cases where many sites must be monitored and the data need not be continuously received during operation of the flexible manufacturing cell, it may be possible to use the same sensor or transducer, sequentially, in the many locations. The robot is well-suited to gathering data at multiple points with a limited number of sensors and transducers. This would extend the mandate of the robot from simply moving workpieces and tools within the flexible manufacturing cell (for production) to include moving sensors (for diagnostic inspection). Within the flexible manufacturing cell, a robot can make measurements at sites inside its work space by taking a sensor or transducer
Networking of Sensors and Control Systems in Manufacturing
from a tool magazine, delivering the sensor or transducer to a sensing location, detaching it during data collection, and then retrieving it before moving to the next sensing position. Sensor mobility does, however, add some problems. First, the robot will not be able to reach all points within the flexible manufacturing cell because its work space is only a subspace of the volume taken up by the flexible manufacturing cell. The manipulator may be unable to assume an orientation desired for a measurement even inside its workspace. Also, the inspection procedure must limit the robot s influence on the measurement as much as possible. Finally, sensors require connectors on the robot end effectors for signals and power. The end effector would have to be able to accommodate all the types of sensors to be mounted on it.
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