CN-122022007-A - Hydraulic facility fault prediction system and method

CN122022007ACN 122022007 ACN122022007 ACN 122022007ACN-122022007-A

Abstract

The application provides a system and a method for predicting faults of water conservancy facilities, and relates to the technical field of water conservancy facilities, wherein the method comprises the steps of constructing a digital twin body based on equipment parameters; the method comprises the steps of obtaining a first detection parameter output by a digital twin body based on an operation parameter, setting an abnormal deviation threshold based on equipment parameters and the operation parameter, obtaining a second detection parameter output by the equipment, judging whether a difference value between the first detection parameter and the second detection parameter exceeds the abnormal deviation threshold, ending when judging that the difference value between the first detection parameter and the second detection parameter does not exceed the abnormal deviation threshold, obtaining an overhaul result of the equipment when judging that the difference value between the first detection parameter and the second detection parameter exceeds the abnormal deviation threshold, judging whether the equipment is abnormal based on the overhaul result of the equipment, and correcting the abnormal deviation threshold when judging that the equipment is not abnormal. The hydraulic facility fault prediction method provided by the embodiment of the application can reduce the error rate of equipment faults.

Inventors

XING JINMING
Tao Suya
PAN WENHAO
YANG ZHILIN
LI SONGLIN

Assignees

云南水投信息科技有限公司

Dates

Publication Date: 20260512
Application Date: 20251226

Claims (8)

1. A method for predicting a water conservancy facility failure, comprising: S10, constructing a digital twin body based on equipment parameters; s20, acquiring a first detection parameter of digital twin body output based on the operation parameter, and setting an abnormal deviation threshold based on the equipment parameter and the operation parameter; s30, acquiring a second detection parameter output by the equipment; S40, judging whether the difference value between the first detection parameter and the second detection parameter exceeds an abnormal deviation threshold value; S50, when the difference value between the first detection parameter and the second detection parameter is judged not to exceed the abnormal deviation threshold value, ending; s60, when the difference value between the first detection parameter and the second detection parameter exceeds an abnormal deviation threshold, acquiring an overhaul result of the equipment, and judging whether the equipment is abnormal or not based on the overhaul result of the equipment; And S70, when the equipment is judged to be abnormal, correcting the abnormal deviation threshold value based on the difference value of the first detection parameter and the second detection parameter.
2. The hydraulic facility failure prediction method according to claim 1, further comprising the steps of, after determining whether an abnormality has occurred in the apparatus: s80, when the equipment is judged to be abnormal, reducing an abnormal deviation threshold according to a first preset gradient value; And S90, in the subsequent repeated steps of S20-S70, when the equipment is determined to be abnormal again, selecting the last abnormal deviation threshold as the short-time lowest abnormal deviation threshold.
3. The hydraulic facility failure prediction method according to claim 2, further comprising, after selecting the last abnormality deviation threshold as the short-time lowest abnormality deviation threshold, the steps of: S100, in a preset time period, ending when the abnormality of the equipment is judged again; s110, after a preset time period, when the equipment is judged to be abnormal again, repeating the steps S80-S90, and correcting the short-time minimum abnormal deviation threshold.
4. The method of claim 1, wherein correcting the threshold value of the anomaly deviation comprises increasing the threshold value of the anomaly deviation according to a second predetermined gradient value.
5. The method of predicting a water conservancy facility failure as recited in claim 1 wherein correcting the abnormal deviation threshold includes replacing the abnormal deviation threshold based on a difference between the first sensed parameter and the second sensed parameter.
6. The hydraulic facility failure prediction method according to claim 1, wherein in the step S20, setting the abnormality deviation threshold includes setting the abnormality deviation threshold based on a history parameter record and an operation parameter record of the past equipment, based on a fluctuation value of the equipment failure.
7. The hydraulic facility failure prediction method according to claim 6, wherein a minimum fluctuation value for determining that the equipment fails is selected as the abnormality deviation threshold value based on the history parameter record and the operation parameter record of the past equipment.
8. A hydraulic equipment fault prediction system comprising a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the hydraulic equipment fault prediction method of any one of claims 1-7.

Description

Hydraulic facility fault prediction system and method Technical Field The application relates to the technical field of water conservancy facilities, in particular to a system and a method for predicting faults of water conservancy facilities. Background The water conservancy facilities are important foundations for guaranteeing reasonable utilization of water resources, flood control, disaster reduction and the like. However, in the long-term operation process of the hydraulic facility, various faults are easily caused by the influence of various factors such as natural environment, equipment aging and the like. These faults not only affect the normal operation of the hydraulic facility, but also may cause serious safety accidents and economic losses. The traditional water conservancy facility fault detection method mainly relies on manual inspection and periodical maintenance, and the problems of low efficiency, untimely detection and the like exist in the mode, so that the requirements of high-efficiency and safe operation of modern water conservancy facilities are difficult to meet. At present, a mode of constructing a digital twin body based on equipment is adopted, whether the equipment fails or not is predicted through the digital twin body, however, the mode has the following defects that as the service life of the equipment is prolonged and the field operation environment is changed, the detection parameters output by the digital twin body are excessively different from the detection parameters output by actual water conservancy equipment, and accordingly the frequency of equipment failure prediction is frequently reported wrong. Disclosure of Invention The system and the method for predicting the water conservancy facility faults can reduce the fault reporting rate of equipment faults. The specific technical scheme of the embodiment is as follows: in one aspect, an embodiment of the present application provides a method for predicting a hydraulic facility fault, including: S10, constructing a digital twin body based on equipment parameters; s20, acquiring a first detection parameter of digital twin body output based on the operation parameter, and setting an abnormal deviation threshold based on the equipment parameter and the operation parameter; s30, acquiring a second detection parameter output by the equipment; S40, judging whether the difference value between the first detection parameter and the second detection parameter exceeds an abnormal deviation threshold value; S50, when the difference value between the first detection parameter and the second detection parameter is judged not to exceed the abnormal deviation threshold value, ending; s60, when the difference value between the first detection parameter and the second detection parameter exceeds an abnormal deviation threshold, acquiring an overhaul result of the equipment, and judging whether the equipment is abnormal or not based on the overhaul result of the equipment; And S70, when the equipment is judged to be abnormal, correcting the abnormal deviation threshold value based on the difference value of the first detection parameter and the second detection parameter. In some embodiments, after determining whether the device is abnormal, the method further comprises the following steps: s80, when the equipment is judged to be abnormal, reducing an abnormal deviation threshold according to a first preset gradient value; And S90, in the subsequent repeated steps of S20-S70, when the equipment is determined to be abnormal again, selecting the last abnormal deviation threshold as the short-time lowest abnormal deviation threshold. In some embodiments, after selecting the last abnormal deviation threshold as the short-time lowest abnormal deviation threshold, the method further comprises the following steps: S100, in a preset time period, ending when the abnormality of the equipment is judged again; s110, after a preset time period, when the equipment is judged to be abnormal again, repeating the steps S80-S90, and correcting the short-time minimum abnormal deviation threshold. In some of these embodiments, correcting the anomaly deviation threshold value includes increasing the anomaly deviation threshold value according to a second predetermined gradient value. In some of these embodiments, correcting the anomaly deviation threshold value includes replacing the anomaly deviation threshold value based on a difference between the first detection parameter and the second detection parameter. In some of these embodiments, in step S20, setting the anomaly deviation threshold value includes setting the anomaly deviation threshold value based on historical parameter records and operational parameter records of past equipment, based on a fluctuation value of equipment failure. In some embodiments, the minimum fluctuation value for judging the equipment to fail is selected as an abnormal deviation threshold value according to the historical para