With the development of economy, there are an increasing number of cars as well as traffic accidents, thus intensifying the need to take measures to reduce traffic accidents and protect the safety of life and property. Vehicle distance is one of the most important indexes of traffic safety. The measurement of safety vehicle distance has become an increasingly hot research area of intelligent transportation. Through analyzing the basic principle of stereo vision and calibrating the parameters of the CCD sensors both inside and outside, this paper comes up with a method to measure the former vehicle distance based on stereo vision and DSP. Once the vehicle speed and distance form a non-security association, it will give a warning, and upload data or force speed-limiting. According to the different coordinates of the obtained images of the target vehicle from the left and the right sensor, this method can identify feature points, calculate distance to the target vehicle, and analyze the security of vehicle distance. The experimental results show that this method has wide measurement range, high measurement accuracy, and fast operation rate, thus it can meet the actual needs of the measurement of safe vehicle distance in intelligent transportation.
Compared to the probe based on conventional piezoelectric ceramic, the high-performance ultrasonic probe made from polymer composite materials is much better, which has characteristics such as high sensitivity, wide bandwidth and good directional. And probe’s thickness electromechanical coupling coefficient KT value is up to 68%, which means it can reduce the crosstalk effectively to the phased array probe. In industrial, due to its high bandwidth, it has obvious advantages when used in coarse-grained materials testing and high-precision thickness measurement. In the medical field, ultrasound will reflex significantly at the impurities or the interfaces, and produce the Doppler effect in the flow of blood. Based on the sound field distribution comparative study of polymer materials ultrasonic probe chip, this paper proposed some polymer new applications in ultrasonic testing field.
This paper proposes and analyzes sensory measurement of tire based on image processing, which uses tangent value method, proportion method and Euclidean distance method to detect tire pressure and overload and uses Tamura texture features to describe tire abrasion level. The research presents a contactless way to detect tire pressure, overload and abrasion level and has certain advantages and innovations in function and implementation compared with existing TPMS which can’t detect the tire abrasion level. This research is an application of image processing-based computer vision in tire sensory measurement; it makes the measurement of tire automatically and intelligently and can be used to prevent traffic accidents caused by tires effectively. There are practical values.
Through the furnace-flame image-signal processing for power plant, effective-temperature field proportions, high-temperature field proportions, centroid offset distances, and circular degrees in high-temperature field can be all obtained. What’s more, based on the above data and related signals collected by sensors such as flame detectors as a criterion, the Kohonen’s self-organizing neural network is introduced to distinguish the states of furnace flame. Therefore, the opening incremental adjustment is proposed to achieve real-time control of furnace flame.
When car is in the process of high-speed, the faults caused by tire pressure anomalies are the most worried and difficult to prevent for all drivers. It is one of the important reasons for the sudden traffic accidents. Tire pressure related to ride comfort, fuel consumption, tire wear and vehicle safety, so tire pressure’s monitoring has been one of the important research directions in the safe driving of vehicle. The anomalies of tire pressure made the vehicles appear to tilt and shorten the distance between rim centres and the ground. Using image technology can detect intuitively and fast. This paper measures the dynamic tire pressure based on image processing technology. The vehicles tires goal was extracted by three image differences. After morphological processing, it used three methods to make comprehensive analysis and judgement of whether the tire pressure is normal, to realize the automation and intelligence. This method had realized real-time non-contact detection for dynamic tire pressure, which has extended significance to popularize.
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