Development of an Abnormal Sound Detection System for Rotating Bodies Using Deep Learning
| العنوان: | Development of an Abnormal Sound Detection System for Rotating Bodies Using Deep Learning |
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| المؤلفون: | Haiyoung Jung, Hoseung Shin, Myunggoo Jung, Bohee Lee |
| المصدر: | Fire Science and Engineering. 37:81-88 |
| بيانات النشر: | Korea Institute of Fire Science and Engineering, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Industrial and Manufacturing Engineering |
| الوصف: | Conveyor systems have a rotating body component that generates various sound signals when malfunction occurs. This work studies the development of a system that collects sound signal data generated during operation of a rotating body, applies an artificial intelligence (AI) algorithm over the data, and diagnoses if the motion of the rotating body is abnormal. The conveyor belt system is installed in various working environments such as mines and factories and consists of a number of rotors. Multiple connected data collection devices developed in this work are placed around the conveyor belt rotors to detect abnormalities in the rotors. Each collection device is equipped with the AI algorithm, which performs the data preprocessing on the sound data collected by each device. For the diagnosis of the rotor failure, sound data collected from the devices are converted to 2D spectrogram images, and a convolutional neural network model is applied to the converted images for determining the status of the rotating body which is transmitted as normal or failure to the manager via Ethernet TCP/IP protocol. |
| تدمد: | 2765-088X 2765-060X |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::dbe0663923433a5816f76550f66bdcd3 https://doi.org/10.7731/kifse.4ffc23a9 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........dbe0663923433a5816f76550f66bdcd3 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 2765088X 2765060X |
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