A Scalable Spark-Based Fault Diagnosis Platform for Gearbox Fault Diagnosis in Wind Farms

2017 ◽  
Author(s):  
Maryam Bahojb Imani ◽  
Mehrdad Heydarzadeh ◽  
Latifur Khan ◽  
Mehrdad Nourani
Keyword(s):  
Fault Diagnosis ◽  
Wind Farms

scholarly journals A Survey of Condition Monitoring and Fault Diagnosis toward Integrated O&M for Wind Turbines

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2801 ◽  
Author(s):  
Pinjia Zhang ◽  
Delong Lu
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Information Flow ◽  
Wind Turbines ◽  
Energy Flow ◽  
Global Climate ◽  
Rapid Development ◽  
Wind Farms ◽  
Flow Information ◽  
Comprehensive Survey

Wind power, as a renewable energy for coping with global climate change challenge, has achieved rapid development in recent years. The breakdown of wind turbines (WTs) not only leads to high repair expenses but also may threaten the stability of the whole power grid. How to reduce the operation and the maintenance (O&M) cost of wind farms is an obstacle to its further promotion and application. To provide reliable condition monitoring and fault diagnosis (CMFD) for WTs, this paper presents a comprehensive survey of the existing CMFD methods in the following three aspects: energy flow, information flow, and integrated O&M system. Energy flow mainly analyzes the characteristics of each component from the angle of energy conversion of WTs. Information flow is the carrier of fault and control information of WT. At the end of this paper, an integrated WT O&M system based on electrical signals is proposed.

Monitor Method of Offshore Wind Turbine Based on Memory-Like and Neural Network Expert System

2014 ◽  
Vol 635-637 ◽  
pp. 687-693
Author(s):  
Ling Xia Su ◽  
Xia Xia Ma
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Offshore Wind Farms ◽  
Onshore Wind ◽  
Diagnosis Method ◽  
Simulation Results ◽  
Improve Reliability

The number of offshore wind farms increases gradually because of the high capability of power generation. However, the costs of manufacturing, logistics, installation and maintenance of offshore wind turbine are higher than those of onshore wind turbine. Thus the introduction of fault diagnosis is considered as a suitable way to improve reliability of wind turbine and reduce costs of repairs and casualties. In this paper, 3 major failures of direct-driven wind turbine according to urgency and system responses are discussed. A "memory-like" model pretreatment method and a fault diagnosis method for the failures are investigated. The simulation results show that total amount of fault data to be processed and stored is reduced, and difficulties of knowledge gaining and fault reasoning are also decreased.

scholarly journals Condition Monitoring and Fault Diagnosis of Wind Turbines Gearbox Bearing Temperature Based on Kolmogorov-Smirnov Test and Convolutional Neural Network Model

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2248 ◽  
Author(s):  
Peng Guo ◽  
Jian Fu ◽  
XiYun Yang
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Condition Monitoring ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Main Trend ◽  
Maintenance Cost ◽  
Monitoring Method

Wind turbine condition-monitoring and fault diagnosis have important practical value for wind farms to reduce maintenance cost and improve operating level. Due to the special distribution law of the operating parameters of similar turbines, this paper compares the instantaneous operation parameters of four 1.5 MW turbines with strong correlation of a wind farm. The temperature-power distribution of the gearbox bearings is analyzed to find out the main trend of the turbines and the deviations of individual turbine parameters. At the same time, for the huge amount of data caused by the increase of turbines number and monitoring parameters, this paper uses the huge neural network and multi-hidden layer of a convolutional neural network to model historical data. Finally, the rapid warning and judgment of gearbox bearing over-temperature faults proves that the monitoring method is of great significance for large-scale wind farms.

scholarly journals Data–Driven Fault Diagnosis of a Wind Farm Benchmark Model

2017 ◽  
Author(s):  
Silvio Simani ◽  
Paolo Castaldi ◽  
Saverio Farsoni
Keyword(s):  
Fault Diagnosis ◽  
Wind Farm ◽  
Wind Farms ◽  
Monte Carlo Analysis ◽  
Fault Detection And Isolation ◽  
Data Driven ◽  
Parameter Uncertainties ◽  
Benchmark Model ◽  
Research Activities ◽  
Wind Park

The fault diagnosis of wind farms has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of a wind park benchmark model, and it considers viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, noise, uncertainty and disturbances. In particular, the proposed data-driven solutions rely on fuzzy models and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive with exogenous input models, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind farm installation. The achieved performances are also compared with those of a model-based approach relying on nonlinear differential geometry tools. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.

The Research of Data Communication on Wind Power Monitoring and Diagnosis System Based on XML

2014 ◽  
Vol 926-930 ◽  
pp. 2155-2159
Author(s):  
Chao Zhang ◽  
Xiang Jun Pan
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Remote Monitoring ◽  
Information Exchange ◽  
Data Exchange ◽  
Data Communication ◽  
Wind Farms ◽  
Stable Operation ◽  
Diagnosis System ◽  
Power Monitoring

The wind turbine remote monitoring and fault diagnosis is the key of improving unit efficiency, reducing maintenance costs, and ensuring safe and stable operation of the wind farms. A wide variety of wind farm monitoring systems, non-uniform communication standards, and heterogeneous communication platforms is result in a difficulty of information exchange. In this paper, on the basis of following IEC61400-25 standard, we put forward using XML technology to encapsulate data to avoid the formation of the "information island" in wind farms; By combining with VC++ Socket technology to establish a network communication system, this paper solves the data exchange problem of the wind turbine remote monitoring and fault diagnosis system through achievement of data receiving and dispatching; In the end, we use the waveform curve way to display the XML parsing of data, which is convenient for staff to observe and analyze the data.

Sign in / Sign up

Export Citation Format

Share Document