A kind of mechanical fault detection and diagnosis method and its equipment

Abstract

The invention discloses a method for detecting and diagnosing mechanical faults. The specific steps are as follows: installing a plurality of mechanical vibration sensors on the detected mechanical equipment; separately collecting vibration signals of the mechanical equipment in normal operation and operating under different fault type conditions; generating SVM classification rules for mechanical fault detection; train the SVM trainer and adjust the training rules of the SVM trainer; collect mechanical vibration signals through the vibration sensor, and perform preliminary fault detection by the SVM classifier; apply the multi-sample voting algorithm to the preliminary detection The results of voting are analyzed to obtain the final fault detection results. A mechanical fault detection device is characterized in that it includes an SVM trainer and a plurality of mechanical vibration signal acquisition sensors. A mechanical fault detection and diagnosis method and its equipment proposed by the present invention ensure the accuracy of the detection results, can detect and identify typical mechanical faults, and can adapt to the detection and identification of various types of mechanical equipment with different performance characteristics. Fault detection and diagnosis, improving the accuracy of mechanical fault detection.

Description

technical field [0001] The invention relates to a mechanical fault detection method and detection equipment thereof. Background technique [0002] At present, there are many mechanical fault diagnosis methods, including static-based mechanical fault diagnosis methods and dynamic mechanical fault diagnosis methods. Among them, the mechanical fault detection method that takes mechanical vibration as the detection object is currently a new method in the field of mechanical fault detection. Mainstream method. However, the accuracy of fault diagnosis and the type of fault identification based on mechanical vibration fault detection methods largely depend on the analysis and processing capabilities of mechanical vibration signals. At present, most of the existing mechanical fault diagnosis methods focus on the acquisition and analysis algorithms of mechanical vibration signals, which also include a large number of different transformations or signal conversions for the collected ...

AI Technical Summary

Problems solved by technology

However, the current series of typical mechanical fault diagnosis methods, the fault time and diagnosis algorithm designed by them largely depend on statistical or probability analysis, and there is no clear basis for fault identification.

Because of this, the current mechanical fault detection methods have strong limitations, that is, for different scenarios and different detection objects, the ability and effect of fault detection often vary greatly.

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