Search

Non-Dispersive InfraRed (NDIR) gas sensor is widely used for gas detection in collieries and the gas chemical industry, etc. The performance of the NDIR gas sensor depends on the volume, optical length and transmittance of the gas chamber. However, the existing gas sensor products have problems of large volume, high cost and incapable of integration, which need to develop towards the miniaturized sensor. This paper first presents the theoretical background of the NDIR gas sensor and the novel structure of a fully integrated infrared gas sensor and its micro-machined gas chamber structure. Then, the light structure and the gas flow of the gas chamber are optimized on Tracepro software and Ansys workbench, respectively, and the technological process for preparing the Micro-Electro-Mechanical System (MEMS) gas chamber is designed. Finally, we produce a gas chamber with a small volume and good transmissivity, which would be the most important part of producing the miniaturized NDIR gas sensor.

A sub-surface imaging method for detecting invisible and buried micro-flaws under fine metallic surface is described. This system, which has a laser source, a CCD camera, and an eddy current exciting device is developed for this work. A pulse generator supplies an intermittent square pulse to induce the exciting coil, which can intensify eddy currents yet reduce the working temperature of the exciting coil and specimens. The magnetic field variation produced by the imbedded defect causes a rotation of the polarization plane of the reflected beam, therefore the reflected beam carries an image of the defect, which is received by a CCD camera. Now the imperceptible flaws in subsurface of mental product are visually tested. Image edge processing approaches are designed to enhance the imaging effect. The method presented is proved to be feasible by the experiment results.

For sensor management of hierarchy multi-sensor information fusion system, a sensor management method based on immunity fuzzy feedback neural network(IFFNN) is proposed in the paper. The method introduces immune algorithm to enhance fault-tolerance of sensor fault system and utilizes fuzzy algorithm and self-learning of neural network to enhance self-adaptation of system. Experiments and analysis show that the proposed method is an effective method to manage sensor.

In this paper, a new mathematic model for calculating available transfer capability (ATC) of power system in power market is presented. This model considers the bidding of generators, bus locational marginal price (LMP) and system security constraints. The objective function is to maximize the total active power consumption for load in sink area. The constraint is the system operation in a security and economy way. A bi-level leader-follower decision-making measure is taken to solve the problem. Relative to the former ATC models which only consider system security constraints, this model is more in accord with the market reality and its solution can guide all parties in market to make decision more efficiently. The numerical simulation results in IEEE30 bus system demonstrate the validity of this model.