Visualization: BKC critical machinery health monitoring system combines with the three-dimensional model of the plant and machine assets, present the real-time data and state changing visually. For instance, through shaft center line plots at all bearings,you can see the minimal oil film clearances, and you can also check if the shaft was lift correctly during the turning gear, etc. Moreover, the difficult-to-understand time-frequency analysis results are directly linked to the status of the unit to achievereal-time visual asset condition monitoring.
Analytics: Our system providing complete all tools of asset condition monitoring, include the alarming approaches with BKC many years’ experiences, so, we can quickly detect the meaningful anomaly changes,release manpower from the huge measured data. BKC developed an intelligent fault diagnosis knowledge base plug-in system with BKC proprietary algorithm, it can analysis the data and conduct the anomaly detection and identify potential malfunctions indetail, find out the fault locations, severity, root causes and action plans, generate the exception report, and deliver the messages to the right people, provide advanced decision supports for the machinery healthy operation.
◆fromTSIThe collected data is introduced into the expert analysis system to automatically collect fault vector features, and through the self-learning ability of the big data feature matrix; ◆With the help of the specialist diagnosis engine, the operation status and the starting point of deterioration are automatically detected, analyzed and judged, and maintenance and repair suggestions are automatically pushed to avoid fault tripping caused by the failure of regular detection, unclear analysis and judgment, and lack of equipment maintenance strategies. ◆Three-dimensional dynamic display of the trends of the shafting, cylinder block, sliding pin system and water and steam intake models.
◆Cold-state stamping parameters can be recommended, with three-dimensional intuitive display of the bearing lifting height and real-time analysisTSIData, intelligent diagnosis of the impact of shafting changes after major overhauls, and average shortening of the time affected by faults24h; ◆The causes of the "tripping" of steam turbine faults are automatically diagnosed and analyzed, including imbalance, thermal bending, unstable oil film, etc., to shorten the time for fault analysis of the unit. ◆Establish a vibration fault model for steam turbine generators. By automatically identifying signal characteristics, accurately judge different types and natures of faults, and automatically push out solutions to reduce unnecessary maintenance and downtime.
Five-In-One-Inspection Equipment Intelligent Maintenance and Decision System 
Precision Inspection and Remote Diagnosis System 
an intelligent predictive maintenance visualization system for your most critical machinery health and condition monitoring 
Visualized Auxiliary Machinery Intelligent Safety Pre-control System