PHM Solution of Air Compressor

According to the problems encountered in the air compressor industry,Witium launched the "air compressor fault prediction solution", which carries out the health status analysis and early warning fault analysis of the air compressor and host equipment for the monitoring of the operation status of the air compressor on the user's site, forms a professional air compressor fault prediction and health diagnosis report, and gives maintenance suggestions. Witium 's air compressor fault prediction solution brings great commercial value to users:

  The air compressor fault prediction solution uses the Internet of things high-frequency vibration sensor to collect the equipment vibration waveform samples and surface temperature, and generate the vibration characteristic samples of the air compressor equipment; The edge computing gateway collects the three-phase winding temperature and lubricating oil temperature of the air compressor through the platinum resistance to understand the operating load state of the air compressor. Combined with the vibration characteristics of the sensor, the intelligent mechanism model algorithm is used to analyze the big data of the sampled data, so as to realize the prediction of air compressor equipment faults such as imbalance, misalignment, looseness, gear wear and bearing aging; Then upload the data samples and analysis learning results to the witcloud Internet of things data cloud platform through mqtt; The SaaS business cloud platform of the solution provides users with status monitoring, scene monitoring, fault management, operation and maintenance management, equipment management, customer management, authority management and other functions; It also provides data interface function to facilitate users to import equipment status into intelligent factory operation and maintenance platform system. At the same time, the business cloud platform provides professional users with operation status analysis and early warning fault analysis of air compressor equipment through big data analysis tools, and forms professional air compressor equipment health diagnosis reports and maintenance suggestions.