Literature DB >> 34372210

A Survey on the Application of WirelessHART for Industrial Process Monitoring and Control.

P Arun Mozhi Devan1, Fawnizu Azmadi Hussin1, Rosdiazli Ibrahim1, Kishore Bingi2, Farooq Ahmad Khanday3.   

Abstract

Industrialization has led to a huge demand for a network control system to monitor and control multi-loop processes with high effectiveness. Due to these advancements, new industrial wireless sensor network (IWSN) standards such as ZigBee, WirelessHART, ISA 100.11a wireless, and Wireless network for Industrial Automation-Process Automation (WIA-PA) have begun to emerge based on their wired conventional structure with additional developments. This advancement improved flexibility, scalability, needed fewer cables, reduced the network installation and commissioning time, increased productivity, and reduced maintenance costs compared to wired networks. On the other hand, using IWSNs for process control comes with the critical challenge of handling stochastic network delays, packet drop, and external noises which are capable of degrading the controller performance. Thus, this paper presents a detailed study focusing only on the adoption of WirelessHART in simulations and real-time applications for industrial process monitoring and control with its crucial challenges and design requirements.

Entities:  

Keywords:  WirelessHART; automation; control system; fractional-order control; industrial wireless sensor networks; network control system; process control; wireless control

Year:  2021        PMID: 34372210     DOI: 10.3390/s21154951

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

1.  Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems.

Authors:  Willie H Mims; Michael A Temple; Robert F Mills
Journal:  Sensors (Basel)       Date:  2022-06-29       Impact factor: 3.847

2.  Fast Fault Diagnosis in Industrial Embedded Systems Based on Compressed Sensing and Deep Kernel Extreme Learning Machines.

Authors:  Nanliang Shan; Xinghua Xu; Xianqiang Bao; Shaohua Qiu
Journal:  Sensors (Basel)       Date:  2022-05-25       Impact factor: 3.847

3.  An Arithmetic-Trigonometric Optimization Algorithm with Application for Control of Real-Time Pressure Process Plant.

Authors:  P Arun Mozhi Devan; Fawnizu Azmadi Hussin; Rosdiazli B Ibrahim; Kishore Bingi; M Nagarajapandian; Maher Assaad
Journal:  Sensors (Basel)       Date:  2022-01-13       Impact factor: 3.576

  3 in total

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