Three-sensor tracing principle for crankshaft roundness error measurement during noncircular grinding process

Yingzhong Tian; Ming Li; Wei Li; Zhiliang Yao; Minglun Fang

doi:10.1117/12.717156

24 October 2006 Three-sensor tracing principle for crankshaft roundness error measurement during noncircular grinding process

Yingzhong Tian, Ming Li, Wei Li, Zhiliang Yao, Minglun Fang

Author Affiliations +

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 63572D (2006) https://doi.org/10.1117/12.717156
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

Researches are made to find out the active tracing measurement strategy of crankshaft roundness error during noncircular grinding process. This paper makes a detailed study on the tracing motion equations of the measurement system. Aiming at the request of three sensors' linear dependence in frequency-domain analysis, this paper also describes the constraint condition of uniform sampling. For improve the in-situ measurement precision, the three-sensor tracing principle of roundness error separation (TTPRES) is proposed under motion stage. Furthermore, the method for avoiding harmonic suppression by adjusting the installation angles of three sensors is discussed. Finally, the data processed by error separating are calculated using Least Square Method (LSM), and contrasted the compute result with the measurement result of Roundness Measuring Instrument. The experiment proves the validity of in-situ tracing measurement strategy of crankshaft roundness error during noncircular grinding process.

Citation Download Citation

Yingzhong Tian, Ming Li, Wei Li, Zhiliang Yao, and Minglun Fang "Three-sensor tracing principle for crankshaft roundness error measurement during noncircular grinding process", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63572D (24 October 2006); https://doi.org/10.1117/12.717156

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