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Aiming at the disadvantages of traditional vehicle locator, such as GPS positioning system, GPRS communication mode and other related technologies, resulting in inaccurate positioning, long positioning time and high power consumption, a vehicle locator based on BDS / GPS dual-mode combined positioning system is proposed. The positioner adopts BDS / GPS integrated positioning mode, Nb IOT wireless communication mode, power management module lm2596, and COAP transmission mode for positioning data according to NMEA-0183 protocol, which can better ensure the positioning accuracy, positioning speed and stable operation of the locator. The experimental data show that the locator can accurately and quickly measure the positioning data, and the positioning accuracy is high, which can meet the requirements of practical application.

Aiming at the problem of low precision of traditional pipeline leakage detection method, a high-precision pipeline leakage detection method based on acoustic signal is proposed, which combines multiresolution analysis of wavelet transform and cross-correlation algorithm of signal processing. As of the large amount of background noise in the pipeline, it is necessary to filter the high-frequency noise by wavelet transform. In order to improve the accuracy of localisation, the noise is checked at different scales and the noise is filtered at lower scales to retain more details of the acoustic signal leakage. Combined with cross-correlation function, the location of pipeline leakage location is repeatedly positioned to improve the accuracy of positioning.

In this paper, the hardware and software design of the chlorine leakage inspection instrument based on STM32F103ZET6 MCU is introduced. The design of the constant voltage circuit, signal conditioning circuit (including filtering and amplifying circuit), power supply circuit, display circuit and alarm circuit, and through the GPRS module and the cloud server platform to realize data storage and remote viewing. Finally, through the host computer LABVIEW software to query the historical data stored in the cloud server. The equipment can be widely used in ten petrochemical, papermaking, textile, water treatment and other occasions.

Aerial target detection and avoidance is vital for the flight safety of unmanned aerial vehicles (UAVs). The limited amount of feature points for small and mobile obstacles make them very difficult to be detected. In this paper, the background segmentation and small target detection algorithm is applied in the obstacle detection, and the obstacle localization is achieved by the triangulation method, after which, the threat of collision is evaluated using the safety envelope method. Based on the evaluation results, a UAV can avoid the obstacles by the target point avoidance method. Experiments using a six rotor equipped with a stereo vision system have been implemented to testify the method effectiveness and the results show that the UAV can detect and avoid obstacles effectively.

The performance of SAA (Sense and Avoid) for UAV (Unmanned Aerial Vehicle) is the key function to ensure the UAV's autonomous flight safety. Due to the limitation of payload and size, the micro UAV can't equip large sensors such as radar, etc. Toward the challenging operation condition in low altitude flight environment, we proposed a complete stereo vision based SAA solution suitable for MUAV (Micro Unmanned Aerial Vehicle). By processing the stereo vision data onboard the micro UAV, the proposed method is able to efficiently detect obstacle, evaluate threat level and perform collision avoid maneuver. Experimental results show that the SAA method based on stereo vision can achieve accurate obstacles sensing and effective avoidance maneuver in low altitude airspace, The proposed SAA method can be a practical resolution to ensure low altitude SUAV's safety.