Misalignment is one of the common faults for the doubly-fed wind turbine (DFWT), and the normal operation of the unit will be greatly affected under this state. Because it is difficult to obtain a large number of misaligned fault samples of wind turbines in practice, ADAMS and MATLAB are used to simulate the various misalignment conditions of the wind turbine transmission system to obtain the corresponding stator current in this paper. Then, the dual-tree complex wavelet transform is used to decompose and reconstruct the characteristic signal, and the dual-tree complex wavelet energy entropy is obtained from the reconstructed coefficients to form the feature vector of the fault diagnosis. Support vector machine is used as classifier and particle swarm optimization is used to optimize the relevant parameters of support vector machine (SVM) to improve its classification performance. The results show that the method proposed in this paper can effectively and accurately classify the misalignment of the transmission system of the wind turbine and improve the reliability of the fault diagnosis.
Wind power generation systems require complex control systems with multiple working conditions and multiple controllers. Under different operating conditions, switching without disturbance between the sub-controllers plays a critical role in ensuring the stability of power systems. The sub-controllers of two typical cases in the permanent magnet direct drive (PMDD) wind turbine running process are studied, one is the proportional integral (PI) controller in the maximum power points tracking (MPPT) stage, the other is the fuzzy pitch angle controller in the constant power stage. The switching strategy of the two sub-controllers is the emphasis in this research. Based on the active disturbance rejection control (ADRC), the switching mode of the sub-controllers is proposed, which can effectively restrain the sudden changes of the rotor current during the switching process, and improve the quality of power generation. The feasibility and effectiveness of the sub-controller switching strategy is verified by Matlab/Simulink simulation for a 2 MW PMDD wind turbine.
With increasing demands of effective and efficient transportation from our society, the transportation issue has become a noticeable obstacle to the economic development for all countries and regions to a great extend. ITS (Intelligent Transportation Systems) technology is brought forward and considered as an effective approach that promises to alleviate many transportation problems such as traffic congestion, high accident rate, air pollution, and improve safety and reliability on existing roadway system. However, current ITS architectures do not give proper answers to some important problems in ITS such as how to integrate heterogeneous data on the semantic level, how to manage dynamic business process, how to cooperate ITS subsystems among different domains, how to communicate among traffic control center and road sensor network, etc. Hence, a fundamental shift in approach is needed to effectively resolve these complex problems.Fortunately, Grid technology, Semantic Web technology, Web Service technology, Messaging Oriented Middleware (MOM) technology bring us great chance to build a integrated platform for ITS to solve the beforementioned issues. Grid Computing is an ideal technology to realize resource sharing in distributed heterogeneity environments. Semantic Web offers a great opportunity to support data semantization based on a domain-specific ontology database. Process coordination based on Web Service gives a unified way to cooperate ITS subsystems among different organizations. Messaging Oriented Middleware enables distributed communication that is loosely coupled, reliable, and asynchronous in complex network environment.In this paper, we explore four technologies to build a novel Integrated Intelligent Transportation Information and Service Platform to realize traffic data semantization, traffic resource sharing, cooperation traffic process management, and traffic sensor network communication.As a result, a key project for ITISP, ITSGrid, was started up by Zhejiang University and Hangzhou Enjoyor Electronics Co. Ltd in 2005. ITSGrid is an undergoing joint engineering project designed and developed by CCNT Lab in Zhejiang University and Enjoyor Electronics. The new features of ITSGrid are originated from two important research projects -DartGrid and DartFlow, and one key engineering project -JTang Application Server, in CCNT Lab. Its goal is to build intelligent transportation information and service platform, to integrate traffic data resources collected by Enjoyor and cooperate existing ITS subsystems and services deployed by Enjoyor, finally serve for transportation construction in China. . Their xperience includes intelligent transportation systems and services, web service, semantic web, grid computing, and middleware.Xiaohong Qian, Xiuhai Chen, Quanming Xu and Feihu Chen are managers and members of ENJOYOR Intelligent Communications Corporation in Hangzhou. They have over 30 years of research and engineering experiences in intelligent traffic field.
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