A Method for Accurately Locating Equipment Faults

Abstract

The invention relates to an equipment fault accurate positioning method. The method comprises the following steps of obtaining equipment detection data, calculating to obtain equipment monitoring values based on the equipment detection data, comparing the equipment monitoring values with the normal operation data of equipment, judging the operation state of equipment, and recording abnormal data;recognizing the part to which the abnormal data belongs, comparing the abnormal data with a fault database of the part to which the abnormal data belongs, and recognizing a fault; pushing the recognized fault to the monitoring personnel, extracting corresponding maintenance suggestions from a maintenance database and pushing the fault and the suggestions to the monitoring personnel; judging whether the recognition is correct or not after the maintenance is finished; if the recognition is correct, inputting the fault data into the fault database, marking the data to be correctly recognized, adopting the data as reference data for machine learning, and ending the positioning; otherwise, inputting the fault data into the fault database, marking the data to be wrongly recognized, adopting thedata as reference data for machine learning, and ending the positioning.

Description

technical field [0001] The invention relates to the field of equipment detection, in particular to a method for accurately locating equipment faults. Background technique [0002] The mainstream method of fault detection for existing mechanical equipment is PHM (failure prediction and health management technology). PHM mainly uses 1) model-based fault prediction technology; 2) data-driven fault prediction technology; 3) fault prediction based on statistical reliability technology. In the field of power stations, it is mainly used in wind power generation. Ultrasonic waves are used to detect the vibration status of generator sets, and then equipment faults can be inferred through abnormal vibration values. However, in the field of hydroelectric power generation, due to the complexity of hydroelectric generating units is much higher than that of wind turbines, coupled with the excessive noise of water flow, it is impossible to use the same technology for equipment detection, ...

AI Technical Summary

Problems solved by technology

However, in the field of hydropower generation, due to the complexity of hydroelectric generating units is much higher than that of wind turbines, coupled with the excessive noise of water flow, it is impossible for hydroelectric generating units to use the same technology for equipment detection, let alone locate equipment faults

[0003] Troubleshooting and repairing of existing hydroelectric generating units still only depends on dismantling the entire equipment and manually inspecting and repairing, which will not only take a lot of time and maintenance costs, but also cause hidden huge economic losses due to the reduction of power supply due to long-term shutdown

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