Coal mill coal blockage fault judgment and fault self-healing method and system

Abstract

The invention discloses a coal mill coal blockage fault judgment and fault self-healing method, which comprises the following steps of: extracting and calculating working state data of a coal mill, judging whether coal blockage occurs or not through coal blockage fault judgment logic, sending out a sound-light alarm when coal blockage occurs, and automatically processing according to the existing fault self-healing logic. According to the invention, a plurality of working state data can be comprehensively judged, fault reasons can be given, self-healing can be carried out in time when faults occur, time is bought for accident handling, fault expansion is effectively avoided, and the maintenance cost is reduced. The invention also discloses a coal mill coal blockage fault judgment and fault self-healing system, which can diagnose a plurality of working state data of the coal mill according to a preset coal blockage fault judgment logic, judge whether a coal blockage fault occurs or not, return a monitoring interface to the mobile terminal module and receive monitoring information sent by a WEB module in real time; The coal mill coal blockage fault judgment and fault self-healing method is high in automation degree, and greatly improves the alarm accuracy and reliability of the system.

Description

Technical field: [0001] The invention relates to the field of coal mill monitoring, in particular to a coal mill coal blocking fault judgment and fault self-healing method and system. Background technique: [0002] The coal pulverizer is a machine that breaks coal and grinds it into pulverized coal. It is an important auxiliary equipment for pulverized coal furnaces and the key equipment to ensure the long-term operation of pulverized coal furnaces. Therefore, it is necessary to monitor the operation status of coal pulverizers. , Once the coal mill fails, it needs to be dealt with in time. At present, the commonly used coal mill monitoring system only sets up individual monitoring equipment at each monitoring point. When the monitored data exceeds the preset value, it will alarm. The system cannot directly give the cause of the failure, and the staff needs to make their own judgments based on work experience. The requirements for the working experience of the staff are high...

AI Technical Summary

Problems solved by technology

At present, the commonly used coal mill monitoring system only sets up individual monitoring equipment at each monitoring point. When the monitored data exceeds the preset value, it will alarm. The system cannot directly give the cause of the failure, and the staff needs to make their own judgments based on work experience. The requirements for the working experience of the staff are high, and there is a possibility of misjudgment; and it takes time for the staff to make a judgment, which makes it impossible to carry out maintenance in time, and often misses the best time to deal with the fault; at the same time, there is a single feature extraction , it is impossible to make a comprehensive judgment, which makes the system have a high rate of false alarms and poor reliability; in addition, the current monitoring system does not have the function of self-healing of faults, the degree of automation is low, and a large amount of manpower is required for maintenance

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