Electrical equipment fault early warning method and system based on RFID monitoring

A technology for fault warning and electrical equipment, applied in measuring devices, heat measurement, electronic circuit testing, etc., can solve problems such as abnormal trend, low prediction accuracy, and data transmission interference, so as to avoid economic losses, improve prediction accuracy, and predict high precision effect

Pending Publication Date: 2021-01-15
SHANGHAI MUNICIPAL ELECTRIC POWER CO
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The temperature acquisition data of the power equipment temperature acquisition system based on RFID technology has the following problems: due to the collision between multiple tags and multiple readers, there are abnormal data such as missing data points and data dislocation in the data set; RFID realizes data based on reverse electromagnetic waves. Communication and transmission, the working environment of power equipment in the actual scene is complex, and the electromagnetic field in the external environment interferes with data transmission and generates data noise; whe

Method used

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  • Electrical equipment fault early warning method and system based on RFID monitoring
  • Electrical equipment fault early warning method and system based on RFID monitoring
  • Electrical equipment fault early warning method and system based on RFID monitoring

Examples

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Embodiment 1

[0054] A method for early warning of electrical equipment failure based on RFID monitoring, such as figure 1 , figure 2 and image 3 Specifically:

[0055] The time-series temperature data set of electrical equipment is collected by the RFID temperature acquisition system and preprocessed. The preprocessed time-series temperature data set S is divided into a training set E and a test set R, and the training set E is divided into two sub-sets. set, denoted as D 1 and D 2 , the set relationship is:

[0056] S=E∪R

[0057]

[0058] E=D 1 ∪D 2

[0059]

[0060] Fetch from history with D 1 Corresponding fault warning information and D 2 Corresponding fault warning information, using D 1 and with D 1 The corresponding fault warning information trains the denoising autoencoder network AE, and uses D 2 and with D 2 The corresponding fault warning information trains the long-short-term memory neural network LSTM; the fault warning information corresponding to the h...

Embodiment 2

[0076] An electrical equipment fault early warning system based on RFID monitoring, including a data acquisition module, a data processing module, a first prediction module, a second prediction module, a fault early warning module and a model training module:

[0077] The data acquisition module is used to collect time-series temperature data sets of electrical equipment through the RFID temperature acquisition system, and simultaneously collect historical fault warning information and corresponding historical fault warning levels of electrical equipment. The fault warning levels are divided into several levels according to the severity of the fault warning information ;

[0078] The data processing module is used to preprocess the time-series temperature data set collected;

[0079] The first prediction module is used to input the preprocessed time-series temperature data set into the trained denoising self-encoding network to obtain the first fault early warning information;...

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Abstract

The invention relates to an electrical equipment fault early warning method and system based on RFID monitoring, and the method specifically comprises the steps: collecting a time sequence temperaturedata set of electrical equipment through an RFID temperature collection system, preprocessing, and inputting the data set into a trained denoising self-coding network and a trained long and short time memory neural network; respectively obtaining first fault early warning information and first prediction fault early warning information, and inputting the first fault early warning information andthe first prediction fault early warning information into the trained Xgboost model to obtain a fault early warning level; acquiring historical time sequence temperature data and corresponding historical fault early warning information of electrical equipment, preprocessing the historical time sequence temperature data, and using the preprocessed historical time sequence temperature data and the corresponding historical fault early warning information as a training set by a denoising self-encoding network and a long-short-term memory neural network; and enabling the Xgboost model to take the historical fault early warning information and the corresponding fault early warning level as a training set. Compared with the prior art, the invention has the advantages of avoiding over-fitting, being high in precision and the like.

Description

technical field [0001] The invention relates to an electrical equipment monitoring technology, in particular to an electrical equipment fault early warning method and system based on RFID monitoring. Background technique [0002] In the power system, the safe and stable operation of power equipment is the basis for the stability of the power system. However, in the actual power system, many factors such as loose connection of electrical equipment, poor contact, magnetic flux leakage, overcurrent, etc. can cause equipment overheating and cause equipment failure. Therefore, temperature detection is one of the main ways to determine whether the electrical equipment is abnormal. For the power equipment temperature detection system based on UHF radio frequency identification technology, the time series data of power equipment temperature detected by the system is used, and the deep learning technology is integrated to realize the abnormal trend identification of time series temp...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G01R31/302G01K1/02
CPCG06N3/049G01R31/302G01K1/02G06N3/044G06F18/24323
Inventor 贺林覃兆宇焦婷崔律
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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