Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing
This paper presents the design and development of a proof of concept (PoC) open-source data logger system for wireless data acquisition via Wi-Fi aimed at bench testing and fault detection in combustion and electric engines. The system integrates multiple sensors, including accelerometers, microphon...
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MDPI AG
2024-12-01
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| Online Access: | https://www.mdpi.com/2411-5134/9/6/120 |
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| author | Marcio Luís Munhoz Amorim Jorge Gomes Lima Norah Nadia Sánchez Torres Jose A. Afonso Sérgio F. Lopes João P. P. do Carmo Lucas Vinicius Hartmann Cicero Rocha Souto Fabiano Salvadori Oswaldo Hideo Ando Junior |
| author_facet | Marcio Luís Munhoz Amorim Jorge Gomes Lima Norah Nadia Sánchez Torres Jose A. Afonso Sérgio F. Lopes João P. P. do Carmo Lucas Vinicius Hartmann Cicero Rocha Souto Fabiano Salvadori Oswaldo Hideo Ando Junior |
| author_sort | Marcio Luís Munhoz Amorim |
| collection | DOAJ |
| description | This paper presents the design and development of a proof of concept (PoC) open-source data logger system for wireless data acquisition via Wi-Fi aimed at bench testing and fault detection in combustion and electric engines. The system integrates multiple sensors, including accelerometers, microphones, thermocouples, and gas sensors, to monitor critical parameters, such as vibration, sound, temperature, and CO<sub>2</sub> levels. These measurements are crucial for detecting anomalies in engine performance, such as ignition and combustion faults. For combustion engines, temperature sensors detect operational anomalies, including diesel engines operating beyond the normal range of 80 °C to 95 °C and gasoline engines between 90 °C and 110 °C. These readings help identify failures in cooling systems, thermostat valves, or potential coolant leaks. Acoustic sensors identify abnormal noises indicative of issues such as belt misalignment, valve knocking, timing irregularities, or loose parts. Vibration sensors detect displacement issues caused by engine mount failures, cracks in the engine block, or defects in pistons and valves. These sensors can work synergistically with acoustic sensors to enhance fault detection. Additionally, CO<sub>2</sub> and organic compound sensors monitor fuel combustion efficiency and detect failures in the exhaust system. For electric motors, temperature sensors help identify anomalies, such as overloads, bearing problems, or excessive shaft load. Acoustic sensors diagnose coil issues, phase imbalances, bearing defects, and faults in chain or belt systems. Vibration sensors detect shaft and bearing problems, inadequate motor mounting, or overload conditions. The collected data are processed and analyzed to improve engine performance, contributing to reduced greenhouse gas (GHG) emissions and enhanced energy efficiency. This PoC system leverages open-source technology to provide a cost-effective and versatile solution for both research and practical applications. Initial laboratory tests validate its feasibility for real-time data acquisition and highlight its potential for creating datasets to support advanced diagnostic algorithms. Future work will focus on enhancing telemetry capabilities, improving Wi-Fi and cloud integration, and developing machine learning-based diagnostic methodologies for combustion and electric engines. |
| format | Article |
| id | doaj-art-0a3d44e700fc46fa952c1aa1153f2bb2 |
| institution | Kabale University |
| issn | 2411-5134 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Inventions |
| spelling | doaj-art-0a3d44e700fc46fa952c1aa1153f2bb22024-12-27T14:31:36ZengMDPI AGInventions2411-51342024-12-019612010.3390/inventions9060120Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench TestingMarcio Luís Munhoz Amorim0Jorge Gomes Lima1Norah Nadia Sánchez Torres2Jose A. Afonso3Sérgio F. Lopes4João P. P. do Carmo5Lucas Vinicius Hartmann6Cicero Rocha Souto7Fabiano Salvadori8Oswaldo Hideo Ando Junior9Group of Metamaterials Microwaves and Optics (GMeta), Department of Electrical Engineering (SEL), University of São Paulo (USP), Avenida Trabalhador São-Carlense, Nr. 400, Parque Industrial Arnold Schmidt, São Carlos 05508-220, SP, BrazilSmart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-970, PB, BrazilResearch Group on Energy & Energy Sustainability (GPEnSE), Academic Unit of Cabo de Santo Agostinho (UACSA), Federal Rural University of Pernambuco (UFRPE), Cabo de Santo Agostinho 54518-430, PE, BrazilCenter for Microelectromechanical Systems (CMEMS), University of Minho, 4800-058 Guimarães, PortugalCentro Algoritmi (LASI), University of Minho, 4704-553 Guimarães, PortugalGroup of Metamaterials Microwaves and Optics (GMeta), Department of Electrical Engineering (SEL), University of São Paulo (USP), Avenida Trabalhador São-Carlense, Nr. 400, Parque Industrial Arnold Schmidt, São Carlos 05508-220, SP, BrazilSmart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-970, PB, BrazilSmart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-970, PB, BrazilSmart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-970, PB, BrazilSmart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-970, PB, BrazilThis paper presents the design and development of a proof of concept (PoC) open-source data logger system for wireless data acquisition via Wi-Fi aimed at bench testing and fault detection in combustion and electric engines. The system integrates multiple sensors, including accelerometers, microphones, thermocouples, and gas sensors, to monitor critical parameters, such as vibration, sound, temperature, and CO<sub>2</sub> levels. These measurements are crucial for detecting anomalies in engine performance, such as ignition and combustion faults. For combustion engines, temperature sensors detect operational anomalies, including diesel engines operating beyond the normal range of 80 °C to 95 °C and gasoline engines between 90 °C and 110 °C. These readings help identify failures in cooling systems, thermostat valves, or potential coolant leaks. Acoustic sensors identify abnormal noises indicative of issues such as belt misalignment, valve knocking, timing irregularities, or loose parts. Vibration sensors detect displacement issues caused by engine mount failures, cracks in the engine block, or defects in pistons and valves. These sensors can work synergistically with acoustic sensors to enhance fault detection. Additionally, CO<sub>2</sub> and organic compound sensors monitor fuel combustion efficiency and detect failures in the exhaust system. For electric motors, temperature sensors help identify anomalies, such as overloads, bearing problems, or excessive shaft load. Acoustic sensors diagnose coil issues, phase imbalances, bearing defects, and faults in chain or belt systems. Vibration sensors detect shaft and bearing problems, inadequate motor mounting, or overload conditions. The collected data are processed and analyzed to improve engine performance, contributing to reduced greenhouse gas (GHG) emissions and enhanced energy efficiency. This PoC system leverages open-source technology to provide a cost-effective and versatile solution for both research and practical applications. Initial laboratory tests validate its feasibility for real-time data acquisition and highlight its potential for creating datasets to support advanced diagnostic algorithms. Future work will focus on enhancing telemetry capabilities, improving Wi-Fi and cloud integration, and developing machine learning-based diagnostic methodologies for combustion and electric engines.https://www.mdpi.com/2411-5134/9/6/120open-source codedata loggerInternet of Thingswireless communicationcombustion engineselectrical engines |
| spellingShingle | Marcio Luís Munhoz Amorim Jorge Gomes Lima Norah Nadia Sánchez Torres Jose A. Afonso Sérgio F. Lopes João P. P. do Carmo Lucas Vinicius Hartmann Cicero Rocha Souto Fabiano Salvadori Oswaldo Hideo Ando Junior Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing Inventions open-source code data logger Internet of Things wireless communication combustion engines electrical engines |
| title | Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing |
| title_full | Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing |
| title_fullStr | Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing |
| title_full_unstemmed | Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing |
| title_short | Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing |
| title_sort | open source data logger system for real time monitoring and fault detection in bench testing |
| topic | open-source code data logger Internet of Things wireless communication combustion engines electrical engines |
| url | https://www.mdpi.com/2411-5134/9/6/120 |
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