Wind turbine generator system spare part demand prediction method, device and equipment

Abstract

The invention provides a wind turbine generator system spare part demand prediction method, device and equipment. The method comprises steps that the service life information of wind turbine generatorsystem spare parts is acquired according to the historical consumption information of the wind turbine generator system spare parts; a cumulative probability distribution function of the service lifeof the wind turbine generator system spare parts is acquired according to the service life information and a service life distribution model; failure frequency of the wind turbine generator system spare parts is acquired according to the cumulative probability distribution function, and the demand quantity of the wind turbine generator system spare parts in an order period is acquired according to the failure frequency. The service life distribution model in the reliability field is applied to demand prediction of the wind turbine generator system spare parts, the multi-time failure possibility of the wind turbine generator system spare parts in the order period is considered, wind turbine generator system spare part demand prediction based on self wind turbine generator system spare partfailure rules is realized, and prediction result accuracy is relatively high.

Description

technical field [0001] The invention relates to the technical field of spare parts management, in particular to a method, device and equipment for predicting demand for spare parts of a wind turbine. Background technique [0002] In order to shorten the downtime of wind turbine equipment repair and ensure maintenance efficiency, a certain amount of spare parts inventory is necessary. The shortage of spare parts inventory may cause the equipment to not be repaired and put into use in time, causing huge economic losses; excessive spare parts reserves will generate a large amount of sluggish inventory, resulting in additional consumption such as warehouse site fees, storage fees, and losses caused by damage to spare parts, occupying a large amount of business flow funds, affecting business operations. Therefore, it is of great significance to reasonably predict the demand for spare parts and reduce the inventory of spare parts on the premise of ensuring the normal maintenance ...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a method, device and equipment for forecasting demand for wind turbine spare parts to overcome the problem of low forecasting accuracy in the prior art

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