A fault diagnosis method for open pit gyratory crusher based on bp neural network

Abstract

The invention is a BP neural network -based open -air mineral rotary crusher diagnosis method. It uses a rotary crusher as a fault diagnosis object, and the state of the crusher of the crusher obtains the crusher with the Internet of Things.Corresponding fault feature parameters, and select the faulty feature parameter data according to the distribution uniformity and effectiveness; then use BP neural network as a fault diagnosis technology, use the fault feature parameters as the BP neural network input, use the fault type as the BP neural network output, Using the non -linear relationship between the type of failure type and the corresponding fault feature parameters of the BP neural network, the trainer rotary crusher fault diagnosis model is trained and the diagnostic model is further optimized through the implicit number of layers, and the diagnostic model of the rotary crusher diagnosis model is completed.Training; Finally, the rotary crusher fault diagnostic model is completed through the training model. The crusher fails to analyze the crusher failure. It has the advantages of simple models, strong real -time, and rapid diagnosis.

Description

technical field [0001] The invention belongs to the technical field of mining system engineering and mine optimization, and in particular relates to the establishment and application of a fault diagnosis model of a gyratory crusher in an open-pit mine based on a BP neural network. Background technique [0002] During the development of mineral resources in my country's mining enterprises, mine crushers are one of the commonly used mechanical equipment in the development of mineral resources. Its application can greatly improve the development efficiency and quality of mineral resources. However, in the process of its use, due to the harsh environment, high mining intensity and improper maintenance, etc., it will cause a series of failures of the crusher. Once a failure occurs, it will bring a lot of losses and safety problems to the enterprise. Fault diagnosis If it is not timely, it will not only fail to improve the efficiency of mineral resource development, but will also ...

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Problems solved by technology

However, in the process of its use, due to the harsh environment, high mining intensity and improper maintenance, etc., it will cause a series of failures of the crusher. Once a failure occurs, it will bring a lot of losses and safety problems to the enterprise. Fault diagnosis If it is not timely, it will not only fail to improve the efficiency of mineral resources development, but will also increase the maintenance cost and downtime loss of the enterprise. Therefore, the fault diagnosis of large crushers has always been an urgent problem for mining enterprises.

Because the crusher is a large-scale machine, the structure and mechanism of the equipment are highly complex, and the cause of the failure is relatively complicated. Most of the diagnostic techniques used by mining companies for crushers are still subjective diagnostic techniques, and most of them rely on the experience of personnel to solve problems, which often cannot be achieved accurately. And rapid diagnosis, the processing of crusher faults is mostly in the state of after-the-fact maintenance, resulting in a large waste of maintenance resources. Therefore, it is of great significance to introduce IoT sensor technology and intelligent fault diagnosis technology to realize the prevention-oriented fault diagnosis method.

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