Distributed intelligent monitoring system for motor

Abstract

The present invention relates to a distributed intelligent motor monitoring system. The system includes a locale bottom layer intelligent monitoring substation, a high layer intelligent monitoring main station, and a modular system application software for executing data acquisition and information processing to realize motor monitoring function. Wherein, the monitoring substation is connected to the motor in corresponding position, and is composed of an intelligent monitoring module including monitoring instrument, instrument and data sampler, the intelligent monitoring main station is composed of computers for realizing motor information centralized processing and intelligent monitoring, the substation and the main station is interconnected by data communication network. The system can realize the real time acquisition and local / remote monitoring for the parameters of single or multiple motors, the motor running status recognition and failure diagnosis function. The system not only can be used as the special equipment for delivery tests and type approval test for the motor manufacturer, but also can be broadly used for the motor real time monitoring or on line failure monitoring for the industrial department such as metallurgy, chemical industry, petroleum and pharmacy.

Description

Technical field: [0001] The invention belongs to the technical field of motor measurement and control, and relates to a distributed intelligent motor monitoring system. Background technique: [0002] At present, most domestic motor manufacturers and motor users often use relatively primitive instruments such as ammeters, voltmeters, and tachometers to conduct motor tests (factory tests and type tests) and motor maintenance, which has high labor intensity, large test errors, and high efficiency. Inferior disadvantages; some existing motor experiment systems in China are realized under the DOS system, which has simple functions, poor compatibility, scalability and real-time performance, and it is difficult to realize synchronous monitoring (detection) of multiple motors. Fully meet the test requirements of the type test of the motor manufacturer. In metallurgy, chemical industry, petroleum, pharmaceutical and other industrial sectors, online real-time monitoring and fault dia...

AI Technical Summary

Problems solved by technology

Many of the existing motor fault diagnosis technologies operate offline, without analyzing and processing real-time collected data. Some fault diagnosis technologies based on wavelet analysis and neural network are still in the theoretical research stage, and it is difficult to realize real-time identification of motor operating conditions. , fault diagnosis and prediction, which brings huge hidden dangers to the safety of personnel and equipment and industrial production

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