تست دینامیکی عقربه سنج اتومبیل
Abstract
1-Introduction
2-Basics Structure and Work Flow
3- Image Preprocess and Parameter Calibration
4-Method to Obtain Dynamic Indication
5-Experiment
6-Conclusion
References
Abstract
In the production of automotive gauge, one of the most important step is to test the meters on the dashboard some of which are needle meters. Based on computer vision technology, a dynamic automatic reading value test method is presented in the paper. With a hardware in the loop (HIL) platform simulating the actual vehicle running state and providing sensor signals or data via CAN(controller area network) bus for the tested automotive dashboard, the needle meters of the dashboard are tested by comparing the input and indication which is obtained through image process method. As the core technology of the method, how to read the indication of the needle meters automatically is expounded in detail. The proposed method is tested on an experimental system which is composed of a HIL platform based on VECTOR dSpace and a computer vision equipment including several MV-VS078FC cameras. The HIL and vision parts can coordinately work to fulfil the automatic test procedure. The meters can be dynamically driven and precisely automaticly read out.
Introduction
In the production or in the product testing process of automotive gauge, one of the most important step is to test the meters on the dashboard some of which are needle meters. Automatic test methods play an increasingly important role in the field. Automatic reading of the needle meters is one of most challenging task in designing the automatic test systems. As the needle meters is functionally oriented to the human vision, the image recognition is the most direct and effective technical method to read their value and automatic test system based on computer vision technology is an effective way to solve this problem[1]. Some automatic reading techniques of meters based on computer vision are presented[2,3,4]. Now the needle meters of automobiles usually receive the data detected by the intelligent sensors or control units from such in vehicle communication networks as CAN(controller area network)[5].