Development and calibration of a cost-effective piezo-electric industrial dynomometer
Force is one of the major key parameters in a cutting process. The measurement of this parameter allows for assessment of the machining operation as well as to monitor tool condition (wear, breakage, etc.) and machine errors (looseness, backlash, etc.). The low cost option for measuring force in man...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2018
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Online Access: | http://hdl.handle.net/10356/73283 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Force is one of the major key parameters in a cutting process. The measurement of this parameter allows for assessment of the machining operation as well as to monitor tool condition (wear, breakage, etc.) and machine errors (looseness, backlash, etc.). The low cost option for measuring force in manufacturing is to use a load cell which is based on strain gauges. This technology has two drawbacks; firstly, strain gauges are not sensitive enough compared to other technologies and will not detect subtle changes in the cutting forces. Secondly, due to their design, load cells are mounted far from the cutting tool which means that the measured force will be not be representative of the actual cutting force. In the research environment, dynamometers are the most common technology that is used for measuring cutting forces in machine tools due to their high sensitivity. These dynamometers can also be mounted directly to the tool holders. They are based on four piezo-electric sensors which are preloaded between top and bottom plates like a sandwich. This dynamometer technology has not found its way into the production line, as it is relatively expensive (around 50,000 Singapore Dollars). Research is going on to develop a similar design of these dynamometers based on a single force sensor. The use of one sensor means that a calibration with a real dynamometer should be performed. In this project a force is applied using a robot arm on the customized dyno and then the readings recorded arc utilized to calibrate and compare them. In this research study, calibration is achieved using the least squares method and artificial neural networks followed by further analyses. |
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