CSIC Chongqing Haizhuang Wind Power Equipment Co.

Chongqing, China

CSIC Chongqing Haizhuang Wind Power Equipment Co.

Chongqing, China
SEARCH FILTERS
Time filter
Source Type

Wang S.,Chongqing University | Zhu C.,Chongqing University | Song C.,Chongqing University | Han H.,CSIC Chongqing Haizhuang Windpower Equipment Co.
Frontiers of Mechanical Engineering | Year: 2017

The reliability and service life of wind turbines are influenced by the complex loading applied on the hub, especially amidst a poor external wind environment. A three-point elastic support, which includes the main bearing and two torque arms, was considered in this study. Based on the flexibilities of the planet carrier and the housing, a coupled dynamic model was developed for a wind turbine drive train. Then, the dynamic behaviors of the drive train for different elastic support parameters were computed and analyzed. Frequency response functions were used to examine how different elastic support parameters influence the dynamic behaviors of the drive train. Results showed that the elastic support parameters considerably influenced the dynamic behaviors of the wind turbine drive train. A large support stiffness of the torque arms decreased the dynamic response of the planet carrier and the main bearing, whereas a large support stiffness of the main bearing decreased the dynamic response of planet carrier while increasing that of the main bearing. The findings of this study provide the foundation for optimizing the elastic support stiffness of the wind turbine drive train. © 2017 Higher Education Press and Springer-Verlag Berlin Heidelberg


Xu X.,Chongqing Jiaotong University | Xu X.,Chongqing University | Dong S.,Chongqing Jiaotong University | Liao C.,Chongqing University | And 2 more authors.
Journal of Vibroengineering | Year: 2016

The dynamical characteristics research of planetary gear system with tooth pitting is useful for early fault diagnosis and monitor. However, it is an unsolved puzzle to establish the relationship between tooth pitting and dynamical characteristics. In this study, a pitting fault analytical model is proposed to investigate the effects of tooth pitting on the gear mesh stiffness. Then this mesh stiffness with tooth pitting is incorporated into a dynamical model of planetary gear system, and the effects of the tooth pitting on the vibration characteristics is investigated. The simulated results show that the time-varying mesh stiffness is reduced with tooth pitting propagations along width or depth direction. The mesh frequency and its harmonics are mainly frequencies components in the frequency spectrum of dynamic mesh force, but sidebands caused by the tooth pitting are more sensitive than the mesh frequency and its harmonics. The tooth pitting frequency and its harmonics also increase with the rising rotational speed of the sun gear. In addition, both relative statistical indicators of RMS and Kurtosis increase with the growth of tooth pitting size. But the relative indicators have different sensitivity on the vibration signal type. These results could supply some guidance to the condition monitoring and fault diagnosis of planetary gear system, especially to the gear tooth pitting at early stage. © JVE INTERNATIONAL LTD.


Li Y.,Chongqing University | Zhu C.,Chongqing University | Tao Y.,CSIC Chongqing Haizhuang Windpower Equipment Co. | Song C.,Chongqing University | Tan J.,Chongqing University
Zhongguo Jixie Gongcheng/China Mechanical Engineering | Year: 2017

The failure modes and research progresses of reliability for wind turbines at home and broad were analyzed. The failure modes, failure reasons and detection methods of key components in the wind turbines were summarized. Also, the frequently used methods of reliability analysis and research status of wind turbine reliability were analyzed. Then research focuses, research methods and measures to improve wind turbine reliability were presented. Combining with the engineering requirements and research status, the development tendency of wind turbine reliability was analyzed and the flowchart to investigate the smart health management technology of wind turbines was proposed. It is of great significance to reduce the costs of operations and maintenances and to improve the safety of wind turbines. © 2017, China Mechanical Engineering Magazine Office. All right reserved.


Jin X.,Chongqing University | Jin X.,Xi'an Jiaotong University | Li L.,Chongqing University | Ju W.,Chongqing University | And 3 more authors.
Renewable Energy | Year: 2016

Guaranteeing a robust and reliable wind turbine design under increasingly demanding conditions requires an expert insight into dynamic loading effects of the complete turbine and its subsystems. Traditionally, aeroelastic codes are used to model the wind turbine, where the gearbox is reduced to a few or only one degree of freedom, as bring limitations to describe the dynamic behavior in detail. In this paper, the gearbox dynamic behavior is assessed by means of three multibody models of varying complexity, which are assessed based on modal and dynamic behaviors. This work shows that the fully flexible multibody dynamic model can better reflect the operating condition of the wind turbine. However, due to high calculation precision, the fully flexible multibody dynamic model consumes much times. Therefore, an artificial neural network method is proposed for the prediction of wind turbine dynamic behaviors. The results show that combination of the multibody method and the artificial neural network can reduce the simulation runtime, guaranteeing the accuracy meantime. Therefore, it is of great significance in engineering practice. © 2016 Elsevier Ltd.


Han H.,Chongqing University | Zhang G.,Chongqing University | Yang W.,CSIC Chongqing Haizhuang Windpower Equipment Co.
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | Year: 2015

Through analyzing the influence of turbulence intensity on statistical power curve of wind turbine, the correction method for output power curve of wind turbine was put forward according to turbulence intensity. By comparing with the measured statistic results of the same wind turbine according to IEC standard, the measurement results by using correction method has lower uncertainty than standard statistical method, which can accurately reflect actual operation situation of wind turbine, and provide reliable basis on normal maintenance, operation optimization of wind turbine, as well as preliminary power estimation of wind farm construction. ©, 2015, Science Press. All right reserved.


Wang C.,Chongqing University of Technology | Li Q.,CSIC Chongqing Haizhuang Windpower Equipment Co. | Zhao W.,Chongqing University of Technology
Gongneng Cailiao/Journal of Functional Materials | Year: 2015

Electro-brush plating were operated on the base material of ADC12 aluminum with alkaline copper primer, respectively fast nickel solution and fast nickel solution + rare earth La2O3 as the working layer. The results showed that adding the appropriate amount of rare earth La2O3 can obtain better properties than without adding rare earth La2O3 into the plating solution, comparing the microstructure, component and hardness, the binding force of the coating and the matrix, corrosion resistance, friction and wear behavior of two kinds of coatings by SEM, XRD, micro hardness tester, utomatic scratch tester, constant potential instrument, abrasion tester, etc. ©, 2015, Journal of Functional Materials. All right reserved.


Yang D.,Chongqing University | Li H.,Chongqing University | Hu Y.,Chongqing University | Zhao J.,Chongqing University | And 2 more authors.
Renewable Energy | Year: 2016

A noise suppression method for feature frequency extraction that is supplemented with multi-point data fusion was investigated in consideration of issues involving wind turbine vibration signals subject to high noise disturbance. The difficulty of extracting early weak fault features was examined as well. First, a de-noising and feature extraction method that uses EMD-Correlation was developed by adding empirical mode decomposition (EMD) and autocorrelation de-noising to the wavelet package transform under the effects of white noise and short-term disturbance noise in wind turbine vibration signals. Second, an EMD-Correlation analysis model for feature frequency extraction supplemented with multi-point data fusion was established with reference to adaptive resonance theory-2 to highlight the feature frequency of a possible early weak fault. Third, the results obtained with the actual and simulated fault vibration signals of wind turbine bearing faults and the outcomes of comparing the different feature frequency extraction methods show that the proposed method of EMD-Correlation that is supplemented with multi-point data fusion can not only effectively reduce white noise and short-term disturbance noise but can also extract the feature frequency of early weak faults. Finally, prototype hardware and software were developed for a wind turbine condition monitoring system based on the aforementioned fault feature extraction algorithms and tested in an actual wind turbine generation system. © 2016 Elsevier Ltd.


Yang C.,Chongqing University of Technology | Li H.,Chongqing University of Technology | Hu Y.,Chongqing University of Technology | Yang D.,Chongqing University of Technology | And 2 more authors.
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2015

To mitigate cyclic loads in the wind turbine generator system (WTGS) caused by rotor unbalance, an adaptive individual pitch control (adaptive-IPC) strategy is proposed. Firstly, based on the relation of the rotational reference frame of blades and the fixed reference frame of hub, the loads characteristics are analyzed for a WTGS with unbalanced rotor. Then, considering that the frequency of the rotor unbalanced loads will vary with the speed of WTGS, a proportional-integral-resonant (PIR) based adaptive-IPC is presented in detail, with the resonant frequency of the R controller being adapted to the WTGS speed. And the pitch controller design method is also investigated. Finally, by using the FAST-MATLAB/Simulink based loads and control co-simulation system for WTGS, loads of a WTGS are simulated and compared in both balanced and unbalanced rotor condition. The load mitigation performance of the proposed adaptive-IPC is simulated with IEC turbulence wind speeds, and the results are compared with that of proportional-integral (PI) and proportional-resonant (PR) based traditional IPC strategies. Results show that the rotor unbalance will cause frequency-varying cyclic loads in the WTGS, and the proposed adaptive-IPC strategy is more effective than the two traditional IPC strategies. ©2015 Automation of Electric Power Systems Press


Li H.,Chongqing University | Hu Y.,Chongqing University | Li Y.,Chongqing University | Yang D.,Chongqing University | And 3 more authors.
Dianli Zidonghua Shebei/Electric Power Automation Equipment | Year: 2015

A method of gradual deterioration probability analysis based on the temperature characteristic parameters is proposed for the critical components of WTGS (Wind Turbine Generator System) to grasp their deterioration level and tendency. Since the fixed threshold may not be used to accurately determine the degradation degree, the concept of data fitting and turbine grouping based on the temperature characteristic parameters and rotation speeds of the critical components is proposed to set the dynamic thresholds for the upper and lower limits of degradation degree. In order to include the effects of operating condition and duration on the degradation degree, the nonparametric kernel density estimation method is applied to build the probability density function of degradation degree for the critical components and a method of gradual deterioration probability analysis is presented for different monitoring cycles. With the rear bearing of a wind-turbine generator in an actual wind farm as an example, the proposed dynamic threshold method and probability analysis method are verified based on the historical monitoring data of its gradual deterioration. Compared with the fixed threshold method, the proposed dynamic threshold method can more accurately determine the degradation degree of components and more effectively analyze the deterioration tendency of critical components. © 2015, Electric Power Automation Equipment Press. All right reserved.


Hu Y.,Chongqing University | Li H.,Chongqing University | Liao X.,Chongqing University | Song E.,Chongqing University | And 2 more authors.
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2016

In order to know about the remaining life of wind turbine bearings, the performance degradation model and real-time remaining life prediction method of wind turbine bearings were proposed based on temperature characteristic parameters. Firstly, because the uncertainty of wind speed and wind direction results in the temperature of wind turbine bearings in a wide range, by using the method of the moving average method, the relative temperature data of wind turbine bearings were smoothed, and the temperature trend data of wind turbine bearings were obtained. Secondly, considering the degradation speed of bearings change with the operational time and external uncertain factors, the performance degradation model was established based on the Wiener process, and the parameters of performance degradation model were obtained by using the method of maximum likelihood estimation. Thirdly, according to the failure principle of the first temperature monitoring value beyond the warning threshold, the remaining life prediction model of wind turbine bearings was established based on the inverse Gaussian distribution. Finally, taken as an example of the remaining life prediction of a practical generator rear bearing, the process of performance degradation and real-time remaining life prediction were demonstrated. By comparison with the practical remaining life, results show that the proposed model and prediction method is correct and effective. © 2016 Chin. Soc. for Elec. Eng.

Loading CSIC Chongqing Haizhuang Wind Power Equipment Co. collaborators
Loading CSIC Chongqing Haizhuang Wind Power Equipment Co. collaborators