An Intelligent Detection Device for Remote Fault Diagnosis

Abstract The remote monitoring and fault diagnosis system can enable equipment suppliers to reduce maintenance costs, thereby saving manpower and material resources, and changing from passive defense to active; it can actively find problems and timely solve equipment after‐sales service and maintenance technical support under global market conditions, so as to improve product competitiveness. In the functional design of the system, the management of maintenance work orders is the core function of the whole system. Its main contents include: query on work orders, that is, query on unprocessed work orders; the establishment of the worksheet, which can set the founder, fault type, creation time, recommended maintenance personnel, etc. Receiving the order means that the maintainer selects the most suitable work order for maintenance according to the specific conditions on the work order. The administrator can view the specific contents of the work order and the work conditions of the maintenance personnel, and can issue work instructions to the maintenance personnel manually. In terms of system logic, the device layer includes the connections between terminal devices such as sensors, actuators, production equipment and control systems. The system uses a variety of networks and industrial buses to connect the terminal equipment, so as to achieve the normal control of data flow between the equipment. The support layer includes equipment failure prediction, maintenance work order recommendation, user management, work order management, interface settings, etc. It is responsible for the sorting and storage of instrument data, fault diagnosis and prediction of equipment, and puts forward suggestions for maintenance work. The data layer is the most basic data storage module, including file loading in the database, creation and analysis of query structured database statements. In the process of fault diagnosis, the overall correct rate of Bayesian network diagnosis with multi‐source information layer was 94.3%. The intelligent detection scheme of remote fault diagnosis proposed in this paper effectively improved the service level of the system, and provided forward‐looking information for equipment maintenance, performance diagnosis, upgrading and transformation, thus promoting the transformation of enterprise service strategy. This article is protected by copyright. All rights reserved.