Elevator reliability prediction method based on unbiased grey fuzzy Markov chain model

A Markov chain, gray fuzzy technology, applied in the direction of electrical digital data processing, resources, instruments, etc., to achieve the effect of high prediction reliability and accuracy

Inactive Publication Date: 2019-01-11
WENZHOU UNIVERSITY
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  • Application Information

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Problems solved by technology

[0004] In order to solve the need to predict the reliability of the elevator and reduce the potential safety hazards of the elevator, the present invention provides an elevator reliability prediction method based on the unbiased gray fuzzy Markov chain model

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  • Elevator reliability prediction method based on unbiased grey fuzzy Markov chain model
  • Elevator reliability prediction method based on unbiased grey fuzzy Markov chain model
  • Elevator reliability prediction method based on unbiased grey fuzzy Markov chain model

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Embodiment Construction

[0012] The embodiments of the present invention will be further described below in conjunction with the drawings:

[0013] The method includes: obtaining the elevator running status in real time through remote monitoring equipment, extracting and recording the fault code when the elevator fails; establishing an unbiased GM(1,1) according to n consecutive historical data of a certain failure of the elevator Model and test the residuals of the model; divide the residual value interval into m states, use fuzzy classification theory to construct fuzzy functions, calculate the fuzzy state probability vector of each data point, and determine each data according to the principle of maximum membership The state of the point; the Markov state transition matrix is ​​established to predict the fuzzy vector of the next occurrence of the fault, and the state of the prediction data is determined according to the principle of maximum membership; when the second prediction is made, the n in the p...

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Abstract

An elevator reliability prediction method based on an unbiased grey fuzzy Markov chain model is presented. When the elevator breaks down, the fault code is extracted, recorded and the historical datais obtained. The unbiased GM (1, 1) model is established according to the historical data, and the residual error of the model is checked. The residual value interval is divided into m states, fuzzy function is constructed by fuzzy classification theory, fuzzy state probability vector of each data point is calculated, and the state of each data point is determined according to the maximum membership principle. The Markov state transition matrix is established to predict the fuzzy vector of the fault next time, and the membership state of the predicted data is determined according to the maximum membership principle. The invention predicts the reliability of the elevator, obtains the time interval trend of the occurrence of a certain fault through an unbiased GM (1, 1), approaches the datafluctuation trend by utilizing the anti-interference property of the fuzzy Markov chain, and slides the Markov chain, so that the reliability prediction result of the elevator is more accurate.

Description

Technical field [0001] The invention relates to the field of failure prediction, and in particular to an elevator reliability prediction method. Background technique [0002] As a means of transportation in buildings, elevators have been increasingly used by modern people. With the increase in the number of elevators, people use elevators more and more frequently. The reliability of elevator operation has become the focus of social concern. The state is directly related to the safety of people's lives and property. At present, elevator remote monitoring equipment has been widely used in elevator real-time operation monitoring. The elevator monitoring equipment transmits real-time information of the monitored elevator to the elevator maintenance unit through the mobile data network. [0003] At present, we can only rely on the regular maintenance of elevators. Regular maintenance with unclear purpose is not only costly and low efficiency, but also difficult to find hidden safety h...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06Q10/06B66B5/00
CPCG06Q10/0635B66B5/0037
Inventor 庞继红王瑞庭赵华金怡妮綦法群周富得谢兆贤
Owner WENZHOU UNIVERSITY
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