Dynamic Condition Assessment of Electrical Equipments Based on Markov Prediction

Abstract:

A novel method for electrical equipments condition assessment is proposed based on Markov prediction. Firstly, the condition representation parameters are induced according to the general volt-ampere characteristics, which can be identified by least square method. Secondly, the number of samples falling into different intervals is counted and the state transition probability matrix is calculated. Last, the distribution of parameters in future detection periods is predicted and the equipments condition is assessed by the ratio of the length of current operation time and the estimated life. Take a single phase two-winding transformer as an example, Monte Carlo simulation is used to generate the leakage inductance data and the electrical data is derived by PSCAD. The equipment condition assessment results verify the effectiveness and feasibility of this proposed method.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 1696-1699
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.1696
• Online since: May 2014
• Authors: Jian Sheng Li*, Jun Liang, Zhi Hao Yun, Li Zhang, Feng Zhang
• Keywords: Condition Assessment, Condition Based Maintenance, Markov Prediction, Monte Carlo Simulation

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