Pub Date : 2022-11-17DOI: 10.1109/ICMIE55541.2022.10048607
Teerapat Riyota, P. Boonpramuk, S. Nuratch
In most industrial automation systems, all machines and equipment must operate smoothly and continuously to maintain the system performance. Therefore, all kinds of unexpected failures of the system cannot be accepted. For this reason, the maintenance processes are the essential operations performed periodically to avoid system failures. Of course, this operation takes time and resources, but it cannot be avoided. It is known that most automation systems compose of electrical motors. They are the core devices for robots and other movable machines. Each motor produces meaningful parameters such as temperature, vibration, speed, noise, and power consumption. This paper presents the design and development techniques of the IoT-based embedded device that can be used for real-time monitoring and analysis of the unexpected operations of motors. The proposed device continuously senses and analyzes motor parameters to monitor and predict unexpected operations. We focus on temperature and unbalanced phenomenal measurement of the motors. The unbalanced parameter is implicitly measured from the speed changes using the time measurement of the sensing signals. The proposed device also supports wireless real-time data exchange to the server. The device and server exchange their data using the WebSockets protocol. The data sent to the server can be used for storage, processing, and monitoring. In this work, we also develop a web-based application that allows users to control and monitor the parameters of motors in real-time. The experimental results show that the proposed method can detect the unbalance operations and temperature of the motors at different operations. Therefore, the proposed system can be used in real-world applications that require abnormality detection, abnormal condition warning, and prediction of mechanical devices.
{"title":"IoT-Based Embedded Device Development and Real-Time Analysis for Unexpected Operations of Motors","authors":"Teerapat Riyota, P. Boonpramuk, S. Nuratch","doi":"10.1109/ICMIE55541.2022.10048607","DOIUrl":"https://doi.org/10.1109/ICMIE55541.2022.10048607","url":null,"abstract":"In most industrial automation systems, all machines and equipment must operate smoothly and continuously to maintain the system performance. Therefore, all kinds of unexpected failures of the system cannot be accepted. For this reason, the maintenance processes are the essential operations performed periodically to avoid system failures. Of course, this operation takes time and resources, but it cannot be avoided. It is known that most automation systems compose of electrical motors. They are the core devices for robots and other movable machines. Each motor produces meaningful parameters such as temperature, vibration, speed, noise, and power consumption. This paper presents the design and development techniques of the IoT-based embedded device that can be used for real-time monitoring and analysis of the unexpected operations of motors. The proposed device continuously senses and analyzes motor parameters to monitor and predict unexpected operations. We focus on temperature and unbalanced phenomenal measurement of the motors. The unbalanced parameter is implicitly measured from the speed changes using the time measurement of the sensing signals. The proposed device also supports wireless real-time data exchange to the server. The device and server exchange their data using the WebSockets protocol. The data sent to the server can be used for storage, processing, and monitoring. In this work, we also develop a web-based application that allows users to control and monitor the parameters of motors in real-time. The experimental results show that the proposed method can detect the unbalance operations and temperature of the motors at different operations. Therefore, the proposed system can be used in real-world applications that require abnormality detection, abnormal condition warning, and prediction of mechanical devices.","PeriodicalId":186894,"journal":{"name":"2022 6th International Conference on Measurement Instrumentation and Electronics (ICMIE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132492142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.1109/ICMIE55541.2022.10048617
Fan Liu, Xing-Fei Li, Ganming Xia
Noise floor plays a key role in evaluating the quality of MHD Angular Rate Sensors (MHD-ARSs). It determines the smallest angular rate signals that can be detected. Consequently, how to measure the noise floor accurately has become a critical issue. To the best of our knowledge, little research has been conducted into the noise floor measurement of MHD-ARSs. Moreover, noise floor estimators which have been used are not clearly defined and assessed. In this research, we aim at the evaluation of two methods for estimating noise floor of MHDARSs in operation, namely two-channel method and three-channel method. We present mathematical models and derive bias errors of both two methods. We set up a noise floor measurement system for two identical MHD-ARSs and test the two methods under the condition in which the two sensors operate in a high output SNR regime. We have obtained significant results demonstrating that: 1) Normalized bias error of two-channel method is approximately 80% to 100% in the case of SNR value greater than 10 dB. 2) Three-channel method exhibits no bias errors in theory, but it suffers from random errors originated from normalized random errors of PSD estimates.
{"title":"Evaluation of Methods for Estimating Noise Floor of MHD Angular Rate Sensors in Operation","authors":"Fan Liu, Xing-Fei Li, Ganming Xia","doi":"10.1109/ICMIE55541.2022.10048617","DOIUrl":"https://doi.org/10.1109/ICMIE55541.2022.10048617","url":null,"abstract":"Noise floor plays a key role in evaluating the quality of MHD Angular Rate Sensors (MHD-ARSs). It determines the smallest angular rate signals that can be detected. Consequently, how to measure the noise floor accurately has become a critical issue. To the best of our knowledge, little research has been conducted into the noise floor measurement of MHD-ARSs. Moreover, noise floor estimators which have been used are not clearly defined and assessed. In this research, we aim at the evaluation of two methods for estimating noise floor of MHDARSs in operation, namely two-channel method and three-channel method. We present mathematical models and derive bias errors of both two methods. We set up a noise floor measurement system for two identical MHD-ARSs and test the two methods under the condition in which the two sensors operate in a high output SNR regime. We have obtained significant results demonstrating that: 1) Normalized bias error of two-channel method is approximately 80% to 100% in the case of SNR value greater than 10 dB. 2) Three-channel method exhibits no bias errors in theory, but it suffers from random errors originated from normalized random errors of PSD estimates.","PeriodicalId":186894,"journal":{"name":"2022 6th International Conference on Measurement Instrumentation and Electronics (ICMIE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.1109/ICMIE55541.2022.10048601
Yi Han, Haozhou Zeng, Zemiao Fang, Shuoyu Wang, Tao Liu
China’s aging population is increasingly serious, the number of patients with upper limb dyskinesia is increasing year by year, and upper limb rehabilitation has become an important link of elderly care service. With the progress of science and technology, the training theory of restoring upper limb function is gradually mature, and auxiliary training equipment is also born and developed. In order to develop a low-cost desktop light-weight rehabilitation training equipment, reduce the doctor workload, improve recovery efficiency and reduce the family economic burden, this paper designs a motor drive for upper limb movement rehabilitation equipment. And verify the performance of the motor drive through the simulation and experiment. The results show that the designed motor driver can control the permanent magnet synchronous motor stable operating in the required mode.
{"title":"Motor Drive Design for Upper Limb Rehabilitation Equipment","authors":"Yi Han, Haozhou Zeng, Zemiao Fang, Shuoyu Wang, Tao Liu","doi":"10.1109/ICMIE55541.2022.10048601","DOIUrl":"https://doi.org/10.1109/ICMIE55541.2022.10048601","url":null,"abstract":"China’s aging population is increasingly serious, the number of patients with upper limb dyskinesia is increasing year by year, and upper limb rehabilitation has become an important link of elderly care service. With the progress of science and technology, the training theory of restoring upper limb function is gradually mature, and auxiliary training equipment is also born and developed. In order to develop a low-cost desktop light-weight rehabilitation training equipment, reduce the doctor workload, improve recovery efficiency and reduce the family economic burden, this paper designs a motor drive for upper limb movement rehabilitation equipment. And verify the performance of the motor drive through the simulation and experiment. The results show that the designed motor driver can control the permanent magnet synchronous motor stable operating in the required mode.","PeriodicalId":186894,"journal":{"name":"2022 6th International Conference on Measurement Instrumentation and Electronics (ICMIE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130771540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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