Machine Signature Integrity and Data Trends Monitoring, a Diagnostic Approach to Fault Detection

Adeyeri, Michael Kanisuru

doi:10.1007/978-3-319-65497-3_2

Cited by 2 publications

(2 citation statements)

References 46 publications

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“…Several methods have been applied by different researchers to develop machine signatures and predict the remaining useful life (RUL) of machine components. Adeyeri (2018), used machine history and its present data through monitoring as a tool for detecting faults. Also, Adebena and Jae-Cheon, (2020) posited that a monitoring program is said to be a function of set parameters that were put in place at a predefined set range to provide signals or alerts whenever there is an incipient fault on the machine system.…”

Section: Introductionmentioning

confidence: 99%

Establishment of Machine Signature for Pulverizing Machine

2023

EPPM-Journal

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Production activities suffered setbacks due to incessant machine breakdown caused by an incipient fault that occurred without prior notification has become worrisome to industrialists or machine users and brought delay to production and products optimization processes. Hence, the need to establish machine signature as a means of assisting plant operators to optimally maintain such machines. Therefore, this paperwork focuses on the establishment of a signature for a developed plantain flour pulverizing machine. In carrying out this research, the pulverizing machine condition data was retrieved under two conditions, namely without degradation; and with imposed degradation at different loading capacities using a data logger to monitor in real-time responses of the machine to operating conditions such as temperature, vibration, and sound. Retrieved data was analyzed using signal analyzer 8.0 in MATLAB software and signal analyzer in Origin software where the signature of pulverizing machine was established under different conditions. A regression model was established for the pulverizing machine using the aforementioned stated conditions. A logarithm function trend describes the operation characteristic note of the machine. Validation of this trend was done, and the result showed that pulverizing machine signature without degradation and imposed degradation have a distinct characteristic. Thus, the study outcome forms the basis for developing a predictive maintenance system for the pulverizing machine which distinguishes it as a novel tool for predictive maintenance and condition monitoring of machinery in the industry.

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Section: Introductionmentioning

confidence: 99%

Establishment of Machine Signature for Pulverizing Machine

2023

EPPM-Journal

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“…[2]. Along with this as safety is also a major concern in industry, so here we will design safety analysis for the machines as well as for a worker, here with help of a approach named accident reduction model which help us in determining the respective weights of human, machine security and work environmental safety for the decision making process in problem [3].But this safety concern is all about safety from the machines or of the machines, as the unwanted signals which we called noise can make machines unable to take decision so, we are detecting as well as rectifying noise, as when there is a difference between machine past and present it generate a noise and with help of algorithms we can rectify that noise, so whenever we get noise instead of only identify it will rectify too [4].For this rectification we have to check machine state regularly so, we are introducing a condition checking process in which we get to know about the machine state without intruding on its working, these checking processes is used to check vibrations, examine engine current mark etc. these we can use to check deformities [5].…”

Section: Introductionmentioning

confidence: 99%

Wireless Sensor Network and Industrial Internet of Things Based Industrial Machinery Control and Noise Detector

Singh¹,

Gehlot²,

Sharma³

2019

IJITEE

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This paper describes a wireless sensor network and industrial internet of things based Industry machinery control and noise detector, where the using control platform is Arduino, While TCP and IOT is serving as a communication protocol. The function of Arduino is to understand data destination along with the functioning of data to that machine similarly sensors used to take information at their level and fed back for the proper functioning. This paper aims in designing a convenient wireless industry where cabling is not possible. It also has lower installation and maintenance charge for flexible Industry. This paper presents the measurement and reduction of noise from the machines for the betterment of workers.

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Machine Signature Integrity and Data Trends Monitoring, a Diagnostic Approach to Fault Detection

Cited by 2 publications

References 46 publications

Establishment of Machine Signature for Pulverizing Machine

Establishment of Machine Signature for Pulverizing Machine

Wireless Sensor Network and Industrial Internet of Things Based Industrial Machinery Control and Noise Detector

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