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Concurrently, the safety requirements for rotating machinery have escalated, necessitating enhanced real-time data processing capabilities. Conventional methods, reliant on experiential approaches, have proven inefficient in meeting these evolving challenges. To this end, a fault detection method for rotating machinery based on mobileNet in MvWSNs is proposed to address these intractable issues. The small and light deep learning model is helpful to realize nearly real-time sensing and fault detection, lightening the communication pressure of MvWSNs. The well-trained deep learning is implanted on the MvWSNs sensor node, an edge computing platform developed via embedded STM32 microcontrollers (STMicroelectronics International NV, Geneva, Switzerland). Data acquisition, data processing, and data classification are all executed on the computing- and energy-constrained sensor node. The experimental results demonstrate that the proposed fault detection method can achieve about 0.99 for the DDS dataset and an accuracy of 0.98 in the MvWSNs sensor node. Furthermore, the final transmission data size is only 0.1% compared to the original data size. It is also a time-saving method that can be accomplished within 135 ms while the raw data will take about 1000 ms to transmit to the monitoring center when there are four sensor nodes in the network. Thus, the proposed edge computing method shows good application prospects in fault detection and control of rotating machinery with high time sensitivity.<\/jats:p>","DOI":"10.3390\/s24165156","type":"journal-article","created":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T11:23:46Z","timestamp":1723461826000},"page":"5156","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Edge Computing and Fault Diagnosis of Rotating Machinery Based on MobileNet in Wireless Sensor Networks for Mechanical Vibration"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7494-4771","authenticated-orcid":false,"given":"Yi","family":"Huang","sequence":"first","affiliation":[{"name":"School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China"},{"name":"Key Laboratory of Optoelectronic Technology & Systems, Ministry of Education, International R & D Center of Micro-Nano Systems and New Materials Technology, Chongqing University, Chongqing 400044, China"}]},{"given":"Shuang","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China"}]},{"given":"Tingqiong","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China"}]},{"given":"Xiaojing","family":"Mu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Technology & Systems, Ministry of Education, International R & D Center of Micro-Nano Systems and New Materials Technology, Chongqing University, Chongqing 400044, China"}]},{"given":"Tianhong","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China"},{"name":"Department of Information and Intelligence Engineering, Chongqing City Vocational College, Chongqing 402160, China"}]},{"given":"Shengxue","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China"},{"name":"Department of Information and Intelligence Engineering, Chongqing City Vocational College, Chongqing 402160, China"}]},{"given":"Guangyong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China"},{"name":"Mining Industry Digital Transformation Laboratory, Mining Institute, T.F. Gorbachev Kuzbass State Technical University, 28 Vesennya St., 650000 Kemerovo, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4538","DOI":"10.1109\/JIOT.2018.2835724","article-title":"IoT-Based Vibration Analytics of Electrical Machines","volume":"5","author":"Ganga","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2449","DOI":"10.1109\/JIOT.2018.2870068","article-title":"IoT-Based Smart Edge for Global Health: Remote Monitoring with Severity Detection and Alerts Transmission","volume":"6","author":"Pathinarupothi","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"110187","DOI":"10.1016\/j.ymssp.2023.110187","article-title":"A concise self-adapting deep learning network for machine remaining useful life prediction","volume":"191","author":"Xiang","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"106994","DOI":"10.1016\/j.ress.2020.106994","article-title":"Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions","volume":"202","author":"Yan","year":"2020","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"112346","DOI":"10.1016\/j.measurement.2022.112346","article-title":"A review of the application of deep learning in intelligent fault diagnosis of rotating machinery","volume":"206","author":"Zhu","year":"2023","journal-title":"Measurement"},{"key":"ref_6","first-page":"1","article-title":"From Anomaly Detection to Novel Fault Discrimination for Wind Turbine Gearboxes with a Sparse Isolation Encoding Forest","volume":"71","author":"Du","year":"2022","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1109\/MIE.2020.3016138","article-title":"Condition Monitoring of Industrial Electric Machines: State of the Art and Future Challenges","volume":"14","author":"Lee","year":"2020","journal-title":"IEEE Ind. Electron. Mag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"9664","DOI":"10.1109\/JIOT.2020.2994200","article-title":"Optimization of Edge-PLC-Based Fault Diagnosis with Random Forest in Industrial Internet of Things","volume":"7","author":"Liu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"106291","DOI":"10.1016\/j.nanoen.2021.106291","article-title":"Reconfigurable optoelectronic memristor for in-sensor computing applications","volume":"89","author":"Wang","year":"2021","journal-title":"Nano Energy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1007\/s40436-022-00433-x","article-title":"Application of sensor data based predictive maintenance and artificial neural networks to enable Industry 4.0","volume":"11","author":"Fordal","year":"2023","journal-title":"Adv. Manuf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"107890","DOI":"10.1016\/j.ymssp.2021.107890","article-title":"Development and experimental validation of self-powered wireless vibration sensor node using vibration energy harvester","volume":"160","author":"Rubes","year":"2021","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_12","first-page":"1","article-title":"Real-Time Fault Diagnosis of Motor Bearing via Improved Cyclostationary Analysis Implemented onto Edge Computing System","volume":"72","author":"He","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Tarokh, M.H., El Houssaini, D., Viehweger, C., and Kanoun, O. (2021). Design of a Wireless Sensor Node Based on MSP430FR5969 for Environment Monitoring Applications, Proceedings of the 2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), Monastir, Tunisia, 22\u201325 March 2021, IEEE.","DOI":"10.1109\/SSD52085.2021.9429293"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1550147719839581","DOI":"10.1177\/1550147719839581","article-title":"An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks","volume":"15","author":"Wang","year":"2019","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"20328","DOI":"10.1109\/JSEN.2022.3209330","article-title":"Sparse Random Reconstruction of Data Loss with Low Redundancy in Wireless Sensor Networks for Mechanical Vibration Monitoring","volume":"22","author":"Huang","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"113710","DOI":"10.1016\/j.eswa.2020.113710","article-title":"A study on adaptation lightweight architecture based deep learning models for bearing fault diagnosis under varying working conditions","volume":"160","author":"Wu","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"037522","DOI":"10.1149\/2.0222003JES","article-title":"Review\u2014Machine Learning Techniques in Wireless Sensor Network Based Precision Agriculture","volume":"167","author":"Mekonnen","year":"2020","journal-title":"J. Electrochem. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4235","DOI":"10.1109\/TII.2019.2902878","article-title":"Artificial Intelligence-Driven Mechanism for Edge Computing-Based Industrial Applications","volume":"15","author":"Sodhro","year":"2019","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Park, D., Kim, S., An, Y., and Jung, J.-Y. (2018). LiReD: A light-weight real-time fault detection system for edge computing using LSTM recurrent neural networks. Sensors, 18.","DOI":"10.3390\/s18072110"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"8287","DOI":"10.1109\/JSEN.2019.2911299","article-title":"In Situ Motor Fault Diagnosis Using Enhanced Convolutional Neural Network in an Embedded System","volume":"20","author":"Lu","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LSENS.2022.3159972","article-title":"Edge-Compatible Convolutional Autoencoder Implemented on FPGA for Anomaly Detection in Vibration Condition-Based Monitoring","volume":"6","author":"Malviya","year":"2022","journal-title":"IEEE Sens. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"8256","DOI":"10.1109\/JSEN.2020.2966049","article-title":"Fuzzy Analytic Hierarchy Process-Based Balanced Topology Control of Wireless Sensor Networks for Machine Vibration Monitoring","volume":"20","author":"Huang","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Sinha, D., and El-Sharkawy, M. (2019, January 10\u201312). Thin mobilenet: An enhanced mobilenet architecture. Proceedings of the 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, USA.","DOI":"10.1109\/UEMCON47517.2019.8993089"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"121470","DOI":"10.1016\/j.eswa.2023.121470","article-title":"Breast cancer diagnosis based on hybrid SqueezeNet and improved chef-based optimizer","volume":"237","author":"Huang","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"106825","DOI":"10.1016\/j.engappai.2023.106825","article-title":"Research on real-time detection method of rail corrugation based on improved ShuffleNet V2","volume":"126","author":"Yang","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"41925","DOI":"10.1109\/ACCESS.2021.3065195","article-title":"An end-to-end intelligent fault diagnosis application for rolling bearing based on MobileNet","volume":"9","author":"Yu","year":"2021","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Pham, M.T., Kim, J.-M., and Kim, C.H. (2020). Deep learning-based bearing fault diagnosis method for embedded systems. Sensors, 20.","DOI":"10.3390\/s20236886"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"124009","DOI":"10.1088\/1361-6501\/ac27ea","article-title":"An intelligent method of roller bearing fault diagnosis and fault characteristic frequency visualization based on improved MobileNet V3","volume":"32","author":"Yao","year":"2021","journal-title":"Meas. Sci. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"122135","DOI":"10.1109\/ACCESS.2020.3007046","article-title":"Li-ion batteries parameter estimation with tiny neural networks embedded on intelligent IoT microcontrollers","volume":"8","author":"Crocioni","year":"2020","journal-title":"IEEE Access"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Jardosh, S., Ranjan, P., and Rawal, D. (2010, January 27\u201329). Prioritized IEEE 802.15.4 for wireless sensor networks. Proceedings of the IEEE Wireless Advanced, London, UK.","DOI":"10.1109\/WIAD.2010.5544872"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/16\/5156\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:34:19Z","timestamp":1760110459000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/16\/5156"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,9]]},"references-count":30,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["s24165156"],"URL":"https:\/\/doi.org\/10.3390\/s24165156","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,9]]}}}