Abstract
Analogue gauges are widely used in process industries. The current method of reading analogue gauges is completely human dependent which involves risk, time and often introduces errors. This calls for an alternative method that is proposed in the paper. The aim of the paper is to demonstrate the use of computer vision in reading analogue gauge parameters using image processing techniques [1]. The results will be available in digital platforms helping in safer, quicker as well as accurate diagnostics and maintenance. A camera is used to capture the gauge image or video and the QR code corresponding to the gauge. In each image or video frame, the QR code will be used to access the database to get the gauge-related information. Using this information from the database, we will detect the needle position with respect to the extreme values using radial lines and calculating average pixel values along them. The current reading is interpolated using the knowledge of gauge scale (liner, square-law, etc.). Experiments show that the proposed method works very well for dial pointer identification of gauges with different shapes and different pointer colours [2]. However, the method fails to read gauges accumulating fog. The maximum uncertainty in the determination of the pointer is less than the human eye can discriminate.
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Ameya, D., Prathmesh, K., Chinmay, D., Kapil, M., Mohnish, ., Anand, I. (2022). Reading Gauges Using Computer Vision. In: Bansal, R.C., Zemmari, A., Sharma, K.G., Gajrani, J. (eds) Proceedings of International Conference on Computational Intelligence and Emerging Power System. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-4103-9_1
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DOI: https://doi.org/10.1007/978-981-16-4103-9_1
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