Self-adaptive PCA model establishment method and ultrasonic machining partial discharge detection method

Abstract

The invention relates to a self-adaptive PCA (Principal Component Analysis) model establishment method. A self-adaptive outlier elimination method is added into a traditional PCA model, the distance square of a projection vector-residual vector of training data in a residual space and a monitoring limit threshold are used as outlier detection bases, namely when the principal component analysis Q statistical magnitude of certain sampling data is higher than the monitoring limit threshold, the data is considered to be abnormal and determined to be an outlier and should be eliminated from a training matrix, abnormal data in all cycles is eliminated by adopting a self-adaptive cycle method, and the training matrix is repeatedly compressed until the monitoring index Q statistical magnitudes of all the samples of the training matrix are lower than the threshold. Meanwhile, the invention further relates to an ultrasonic machining partial discharge detection method based on self-adaptive PCA. The threshold of the monitoring index Q statistical magnitude is greatly reduced through outlier elimination, gross error data caused by partial discharge in the ultrasonic machining process can be well detected, the detection sensitivity and the detection efficiency are improved, and the performance of ultrasonic equipment is reflected in time.

Description

technical field [0001] The invention belongs to the field of partial discharge detection in ultrasonic machining, in particular to a method for detecting partial discharge in ultrasonic machining based on an adaptive principal component analysis (Principal Component Analysis, PCA). Background technique [0002] Ultrasonic vibration machining technology is famous for its typical intermittent machining principle, that is, the tool has a contact separation process between the workpiece and the tool within one cycle. The characteristics of high-frequency periodic separation make ultrasonic machining have the advantages of small average cutting force, high processing efficiency, and good surface processing quality. Ultrasonic vibration machining covers a wide range of applications, mainly including rotary ultrasonic machining, ultrasonic cutting, milling, and grinding. In the context of the maturity of high-power ultrasonic processing technology, the partial discharge problem of...

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Problems solved by technology

The useless residual information of these outliers makes the control limit of the Q statistic, also known as the squared prediction error (Squared Prediction Error, SPE), higher than its true control limit, resulting in low detection efficiency and sensitive detection of small-scale partial discharges. poor sex

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