A novelty dual-stator brushless doubly-fed generator (DSBDFG) with magneticbarrier rotor structure is put forward for application in wind power. Compared with a doublyfed induction generator, the DSBDFG has virtues of high reliability and low maintenance costs because of elimination of brush and sliprings components. Therefore, the proposed structure has tremendous potential as a wind power generator to apply in wind power. According to the operating principle of electric machine, the DSBDFG is studied in wind power application. At first, the topology, the winding connecting, the rotor structure, the power flow chart of different operating models and the variable speed capability of electric machine are discussed and analyzed. Then, a 50 kW DSBDFG is designed. Based on the principal dimension of the design electric machine, the electromagnetic characteristics of the DSBDFG with different running modes are analyzed and calculated to adopt the numerical method. From the result, it meets the requests of electromagnetic consistency and winding connecting in the design electric machine. Meanwhile, it confirms the proposed DSBDFG has the strong ability of speed regulation.

Capacitive leakage and adjacent interference are the main influence sources of the measuring error in the traditional series step-up method. To solve the two problems, a new algorithm was proposed in this study based on a three-ports network. Considering the two influences, it has been proved that response of this three-ports network still has characteristics of linear superposition with this new algorithm. In this threeport network, the auxiliary series voltage transformers use a two-stage structure that can further decrease measurement uncertainty. The measurement uncertainty of this proposed method at 500/√3 kV is 6.8 ppm for ratio error and 7 μrad for phase displacement ( k = 2). This new method has also been verified by comparing its results with measurement results of the PTB in Germany over the same 110/√3 kV standard voltage transformer. According to test results, the error between the two methods was less than 2.7 ppm for ratio error and 2.9 μrad for phase displacement.

This paper develops an automatic method to calculate the macrotexture depth of pavement roads, using the tire/road noise data collected by the two directional microphones mounted underneath a moving test vehicle. The directional microphones collect valid tire/road noise signal at the travel speed of 10–110 km/h, and the sampling frequency is 50 kHz. The tire/road noise signal carries significant amount of road surface information, such as macrotexture depth. Using bandpass filter, principal component analysis, speed effect elimination, Gaussian mixture model, and reversible jump Markov Chain Monte Carlo, the macrotexture depth of pavement roads can be calculated from the tire/road noise data, automatically and efficiently. Compared to the macrotexture depth results by the sand-patch method and laser profiler, the acoustic method has been successfully demonstrated in engineering applications for the accurate results of macrotexture depth with excellent repeatability, at the test vehicle’s travel speed of 10-110 km/h.