Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine
Nowadays, fault diagnostics is widely applied under Industry 4.0 to reduce machine maintenance costs, improve productivity, and increase machine availability. However, fault diagnostics are mostly post-mortem. When the fault is identified, it is already too late because damages have been done to the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/3/1708 |
| _version_ | 1797488903775584256 |
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| author | Shi Feng John P. T. Mo |
| author_facet | Shi Feng John P. T. Mo |
| author_sort | Shi Feng |
| collection | DOAJ |
| description | Nowadays, fault diagnostics is widely applied under Industry 4.0 to reduce machine maintenance costs, improve productivity, and increase machine availability. However, fault diagnostics are mostly post-mortem. When the fault is identified, it is already too late because damages have been done to the product and machine. This paper compares the efficacy of several signal data processing techniques for detecting faults that are about to occur. Our aim is to find an efficient way to predict the fault before it occurs. A continuous wavelet transform synchrosqueezed scalogram was found to be most suitable for this purpose, but it is difficult to apply. A novel procedure is proposed to count the number of pulses in the synchrosqueezed scalogram. A new method for detecting the trend from the pulse counts is then developed to predict the fault before it happens. The procedure and method are illustrated with experimental data collected while running an automated double-thread trampoline webbing machine. |
| first_indexed | 2024-03-10T00:08:56Z |
| format | Article |
| id | doaj.art-36bab9211efb4f32b32884596485df0c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:08:56Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-36bab9211efb4f32b32884596485df0c2023-11-23T16:02:09ZengMDPI AGApplied Sciences2076-34172022-02-01123170810.3390/app12031708Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing MachineShi Feng0John P. T. Mo1School of Engineering, RMIT University, Melbourne, VIC 3083, AustraliaSchool of Engineering, RMIT University, Melbourne, VIC 3083, AustraliaNowadays, fault diagnostics is widely applied under Industry 4.0 to reduce machine maintenance costs, improve productivity, and increase machine availability. However, fault diagnostics are mostly post-mortem. When the fault is identified, it is already too late because damages have been done to the product and machine. This paper compares the efficacy of several signal data processing techniques for detecting faults that are about to occur. Our aim is to find an efficient way to predict the fault before it occurs. A continuous wavelet transform synchrosqueezed scalogram was found to be most suitable for this purpose, but it is difficult to apply. A novel procedure is proposed to count the number of pulses in the synchrosqueezed scalogram. A new method for detecting the trend from the pulse counts is then developed to predict the fault before it happens. The procedure and method are illustrated with experimental data collected while running an automated double-thread trampoline webbing machine.https://www.mdpi.com/2076-3417/12/3/1708Statistical Process Control (SPC)Fast Fourier Transform (FFT)continuous wavelet transform (CWT)synchrosqueezed wavelet transformscalogrampulse time graphs |
| spellingShingle | Shi Feng John P. T. Mo Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine Applied Sciences Statistical Process Control (SPC) Fast Fourier Transform (FFT) continuous wavelet transform (CWT) synchrosqueezed wavelet transform scalogram pulse time graphs |
| title | Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine |
| title_full | Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine |
| title_fullStr | Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine |
| title_full_unstemmed | Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine |
| title_short | Efficacy Study of Fault Trending Algorithm to Prevent Fault Occurrence on Automatic Trampoline Webbing Machine |
| title_sort | efficacy study of fault trending algorithm to prevent fault occurrence on automatic trampoline webbing machine |
| topic | Statistical Process Control (SPC) Fast Fourier Transform (FFT) continuous wavelet transform (CWT) synchrosqueezed wavelet transform scalogram pulse time graphs |
| url | https://www.mdpi.com/2076-3417/12/3/1708 |
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