Design and development of automatic fault diagnosis system for rotating parts of mining machinery based on artificial intelligence technology

Abstract

Based on the BP neural network in the category of artificial intelligence technology, this paper combined with the conventional expert system diagnosis and discrimination method, and completed the construction of automatic fault diagnosis system for rotating parts of mining machinery in ASP.NET environment. Taking the common rotating machinery in mining machinery and equipment as the research object, aiming at the fault characteristics of mining machinery and the difficulties faced by maintenance, such as high difficulty, high cost and high risk factor, the system provides a new comprehensive application solution for the fault diagnosis of rotating machinery with the help of the application advantages of various information technologies. Through data feature extraction, automatic diagnosis, manual diagnosis, data management and other modules in the system, the whole life cycle management of mining machinery and equipment, early warning and treatment of faults, historical data query and other functions are realized. It not only improves the level of health management of mining machinery and equipment, but also establishes a solid guarantee for the safe and stable production of enterprises, and further makes a positive and beneficial attempt for the construction of smart mines in China.