Abstract
With advancement of technologies, instrument cluster is become more complex. Conventional manual testing and validation is difficult to cover all the test cases to provide flawless delivery of product within restricted development timescale. As for now, we are proposing to use computer vision system in automotive manufacturing for automated design validation testing process. The purpose of the inclusion of computer vision system is to replace the conventional design validation testing process which is time consuming and extremely labor intensive. The speedometer, tachometer, fuel gauge and temperature gauge are inspected by comparing the accuracy of the pointer detected using the developed algorithms with the pointer position displayed on the meter. Besides that, the signal indicators status can be inspected using pixel intensity test. Under the assumption of controlled light surrounding and fixed position of the camera, pixel intensity can produce accurate results. The deviation error of needle gauge test and signal indicator test are 2.3%, those error occur while there is some noises influence the threshold value. Besides that, processing time of computer vision is within 0.5 s which is quite efficiency in testing process. In conclusion, the machine vision system is able to help for spectating the automated instrument cluster testing process.
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Ren, T.W., bin Wan Jamaludin, W.S., Lin, K.Y., Mahyuddin, M.N., Bin Rosdi, B.A. (2019). Automated Testing of Vehicle Instrument Cluster Based on Computer Vision. In: Zawawi, M., Teoh, S., Abdullah, N., Mohd Sazali, M. (eds) 10th International Conference on Robotics, Vision, Signal Processing and Power Applications. Lecture Notes in Electrical Engineering, vol 547. Springer, Singapore. https://doi.org/10.1007/978-981-13-6447-1_64
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DOI: https://doi.org/10.1007/978-981-13-6447-1_64
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