Intelligent equipment health management system and method

Abstract

The invention discloses an intelligent equipment health management system and method. The system comprises the following modules: an intelligent comprehensive management module which is used for constructing an early warning algorithm and configuring the early warning algorithm into an early warning module; a data service module which is used for collecting and obtaining real-time operation data, constructing a unified data standard and a data access and storage system, and performing unified data management; a fan early warning diagnosis module which is used for carrying out real-time monitoring and early warning on fan equipment; a blade detection early warning modulewhich is used for monitoring the operation condition and the health state of the fan blade in real time; a photovoltaic equipment early warning diagnosis module which is used for monitoring the photovoltaic equipment in real time; and a man-machine interaction module. The method and system have the beneficial effects that the fault early warning of the fan and the photovoltaic power generation equipment can be realized by monitoring in real time and adopting different diagnosis methods for different equipment, and the sub-health state can be found as early as possible and eliminated in time, so that the fault rate is reduced, and the average fault interval time is prolonged.

Description

technical field [0001] The invention relates to the technical field of intelligent management of wind farms, in particular to an intelligent equipment health management system and method. Background technique [0002] The wind farm is a new energy and environment-friendly power plant that uses wind power to generate electricity. [0003] With the expansion of wind farm scale and the development of information technology, there are certain deficiencies in the operation and management mode centered on the station level, mainly in the scattered resources, high cost, and low efficiency. There are too many operation and maintenance personnel, large investment, and uneven operation and maintenance quality; in addition, the power stations are distributed in a wide area, the site conditions are difficult, the flow of personnel is large, and the investment in logistics support is high; the stock of wind power assets is increasing year by year, and the demand for human resources is to...

AI Technical Summary

Problems solved by technology

[0004] The wind turbines and photovoltaic power generation equipment in the existing wind farm operate continuously, requiring a lot of equipment monitoring and maintenance. Once a certain equipment is abnormal, it will not only require a huge amount of labor to repair and replace, but also cause a lot of economic losses. Therefore, the equipment needs a more intelligent monitoring method to minimize the economic loss caused by equipment abnormalities

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