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Power equipment fault rate prediction method considering aging factors

A technology for power equipment and aging factors, applied in prediction, calculation, instruments, etc., can solve the problems of ignoring the influence of power equipment aging factors and maintenance strategies, and not fully reflecting the distribution of equipment life

Inactive Publication Date: 2013-12-04
STATE GRID CORP OF CHINA +1
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Problems solved by technology

[0003] Traditional power equipment reliability failure rate parameters are generally obtained by calculating long-term average values ​​from statistical data, ignoring the influence of power equipment aging factors and maintenance strategies
The time-varying curve of the failure rate of most power equipment is the classic bathtub curve, which can be roughly divided into three stages: early failure period, occasional failure period and wear-and-tear failure period. rate is constant, so it can only describe the occasional failure phase of the bathtub curve, and cannot fully reflect the life distribution of equipment

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  • Power equipment fault rate prediction method considering aging factors
  • Power equipment fault rate prediction method considering aging factors
  • Power equipment fault rate prediction method considering aging factors

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[0068] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0069] combine Figures 1 to 3 As shown, the method of predicting the failure rate of power equipment considering aging factors includes the following steps:

[0070] a Select n groups of equipment operation fault data, the independent variable of each group of fault data is time t, and the dependent variable failure rate is λ i , Select the first m groups of data from the n groups of data, let m=3, and perform curve fitting on the first m groups of data:

[0071] a1. Initialization parameters, including aging curve parameters and iteration equation related parameters: g (0) =(α 0 ,β 0 ), where α is the shape parameter, β is the scale parameter, the allowable error precision k and the number of iterations l;

[0072] a2. Failure rate λ i Calculate the partial derivative function for α and β respectively to get

[0073] a3. Calculate the...

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Abstract

The present invention discloses a power equipment fault rate prediction method considering aging factors. The power equipment fault rate prediction method comprises the steps of fitting a fault rate curve by utilizing the characteristics of a weibull distribution of possessing shape parameters, possessing a great flexibility on data fitting and being able to describe the stages of a bathtub curve completely, and carrying out parameter estimation by applying a Gauss-Newton iterative method to obtain the demarcation points of the stages respectively. In addition, the fault rate prediction method of the present invention also considers the influence of different maintenance policies on the device fault rate, and applies an equivalent age method to solve the actual fault rate of a device. The device fault rate obtained by utilizing the method in the present invention is closer to the reality, and the prediction accuracy of the power equipment fault rate can be improved effectively, thereby guaranteeing the accuracy of the reliability and risk evaluation of a system, and providing correlated reliable bases for the dispatching and maintenance of the system.

Description

technical field [0001] The invention relates to a method for predicting the failure rate of electric equipment considering aging factors. Background technique [0002] The failure rate data of power equipment in the power system is an important basis for system reliability assessment and risk assessment. The degree of credibility of the data will have an important impact on the actual value of reliability assessment and risk assessment results, and it is also an important basis for assessing the technical status of equipment. , failure intensity, an indicator of maintenance quality and efficiency. [0003] Traditional power equipment reliability failure rate parameters are generally obtained by calculating long-term average values ​​from statistical data, ignoring the influence of power equipment aging factors and maintenance strategies. The time-varying curve of the failure rate of most power equipment is the classic bathtub curve, which can be roughly divided into three s...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 刘文霞徐继凯仇国兵张玉莹李盈枝赵天阳杨勇申永涛李鹤周樨徐晓波卜婷婷张建华
Owner STATE GRID CORP OF CHINA
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