A Factory Health Monitor: System identification, process monitoring, and control

Schroeder, Kyle; Moyne, James; Tilbury, Dawn M.

doi:10.1109/coase.2008.4626536

Cited by 6 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, a model-based approach is introduced to be exploited for change detection and isolation when the performance of the system degrades. Other process monitoring methods, such as [9], describes how controllers can be altered to optimize system efficiency for controllers developed separately from one another. This is useful for the methodology outlined for the power plant, as it proposes that the components are validated apart from the rest of the system with the goal of re-identifying the components when necessary.…”

Section: Related Workmentioning

confidence: 99%

Validation of power plant models using field data with application to the Mostar hydroelectric plant

Podlaski¹,

Bombois²,

Vanfretti³

2022

International Journal of Electrical Power & Energy Systems

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

Validation of power plant models using field data with application to the Mostar hydroelectric plant

Podlaski¹,

Bombois²,

Vanfretti³

2022

International Journal of Electrical Power & Energy Systems

View full text Add to dashboard Cite

“…Numerous industrial and work place hazards necessitate a system that monitors the conditions of a factory area. A factory health monitoring system was created to improve industrial processes by reducing the handling of dangerous things time required [ 3 ]. By using their smart phones, managers can instantly monitor a factory area.…”

Section: Introductionmentioning

confidence: 99%

Mobile Monitoring and Embedded Control System for Factory Environment

Lian

Hsiao

Sung

2013

Sensors

View full text Add to dashboard Cite

This paper proposes a real-time method to carry out the monitoring of factory zone temperatures, humidity and air quality using smart phones. At the same time, the system detects possible flames, and analyzes and monitors electrical load. The monitoring also includes detecting the vibrations of operating machinery in the factory area. The research proposes using ZigBee and Wi-Fi protocol intelligent monitoring system integration within the entire plant framework. The sensors on the factory site deliver messages and real-time sensing data to an integrated embedded systems via the ZigBee protocol. The integrated embedded system is built by the open-source 32-bit ARM (Advanced RISC Machine) core Arduino Due module, where the network control codes are built in for the ARM chipset integrated controller. The intelligent integrated controller is able to instantly provide numerical analysis results according to the received data from the ZigBee sensors. The Android APP and web-based platform are used to show measurement results. The built-up system will transfer these results to a specified cloud device using the TCP/IP protocol. Finally, the Fast Fourier Transform (FFT) approach is used to analyze the power loads in the factory zones. Moreover, Near Field Communication (NFC) technology is used to carry out the actual electricity load experiments using smart phones.

show abstract

“…The proposed system is based on Arduino web server architecture. Operator can remotely log in this monitoring system via his smartphone [1]. This intelligent monitoring system is very suitable for the management and control of the factory area [2] [3].…”

Section: Introductionmentioning

confidence: 99%

Mobile Device Monitoring System in the Plant by an Innovative Approach

Lian

Hsiao

Sung

et al. 2013

AMM

View full text Add to dashboard Cite

This This paper proposed method is to use a Smart phone in the real - time situation to carry out monitoring and controlling factory zone temperature, humidity, air quality, flame detection, staff not near the danger zone detection and electrical load analysis. The monitoring range also includes operating machine vibration detection in the factory area, so these methods are innovative research. Our research proposes the integration of ZigBee and Wi-Fi protocol intelligent monitoring system within the framework of the entire plant. The factory sensor using the ZigBee protocol to deliver the message, and real-time sensing data is sent to our integrated embedded systems. Our paper presents an integrated embedded systems using the open-source Arduino DUE module, which is a 32-bit ARM core. Our study proposed a way that writes the network code to ARM chipset become integrated controller. The intelligent integrated controller will instantly analytical processing by the ZigBee sensor pass to the message. Simultaneously this study using Android APP and web-based methods to show the measurement results. The web-based and Android APP approaches will transfer these results to specify the cloud device by way of the TCP / IP protocol. Finally, this paper utilizes FFT (Fast Fourier Transform) approach to analysis of power loads in the factory zones. Simultaneously this study also uses NFC (Near Field Communication) technology to carry out the actual measurement of the total electricity load experiments by smart phones.

show abstract

A Factory Health Monitor: System identification, process monitoring, and control

Cited by 6 publications

References 7 publications

Validation of power plant models using field data with application to the Mostar hydroelectric plant

Validation of power plant models using field data with application to the Mostar hydroelectric plant

Mobile Monitoring and Embedded Control System for Factory Environment

Mobile Device Monitoring System in the Plant by an Innovative Approach

Contact Info

Product

Resources

About