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UPS health prediction method, system and computer-readable storage medium

A prediction method and health degree technology, applied in the field of big data analysis, can solve problems such as the inability to intuitively and effectively obtain the status of UPS system health changes and trend analysis results, and the inability to accurately and intuitively predict UPS system failures, etc.

Active Publication Date: 2020-10-20
云科(山东)电子科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing methods cannot achieve accurate and effective health prediction, cannot accurately and intuitively predict UPS system failures, and cannot intuitively and effectively obtain UPS system health changes and trend analysis results

Method used

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  • UPS health prediction method, system and computer-readable storage medium
  • UPS health prediction method, system and computer-readable storage medium
  • UPS health prediction method, system and computer-readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] see figure 1 As shown, a method for predicting the health of a UPS system provided by Embodiment 1 of the present invention mainly includes:

[0056] Step 101, obtaining time series historical data of circuit state parameters in the UPS system, where the circuit state parameters include at least one type of circuit state parameters.

[0057] Specifically, the circuit state parameters may include at least one of the following parameter types: circuit voltage state parameters, circuit current state parameters, circuit power state parameters, frequency state parameters, load state parameters;

[0058] Wherein, the circuit voltage state parameter includes at least one of the following: main circuit phase voltage, bypass phase voltage, UPS system output voltage; such as: main circuit phase voltage Ua, Ub, Uc, etc., bypass phase voltage Ua, Ub, Uc Wait, UPS system output voltage Ua, Ub, Uc, etc.;

[0059] The circuit current state parameters include at least one of the foll...

Embodiment 2

[0096] like figure 2 As shown, a method for predicting the health of UPS provided by Embodiment 2 of the present invention, after step 103 in Embodiment 1 above, further includes:

[0097] Step 104, determine potential fault source information according to health degree information analysis. Specifically:

[0098] Fault source information corresponding to each order of fault symptoms in the transition probability matrix of preset multi-order fault symptoms;

[0099] According to the transition probability matrix of the multi-order fault symptom corresponding to the health degree, the probability information of the target fault caused by the corresponding fault source is calculated.

[0100] Analyze the health curve of the UPS system. If the changing trend of the response in the health curve and the value of the health degree meet the preset failure warning conditions, it is determined that there is a potential failure risk. In practical applications, the fault source infor...

Embodiment 3

[0102] Corresponding to the UPS health degree prediction method of the embodiment of the present invention, the embodiment of the present invention also provides a UPS health degree prediction system, such as image 3 As shown, the system mainly includes:

[0103] The historical data obtaining unit 10 is used to obtain the time series historical data of each circuit state parameter in the UPS system, and the circuit state parameter includes at least one parameter type;

[0104] The symptom occurrence probability obtaining unit 20 is used to calculate the transition probability of the multi-order fault symptom corresponding to each circuit state parameter according to the obtained time series historical data of the circuit state parameters in the UPS system;

[0105] The health degree information obtaining unit 30 is configured to calculate and obtain the health degree information of the UPS system according to the transition probabilities of the multi-stage fault symptoms corr...

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Abstract

The invention discloses UPS (Uninterruptible Power Supply) health degree prediction methods and systems and a computer readable memory medium. A method comprises the steps of obtaining time series history data of circuit state parameters in a UPS system, wherein the circuit state parameters comprise at least one type of circuit state parameter; computing transfer probabilities of multiorder failure symptoms corresponding to each circuit state parameter according to the obtained time series history data of the circuit state parameters in the UPS system; and carrying out computing to obtain health degree information of the UPS system according to the transfer probabilities of the multiorder failure symptoms corresponding to each circuit state parameter. Through application of the methods andthe systems, UPS system health degree can be accurately and effectively predicted.

Description

technical field [0001] The present invention relates to the technical field of big data analysis, in particular to a UPS health degree prediction method, system and computer-readable storage medium. Background technique [0002] Health detection for UPS (Uninterruptible Power System / Uninterruptible Power Supply, uninterruptible power supply) system is an important task in daily maintenance. In the prior art, a method of regularly detecting a specific parameter is usually adopted, and the failure of the UPS system is directly judged and predicted based on the result of the measured parameter. Existing methods cannot achieve accurate and effective health prediction, cannot accurately and intuitively predict UPS system failures, and cannot intuitively and effectively obtain UPS system health changes and trend analysis results. Contents of the invention [0003] In view of this, the present invention provides a UPS health prediction method, system and computer-readable storag...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/40
CPCG01R31/40
Inventor 籍宏飞徐鹏李彬姜丛斌侯博伟
Owner 云科(山东)电子科技有限公司
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