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Motor fault prediction method based on grey model and big data processing

A big data processing and fault prediction technology, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve problems such as difficulty in combination, improve accuracy and effectiveness, facilitate maintenance, and save labor The effect of the steps reviewed

Pending Publication Date: 2022-02-15
成都擎熵数据技术有限公司
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Problems solved by technology

Statistical probability speculation, intelligent neural network and gray theoretical mathematical model have always been the key research methods, but these methods have their own advantages and disadvantages and are difficult to combine

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  • Motor fault prediction method based on grey model and big data processing

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Embodiment Construction

[0029] The technical characteristics of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0030] This application is a motor fault prediction method based on gray model and big data processing, including the following steps:

[0031] 1) Query the data about motor operation in the large database, obtain all types of motor operation faults and obtain abnormal data of motor status monitoring that cause different types of motor operation faults, and perform statistics on the obtained data;

[0032] 2) According to the data obtained in step 1), calculate the possibility weights of various motor status monitoring abnormal data leading to motor operation failures and form a motor failure weight matrix;

[0033] 3) Establish the gray model of motor fault prediction and the fuzzy judgment rules of motor fault prediction;

[0034] 4) Monitor the running state of the motor, detect the real-time detection data ...

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Abstract

The invention discloses a motor fault prediction method based on a grey model and big data processing. The method comprises the following steps: 1) querying data about motor operation in a big database, obtaining all motor operation fault types, obtaining motor state monitoring abnormal data causing different motor operation fault types, and carrying out statistical arrangement on the obtained data; 2) according to the data obtained in the step 1), calculating possibility weights of motor operation faults caused by various motor state monitoring abnormal data, and forming a motor fault weight matrix; and 3) establishing a gray model for motor fault prediction and a fuzzy decision rule for motor fault prediction. The motor fault prediction method has the advantages that gray model prediction and fuzzy prediction are combined, data inaccuracy caused by single model prediction is prevented, and prediction precision and effectiveness are improved.

Description

technical field [0001] The invention relates to a motor fault prediction method based on a gray model and big data processing, which belongs to the field of electrical equipment. Background technique [0002] Motor predictive maintenance is condition-based maintenance. When the motor is running, conduct regular (or continuous) state monitoring and fault diagnosis on its main parts, determine the state of the motor, predict the future development trend of the motor state, and according to the state development trend of the motor and possible failure modes, Make a predictive maintenance plan in advance to determine the time, content, method and necessary technical and material support for the motor to be repaired. Motor predictive maintenance integrates motor condition monitoring, fault diagnosis, condition prediction, maintenance decision support and maintenance activities, and is an emerging maintenance method. Fault prediction technology can provide a better theoretical d...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/00G06F16/2455G06F16/2458G06F17/18G06K9/62G06N7/02G06F17/13G06F17/16
CPCG06Q10/04G06Q10/20G06F16/2465G06F16/2462G06F16/24564G06F16/2477G06N7/02G06F17/18G06F17/13G06F17/16G06F18/23
Inventor 向红先
Owner 成都擎熵数据技术有限公司
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