Wind turbine operating state fuzzy synthetic evaluation method based on Markov chain
A technology of fuzzy comprehensive evaluation and Markov chain, applied in the direction of instruments, data processing applications, calculations, etc., can solve the problems that it is difficult to accurately reflect the potential failure of the unit and prone to misjudgment
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Embodiment 1
[0077] The present invention provides a fuzzy comprehensive evaluation method for wind turbine operating state based on Markov chain (also known as Markov chain) parameter prediction, including the following steps:
[0078] Step 1) Determine the evaluation level V of the operation state of the wind turbine; this embodiment takes the evaluation of the operation state of the wind turbine at a single moment as an example, and divides the operation state of the wind turbine into four evaluation levels, namely:
[0079] V = {Good, Passed, Attention, Serious} = {v 1 ,v 2 ,v 3 ,v 4}.
[0080]Step 2) Establish a hierarchical model of wind turbine operating status evaluation indicators: take the wind turbine operating status as the evaluation object, first divide the wind turbine into five sub-items, including the gearbox system, pitch system, generator system, control system and parallel Then, according to the principle of integrity, select the monitoring parameters of the SCADA s...
Embodiment 2
[0178] In this embodiment, the evaluation of the operating state of the wind turbines at continuous time is taken as an example. Table 8 shows the evaluation results of the wind turbine operating status at time T2-T6. Judging from the evaluation results of continuous time, the evaluation results of the proposed model are more in line with the actual operating status of the wind turbine analyzed before. The evaluation results of the traditional FSE model are relatively conservative , in contrast, the evaluation results of the improved FSE model can better reflect the potential failure of the unit, and if maintenance measures are taken at T4 time, the "serious" operating state can be avoided.
[0179] Table 8 State evaluation results at continuous time
[0180]
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