Method for performing equipment diagnosis based on sound features and temperature features

Abstract

The invention discloses a method for performing equipment diagnosis based on sound features and temperature features. The method comprises: sound and temperature signal collection, signal processing,preliminary feature judgment, sound spectrum analysis, deep feature judgment, sound signal single-point continuous collection, fault equipment determine, and result output and storage. According to the method for performing equipment diagnosis based on sound features and temperature features, fault diagnosis of the equipment is performed in combination with the deep level sound spectrum analysis and the temperature feature judgment, the diagnosis process is simple, the diagnosis effect is accurate, and fault monitoring points can be accurately determined. The diagnostic system adopts a wireless connection, the units are modular in design, so that the software has good compatibility and function expansion functions and has better intelligent analysis and self-learning functions with the accumulation of data.

Description

technical field [0001] The invention relates to the technical field of equipment diagnosis, in particular to a method for equipment diagnosis based on sound features and temperature features. Background technique [0002] During the normal operation of logistics equipment, the temperature range, sound intensity and sound frequency of each operating position (such as drive motor, module drive belt, conveyor belt, etc.) will remain within a certain range during normal operation. When the equipment is abnormal, there will be abnormal temperature values, and changes in the intensity and frequency of the sound. In the prior art, there is wireless collection and processing based on mechanical vibration and temperature, so as to diagnose the abnormality of automatic equipment, but the way of judging the status of equipment based on the characteristics of mechanical vibration needs to be close to the vibration source, which cannot adapt to the complex working scene of logistics equi...

AI Technical Summary

Problems solved by technology

In the prior art, there is wireless collection and processing based on mechanical vibration and temperature, so as to diagnose the abnormality of automatic equipment, but the way of judging the status of equipment based on the characteristics of mechanical vibration needs to be close to the vibration source, which cannot adapt to the complex working scene of logistics equipment; the existing In the technology, there are also automatic equipment abnormal diagnosis based solely on the characteristics of noise loudness, but due to the complex on-site environment, it is impossible to distinguish complex sound feature interference

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