Tanggong Chen

New Development of Traveling Wave Induction Heating

The research of travelling wave induction heating (TWIH) has been applied into a broader metallurgical engineering area in current years. Comparing with other known systems, the traveling wave (TW) inductor is more promising, for its ability of obtaining more uniform heating. The traditional induction heating methods have been studied for many years. The TWIH, however, is not fully appreciated with respect to their main advantages and possible industrial applications. Thus, this paper tries to explain the research status and problems in existence of the TWIH technology. Meanwhile, the author aim to discuss the development trend and the direction for the future research in this paper.

On the farther analysis of performance of the artificial searching swarm algorithm

Artificial Searching Swarm Algorithm (ASSA) is an intelligent optimization algorithm, and its performance has been analyzed and compared with some famous algorithms For farther understanding the running principle of ASSA, this work discusses the functions of three behavior rules which decide the moves of searching swarm Some typical functions are selected to do the simulation tests The function simulation tests showed that the three behavior rules are indispensability and endow the ASSA with powerful global optimization ability together.

An Improved Artificial Searching Swarm Algorithm and Its Performance Analysis

Artificial Searching Swarm Algorithm (ASSA) is a novel intelligent optimization algorithm. In this work, an improved ASSA (IASSA) with global inertia weight is proposed. IASSA and ASSA are used for optimizing multivariable functions and the performances have been compared. The results proved that the IASSA possesses a better performance than that of ASSA in both searching precision and convergent speed.

Design Optimization of a Fluxgate Current Sensor With Low Interference

A new fluxgate current sensor is presented in this paper. The sensor consists of an additional magnetic toroidal core and an additional winding, aside from the elements in a traditional sensor. In addition, the exciting winding is wound along the circumference of the toroidal core to decouple the exciting magnetic field and the feedback magnetic field in order to reduce internal interference. With the additional core and the additional winding, the proposed current sensor can extend its bandwidth to medium- and high-frequency ac measurement. Another purpose of introducing the additional core is to concentrate on the exciting magnetic field and to reduce interference from external disturbances. A prototype of the proposed sensor was designed and tested. Test results show that the sensor is less affected by hysteresis effects and has a measurement error (precision) within 0.4% of the full scale, a 40-kHz small-signal bandwidth, remarkable sensitivity, and linearity in the measurement range up to 25 A.

Artificial Tribe Algorithm for solving constrained optimization problems

Artificial Tribe Algorithm (ATA) is a novel optimization algorithm. This paper presents the comparison results on the performance of the ATA for solving constrained optimization problems. The penalty function method and non-parameter penalty method are applied to a set of constrained problems. The simulation results show that ATA is an efficient algorithm for constrained optimization problems.