Papers by Keyword: Multi-Sensor Fusion

Abstract: The complex geographical environment put forward grand challenge to most current detecting robot on the problem of communication control and moving obstacle avoidance.This paper proposed a crawler robot for complex environment detecting.Information acquisition was achieved by Labview programming,the collected sensor information was debugged by fusing and displaying in the Labview interface , in order to realize the stability of the system.The positioning part adopted wireless location technology of ZigBee networks,which can support a large number of network nodes, fast, and reliable security etc.In addition, the upper part of the robot body was equipped with camera and mechanical arm to achieve target capture, carrying something and other tasks. According to the situation of accident, remote control terminal through wireless control function can control the further action of the robot. Through experimental tests, this paper proposes this kind of detection robot had great advantages in detection, search and rescue, it can complete the search under complex and dangerous environment.

Abstract: The interaction of water hyacinth area with growth is known to be strongly influenced by area size, but little is known about the interdependent role that size and time have on dynamic estimation of water hyacinth area. We report on the fusion of specially designed, satellite and GPS sensor data into area growth model as a function of area and time. We employ a multi-sensor fusion technique that is able to generate uniform data of fitting area growth model with complete control of area and time. Evidence of an overall Goodness of Fit Index of 0.9753 was obtained by using conventional statistic analysis. These findings suggest that the multi-sensor fusion technique readily supports area growth model development with highly resolution. Moreover, it was found that area growth model enjoy an appreciable advantage when it comes to harvesting water hyacinth.

Abstract: In order to explore the application of multi-sensor fusion technology in nondestructive testing of agricultural products and develop new detection methods for agriculture, multi-sensor information fusion technology are performed to identify freshness of freshwater fish meat. Different freshness of grass carp specimens were identified by multi-sensor fusion method which three characteristic data that are PH value, conductance and smell were measured, collected, and then fused by fuzzy theory method. During the experiment process the value of the total volatile basic nitrogen (TVB-N) of standard samples and test samples were measured. The freshness standard was established by the TVB-N value of standard samples. Correctness of the results of multi-sensor data fusion was verified by comparing the TVB-N value of the test samples with the freshness standard. The results show that the freshwater fish meat with different freshness can be identified correctly by multi-sensor data fusion method which is fuzzy theory and the accuracy rate is 94%.

Abstract: The spontaneous combustion in coal mine goaf badly influences the underground safe work and regular production, which has become one of the major disasters that get much attention and need to be controlled. This paper analyzes the causes of spontaneous combustion and the relationship between the significant gas and temperature, the degree of spontaneous combustion, and coal category to monitor the composition and concentration of the significant gas of the spontaneous combustion in coal mine goaf and graphically visualize the change trend in a certain period. At the same time, when the composition and concentration of the significant gas approach the spontaneous combustion point, the system can make a sound-light alarm. The system not only provides robust technical support for the prediction of the spontaneous combustion in goaf, but also gives some reference for the prevention of underground spontaneous combustion in coal industry.

Abstract: The speed and position measurement is an important part of the train control system. Accurate measurement of train speed and position ensures safety of train running and improves transportation efficiency. Traditional methods to measure speed and position usually rely on single sensor, which has less accuracy and reliability. A method of measuring train speed and position based on multi-sensor fusion is proposed in this paper. Since trains are running on fixed rail tracks, the position of train can be determined by the traveled distance and speed monitoring is essentially to measure the magnitude of train velocity. According to this characteristic, this measurement system consists of axle odometer, Doppler radar, accelerometer and intermittent inquiry balise. The federated Kalman filter is used to implement multi-sensor fusion. Simulation experiment results prove that this method can improve the accuracy and reliability of train speed and position measurement.

Abstract: To move efficiently in an unknown environment, a mobile robot must use observations taken by various sensors to detect obstacles. This paper describes a new approach to detect obstacles for serpentine robot. It captures the image sequence and analyzed the optical flow modules to estimate the deepness of the scene. This avoids one or higher order differential in the traditional optical flow calculation. The data of ultrasonic sensor and attitude transducer sensor are fused into the algorithm to improve the real-time capability and the robustness. The detecting results are presented by fuzzy diagrams which is concise and convenient. Indoor and outdoor experimental results demonstrate that this method can provide useful and comprehensive environment perception for the robot.

Abstract: Sensors are used more and more widely today. It can get valuable images through multi-sensor fusion technology. The paper designs an image security method for multi-sensor fused image. It includes keys generation, permutation, diffusion and decryption. Using six decimal numbers it can get three keys in keys generation part. The process of permutation used a new chaotic map to shuffle positions of image pixels. The process of diffusion used classic chaotic map to flat the histogram of the ciphered image. Decryption process is the reverse process of encryption process. The results prove its validity. It also show it can be used in real-time information protect for fused image.

Abstract: In this paper an intelligent wheelchair obstacle avoidance system based on multi-sensor data fusion technology is instructed. It giving rises to the hardware architecture of the wheelchair and develops a sonar and camera data acquisition system on the VC++ platform by which we could complete the sonar and camera sensor information collection and data processing. Use a T-S model based fuzzy neural network multi-sensor data fusion method for intelligent wheelchair obstacle avoidance. Some simulations were done to test the method in different environments and the method can effectively integrated the information of sonar and camera, give appropriate control signals to avoid obstacles.

Abstract: Fault tolerance is crucial to the operating safety and performance of train locating system. Based on the requirements of reliability and safety for train locating, the fault characteristics of location measuring sensors are analyzed. Based on the structure of the train locating system, the fault-tolerant design of the system is given with the location filtering module for case, in which six fault detectors are employed to determine the configuration of the module. Then a PCA based fault detection and isolation method is proposed with Hawkins T2 statistics and the corresponding control limit. By dynamically adjusting the efficiency factors, fault could be detected and isolated as prior defined isolating strategies, and then the fault tolerant performance will be guaranteed. Simulation results demonstrate the high fault tolerant ability of the proposed approach and certain practical application value.