| Summary: | 碩士 === 中原大學 === 機械工程研究所 === 100 === This article surface grinder vibration signal, monitoring the distribution of machine spindle vibration for the quality of the state of completion of the grinding process. Statistical parameters of the completion of the finished product analysis, the effects of different parameters and conditions to adjust the detection and warning of abnormal conditions, so that the processing of personnel to take contingency measures to eliminate abnormal process to restore the stability of the process.
Vibration signal is sampled to accelerate scale group, built on a surface grinder spin
-dle retrieve the complete grinding vibration signal statistical parameters extracted from the characteristics of the distribution of values, such as waveform, peak margin, kurtosis and skewness eigenvalue establish training samples, calculate it covariance matrix as classification tools, as by the theory of Bayesian classification basis, completion quality state classification, and the establishment of the completion of the quality status of the training samples in the database.
Information before processing part, Accelerometers filtering algorithm has been built on the system module, Bayesian classification module as a classification basis is based on the Lab VIEW front panel, the part of it grinding completion state HMI display, user will be friendly and understand for the grinding completion of the quality status.
Grinding experimental results can distinguish the quality of the different state of completion, such as mirror、matte、flutter pattern、scrapes and burns, use this grinding completion status classification to achieve will be quality control, and stable process、to improve the yield rate and possibility.
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