A data size reduction approach applicable in process control system of oil and gas plants
| dc.contributor.author | Madhuranthakam, Chandra Mouli | |
| dc.contributor.author | Hourfar, Farzad | |
| dc.contributor.author | Abbasinejad, Reza | |
| dc.contributor.author | Elkamel, Ali | |
| dc.date.accessioned | 2024-08-13T08:57:42Z | |
| dc.date.available | 2024-08-13T08:57:42Z | |
| dc.date.issued | 2020 | |
| dc.description | In order to respond to increasing demand for safe and efficient oil and gas plant operation while considering environmental regulations, the subject of “process control” has become increasingly important in recent years [1]. In process control systems, some activities such as supervisory control, data logging and performance monitoring, with their hierarchical relation illustrated in Figure 1, are pursued based on available process variables [2]. These variables include pressure and flow rate of fluids, temperature of flame or materials, liquid level in tanks, and other quantitative items [3]. Some of these variables are measured by sensors, transferred on industrial networks, processed in distributed or central control systems, and monitored in control consoles [4]. Management of the huge amount of process variables of chemical process plants is recently categorized as a “BIG-DATA” concept [5]. Transmission and storage of these variables has considerable cost in many industrial plants, such as oil and gas refineries, and so reduction of these expenses is vital for managers [6]. | |
| dc.description.abstract | In oil and gas plants, the cost of devices applicable for supervising and controlling systems directly depends on the transmission and storage systems, which are related to the data size of process variables. In this paper, process variables frequency-domain and statistical analysis results have been studied to infer if there exists any possibility to reduce data size of the process variables without loss of any necessary information. Although automatic control is not applicable in a shutdown condition, for generalization of the obtained results, unscheduled shutdown data has also been analyzed and studied. The main goal of this paper is to develop an applicable algorithm for oil and gas plants to decrease the data size in controlling and monitoring systems, based on well-known and powerful mathematical techniques. The results show that it is possible to reduce the size of data dramatically (more than 99% for controlling, and more than 55% for monitoring purposes in comparison with existing methods), without loss of vital information and performance quality. keywords: Data size reduction; Statistics; Supervisory control system; Time series analysis; Variable structure control | |
| dc.identifier.citation | Abbasinejad, R., Hourfar, F., Madhuranthakam, C. M. R., & Elkamel, A. (2020). A data size reduction approach applicable in process control system of oil and gas plants. Sustainability, 12(2), 639. | |
| dc.identifier.doi | https://doi.org/10.3390/su12020639 | |
| dc.identifier.uri | https://repository.adu.ac.ae/handle/1/6152 | |
| dc.language.iso | en | |
| dc.publisher | MDPI | |
| dc.title | A data size reduction approach applicable in process control system of oil and gas plants | |
| dc.type | Article |