A novel measurement system specially used in noise emission assessment and verification of wind turbine generator systems is presented that complies with specifications given in IEC 61400-11 to ensure the process cons...A novel measurement system specially used in noise emission assessment and verification of wind turbine generator systems is presented that complies with specifications given in IEC 61400-11 to ensure the process consistency and accuracy. Theory elements of the calculation formula used for the sound power level of wind turbine have been discussed for the first time, and detailed calculation procedure of tonality and audibility integrating narrowband analysis and psychoacoustics is described. With a microphone and two PXI cards inserted into a PC, this system is designed in Qin′s model using VMIDS development system. Benefiting from the virtual instrument architecture, it′s the first time that all assessment process have been integrated into an organic whole, which gives full advantages of its efficiency, price, and facility. Mass experiments show that its assessment results accord with the ones given by MEASNET member.展开更多
A novel method under the interactive multiple model (IMM) filtering framework is presented in this paper, in which the expectation-maximization (EM) algorithm is used to identify the process noise covariance Q online....A novel method under the interactive multiple model (IMM) filtering framework is presented in this paper, in which the expectation-maximization (EM) algorithm is used to identify the process noise covariance Q online. For the existing IMM filtering theory, the matrix Q is determined by means of design experience, but Q is actually changed with the state of the maneuvering target. Meanwhile it is severely influenced by the environment around the target, i.e., it is a variable of time. Therefore, the experiential covariance Q can not represent the influence of state noise in the maneuvering process exactly. Firstly, it is assumed that the evolved state and the initial conditions of the system can be modeled by using Gaussian distribution, although the dynamic system is of a nonlinear measurement equation, and furthermore the EM algorithm based on IMM filtering with the Q identification online is proposed. Secondly, the truncated error analysis is performed. Finally, the Monte Carlo simulation results are given to show that the proposed algorithm outperforms the existing algorithms and the tracking precision for the maneuvering targets is improved efficiently.展开更多
基金National Natural Science Foundation of China (50605065)
文摘A novel measurement system specially used in noise emission assessment and verification of wind turbine generator systems is presented that complies with specifications given in IEC 61400-11 to ensure the process consistency and accuracy. Theory elements of the calculation formula used for the sound power level of wind turbine have been discussed for the first time, and detailed calculation procedure of tonality and audibility integrating narrowband analysis and psychoacoustics is described. With a microphone and two PXI cards inserted into a PC, this system is designed in Qin′s model using VMIDS development system. Benefiting from the virtual instrument architecture, it′s the first time that all assessment process have been integrated into an organic whole, which gives full advantages of its efficiency, price, and facility. Mass experiments show that its assessment results accord with the ones given by MEASNET member.
基金Supported by the National Key Fundamental Research & Development Programs of P. R. China (2001CB309403)
文摘A novel method under the interactive multiple model (IMM) filtering framework is presented in this paper, in which the expectation-maximization (EM) algorithm is used to identify the process noise covariance Q online. For the existing IMM filtering theory, the matrix Q is determined by means of design experience, but Q is actually changed with the state of the maneuvering target. Meanwhile it is severely influenced by the environment around the target, i.e., it is a variable of time. Therefore, the experiential covariance Q can not represent the influence of state noise in the maneuvering process exactly. Firstly, it is assumed that the evolved state and the initial conditions of the system can be modeled by using Gaussian distribution, although the dynamic system is of a nonlinear measurement equation, and furthermore the EM algorithm based on IMM filtering with the Q identification online is proposed. Secondly, the truncated error analysis is performed. Finally, the Monte Carlo simulation results are given to show that the proposed algorithm outperforms the existing algorithms and the tracking precision for the maneuvering targets is improved efficiently.
