The Data Acquisition Terminal Development Of Mechanical Equipment's Intelligent Maintenance System And The Reliability Study Of The Cooling Fan

This article is divided into two parts which are the data acquisition terminal development of mechanical equipment's intelligent maintenance system and the reliability study of the cooling fan.Part 1 is are the data acquisition terminal development of mechanical equipment's intelligent maintenance system. Now, mechanical equipment is developing towards complicated, intelligent, networked, which is occupying the important status in the national product. At the same time, people pay more and more attention to condition monitoring and fault diagnosis of mechanical equipment. Because of on-line monitoring system with high cost, only applies to large units or key equipment, off-line data acquisition terminal is suitable for the pump group in the factory. From the practical engineering, this article make the data acquisition terminal development of mechanical equipment's intelligent maintenance system, which includes hardware design and software design. In terms of hardware, to aim at the hardware of the embedded products, this article need to make clear the product functional requirement, make the embedded microcontroller processor selection and peripheral interface module circuit design. In the aspect of software, made the embedded operating system selection and the related driver development to guarantee the normal work of the whole product.Part 2 is the reliability study of the cooling fan. With the rapid development of electronic science and technology, the cooling fans is becoming more and more important. Make study for the life prediction and reliability of the cooling fan, formulate reasonable maintenance strategy is of great significance to the health of the cooling fan. This paper built the cooling fan test-bed, simulated fully the operation environment of the cooling fan, made real-time monitoring the speed, current, voltage, vibration, which is from normal operation to the recession phase of the cooling fan. In the aspect of data processing and analysis, this article respectively used two parameters, three parameter weibull distribution model and multivariate support vector machine model to make the life prediction and reliability assessment of the cooling fan. This article analyzed the results and made the error evaluation, to provide the scientific basis for the health management of the cooling fan.