According to the problems encountered in the machine tool industry, Witium launched the "machine tool fault prediction system solution", which collects and monitors the cutting tools, motors, reducers and other units in the machine tool equipment, obtains the health status of the equipment, forecasts and alarms, forms the health diagnosis report of the machine tool equipment sub units, and gives maintenance suggestions. This set of fault prediction system solutions can bring great business value to users:

  The machine tool fault prediction solution uses the Internet of things high-frequency vibration sensor to collect the vibration waveform samples and surface temperature of machine tool equipment, and generate the vibration characteristic samples of machine tool tools and other units; The edge computing gateway collects the three-phase winding temperature and lubricating oil temperature of the machine tool through the platinum resistance to understand the operating load state of the machine tool equipment. Combined with the vibration characteristics of the sensor, the intelligent mechanism model algorithm is used to analyze the big data of the sampled data, and the roughness is detected according to the product indication, so as to realize the gradual deterioration in the cutting process of the equipment, such as tool wear, plastic deformation Fault prediction and diagnosis of poor cutting and vibration intensification; 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 machine tools and equipment through big data analysis tools, and forms professional machine tool equipment health diagnosis reports and maintenance suggestions.