Introduction

Gearboxes, drive shafts and bearings are the core components of the wind turbine transmission chain. Most faults of wind turbine are directly related to the gearbox, drive shaft and bearing. For example, the vibrations caused by mass imbalance, bending or thermal deformation of rotating shaft, improper axis, oil film vortex and oscillation, oil interruption, damage to thrust bearing,

System Structure

System Hardware Equipment

    Particle Detector
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    Normal Temperature Two Core Cable
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    Piezoelectric Acceleration Sensor
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Product Function/ Significance

  • Product Function
  • Product Significance

Real-time monitoring information display

Real-time monitoring information display

The real-time information display includes the overall real-time fault evaluation of the transmission machinery of each unit of the wind power plant, the specific vibration temperature and speed of each wind turbine and other real-time parameter information.

Historical information query

Historical information query

Historical information query mainly queries the historical data of vibration and other measuring points and the historical data of unit fault alarm and is able to query maintenance records of wind turbine units based on equipment manufacturer, type, number, time, etc. Including failure phenomena, failure time, maintenance processing methods, etc.

Fault diagnosis analysis

Fault diagnosis analysis

Fault diagnosis analysis module can more intuitively show all kinds of monitoring information to maintenance workers, including unit overall view, trend chart, time-domain oscillogram, envelope analysis, FFT spectrogram, self-power spectrum, cepstrum, autocorrelation spectrum, waterfall plot, axis trajectory chart, full-spectrum map. 

Early warning and analysis of faults

Early warning and analysis of faults

Based on the historical information of fault occurrence, autoregressive prediction analysis is adopted to judge the unit state trend, predict the development trend of mechanical fault of wind power drive, push the fault warning information to the designated client according to the role, and timely feedback and process the fault information.

Unit information management

Unit information management

Unit information management provides the input and maintenance of basic information such as unit number, name, model, rated power, unit weight, manufacturer, running time and unit leader, and integrates equipment management and maintenance information into the same system to facilitate enterprise management and unified resource scheduling.

User information management

User information management

User information management includes user account creation, password modification, role setting and user permission setting. Administrators of different levels have different permissions. Only senior administrators have the right to delete and modify the original data, while users of general levels only have the right to query and browse the data.

Artificial intelligence can identify fault types and locations

Artificial intelligence can identify fault types and locations

Artificial intelligence can identify fault types and locations, and display them visually, with no need of manual participation in analysis, which could reduce labor costs and improve unit operation and maintenance efficiency

Real-time online management of health status

Real-time online management of health status

Real-time online management of health status, which could achieve timely maintenance and predictive maintenance, eliminating excessive maintenance and avoiding major failures of the unit.

Improve equipment utilization and power generation

Improve equipment utilization and power generation

Improve equipment utilization and power generation

Optimize spare parts management and reduce inventory cost

Optimize spare parts management and reduce inventory cost

Optimize spare parts management and reduce inventory cost.

Artificial intelligence can identify fault types and locations

Artificial intelligence can identify fault types and locations

Artificial intelligence can identify fault types and locations, and display them visually, with no need of manual participation in analysis, which could reduce labor costs and improve unit operation and maintenance efficiency

Real-time online management of health status

Real-time online management of health status

Real-time online management of health status, which could achieve timely maintenance and predictive maintenance, eliminating excessive maintenance and avoiding major failures of the unit.

Cloud Llatforms and Interactions

  • Predictability

    Regression analysis is conducted to determine the current status of WTGSs, predict the possible evolution of WTGS gearing failures, and take moves to handle and forewarn some serial problems.

    Big data

    The availability of historical data required by WTGS information management such as vibration measuring points and WTGS failure warnings enables companies to manage and allocate their resources in a centralized fashion.

    Accuracy

    Advanced algorithms like artificial neural network and fuzzy set theory are utilized to assess the security of WTGS operation accurately.

    Real-time manner

    Gearing failures that happen to wind turbine generator systems (WTGS) of a wind power plant can be evaluated overall in a real-time way, so that it is possible to learn about how each WTGS is operating now, and put all WTGSs under all-around status monitoring.