Sound based fault classify diagnosis method using artificial neural network and autoencoder processing
- Resource Type
- Conference
- Authors
- Lin, Ke Wei; Lin, Wei Ling; Tsai, Ying Pin; Hsiao, Fu Li
- Source
- 2023 Sixth International Symposium on Computer, Consumer and Control (IS3C) IS3C Computer, Consumer and Control (IS3C), 2023 Sixth International Symposium on. :371-373 Jun, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Training
Fault diagnosis
Costs
Neurons
Process control
Artificial neural networks
Quality control
fault diagnosis
neural network
confusion figure
- Language
- ISSN
- 2770-0496
We achieved a fault diagnosis for a certain air pump using an artificial neural network. The operating sound of the pump is recorded by a single microphone, after processing by an unsupervised autoencoder, 108 groups of samples containing only 1-second audio data are inputted to the neural network classifier. The training rounds and the neurons of the autoencoder are tested. After training, the provided detection network can finally give the classifying accuracy of up to 99% according to 1-sec sound data.