Abstract detail

391 / 2022-02-01 07:04:17
On the automated failure diagnostic system for the hydraulic pressing machine
Failure diagnostic,Failure prediction,Hydraulic pressing machine,Vibration measurement
Machine condition monitoring and fault diagnosis
Final Paper
Zhe LI / Toyama Prefectural University
Taisei Kusano / Toyama Prefectural University
Naoyuki Takeda / Toyama Prefectural University
Osamu Terashima / Toyama Prefectural University
In recent years, owing to the effects of the global coronavirus pandemic and decline of the working-age population, production efficiency and labor productivity are being actively improved in manufacturing and production sites by the introduction of digital technologies. Given these trends, we have developed a system to determine the manufacturing statuses of machines at the early stage to aid production efficiency within a manufacturing company. To detect failures and abnormalities in hydraulic presses at the early stages, we have built and commenced operation of a failure diagnostic system using machine learning. A sensor that measures vibration acceleration is attached to the cylinder, oil pump, and pump drive motor, which are the main parts of the press machine; signals are continuously collected, and the signal for normal operation is modeled on the basis of the standard deviation, crest factor, and maximum signal values. Failures and abnormalities are also detected on the basis of the amount of temporal changes and deviations of the model. Thus, the possibility to predict the time to failure by monitoring such variations is shown.

Countdown

  • 00

    Days

  • 00

    Hours

  • 00

    Minutes

  • 00

    Seconds

Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

Contact Us

  Tel: 86-0532-6897 5191 (Ms Yuan)

  Mob: 184 5327 6561
  E-mailsecretariat@apvc2021.org
               organizer@apvc2021.org

Visitors