Fault diagnosis method, device and computer equipment

Abstract

The present invention proposes a fault diagnosis method, device, and computer equipment, wherein the method includes: acquiring first operating data of the equipment to be diagnosed, the first operating data including the continuous time period of each sensor in the equipment to be diagnosed The detection data within; use the trained convolutional neural network to process the first operating data, and determine the fault type, fault location and fault time of the equipment to be diagnosed. As a result, when the equipment to be diagnosed is running, fault diagnosis can be performed in real time according to the operating data of the equipment to be diagnosed, which improves the timeliness and efficiency of fault diagnosis, and the diagnosis process does not require professional technicians to operate, reducing labor costs .

Description

technical field [0001] The invention relates to the technical field of computers, in particular to a fault diagnosis method, device and computer equipment. Background technique [0002] With the development of science and technology, electric power, electronics and other equipment are more and more widely used, and they occupy an increasingly important position in people's life, study and work. If the equipment fails, it will cause serious damage to people's normal work, study or life. huge impact. Therefore, it is of great significance to carry out fault diagnosis on equipment. [0003] The existing fault diagnosis methods usually analyze the fault codes reported by the equipment after the fault occurs, so as to perform fault diagnosis and take corresponding measures according to the diagnosis results. In this way, the equipment fault cannot be found in time, and the fault diagnosis The efficiency is low, and the diagnosis process requires professional technicians to oper...

AI Technical Summary

Problems solved by technology

[0003] The existing fault diagnosis methods usually analyze the fault codes reported by the equipment after the fault occurs, so as to perform fault diagnosis and take corresponding measures according to the diagnosis results. In this way, the equipment fault cannot be found in time, and the fault diagnosis The efficiency is low, and the diagnosis process requires professional technicians to operate, which has high requirements for operators and high labor costs

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