Cloud-Based Characteristic Recognition System of Permanent Magnet DC Motors Measurement

In recent years, the lighting pendant system has played an indispensable and important role in many public spaces. However, daily maintenance and replacing hundreds of lighting fixtures in these high-ceilinged buildings become difficult. In order to solve this problem, many manufacturers combine lighting chandeliers with lifting power modules. However, due to the large number of lifting power modules that need to be installed, it is impossible to measure all modules' worm gear DC motors in the shortest time. Therefore, the portable measurement system in this thesis is developed through Raspberry Pi and Python, and data interpretation is carried out through a quick-release speed measurement mechanism and an acceleration algorithm built in the cloud so that motor measurement can be popularized in various use environments. While the system is not working on measuring, the software also contains an online data collection functionality to monitor the motor for a long time in the era of big data and the Internet of things so that this portable measurement system can fully exert its benefits in the industry.