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Fault Detection in Wastewater Treatment : = Process Supervision to Improve Wastewater Reuse.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Fault Detection in Wastewater Treatment :/
其他題名:	Process Supervision to Improve Wastewater Reuse.
作者:	Ivan, Heidi Lynn.
面頁冊數:	1 online resource (80 pages)
附註:	Source: Masters Abstracts International, Volume: 84-09.
Contained By:	Masters Abstracts International84-09.
標題:	Simulation. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30415269click for full text (PQDT)
ISBN:	9798377628897

Fault Detection in Wastewater Treatment : = Process Supervision to Improve Wastewater Reuse.
Ivan, Heidi Lynn.

Fault Detection in Wastewater Treatment :Process Supervision to Improve Wastewater Reuse. - 1 online resource (80 pages)

Source: Masters Abstracts International, Volume: 84-09.

Thesis (Licentiate)--Malardalen University (Sweden), 2023.

Includes bibliographical references

As wastewater treatment plants transition to water resource recovery facilities, the need for improved control and consequently supervision increases. Despite the large volume of research that has been performed on this topic, the use in industry is scarce. Practical implementation is challenging due to the nature of the process, and a lack of standardisation in the research results in uncertainty as to the state of the art. This is one of the main challenges identified. Experimental work is performed using the Benchmark Simulation Model No. 1 to identify monitoring requirements and evaluate the performance of univariate fault detection methods. For the former, residual based process fault signatures are used to determine minimal sensor requirements based on detectability and isolability goals. Sensor faults are the focus of the latter issue, using the Shewhart, cumulative sum, and exponentially weighted moving average control charts to detect bias and drift faults in a controlled variable sensor. The use of a standard model and known fault detection methods is useful to establish a baseline for future work. Given the lack of standardised use in industry this is considered critical. Both proposed methods emphasise ease of visualisation which is beneficial for industrial implementation.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798377628897Subjects--Topical Terms:

644748
Simulation.
Index Terms--Genre/Form:

542853
Electronic books.

Fault Detection in Wastewater Treatment : = Process Supervision to Improve Wastewater Reuse.
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100 1 $a Ivan, Heidi Lynn. $3 3695530
245 1 0 $a Fault Detection in Wastewater Treatment : $b Process Supervision to Improve Wastewater Reuse.
264 0 $c 2023
300 $a 1 online resource (80 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Masters Abstracts International, Volume: 84-09.
500 $a Advisor: Odlare, Monica ; Zaccaria, Valentina ; Skvaril, Jan.
502 $a Thesis (Licentiate)--Malardalen University (Sweden), 2023.
504 $a Includes bibliographical references
520 $a As wastewater treatment plants transition to water resource recovery facilities, the need for improved control and consequently supervision increases. Despite the large volume of research that has been performed on this topic, the use in industry is scarce. Practical implementation is challenging due to the nature of the process, and a lack of standardisation in the research results in uncertainty as to the state of the art. This is one of the main challenges identified. Experimental work is performed using the Benchmark Simulation Model No. 1 to identify monitoring requirements and evaluate the performance of univariate fault detection methods. For the former, residual based process fault signatures are used to determine minimal sensor requirements based on detectability and isolability goals. Sensor faults are the focus of the latter issue, using the Shewhart, cumulative sum, and exponentially weighted moving average control charts to detect bias and drift faults in a controlled variable sensor. The use of a standard model and known fault detection methods is useful to establish a baseline for future work. Given the lack of standardised use in industry this is considered critical. Both proposed methods emphasise ease of visualisation which is beneficial for industrial implementation.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Simulation. $3 644748
650 4 $a Resource recovery. $3 3683855
650 4 $a Freshwater resources. $3 3687616
650 4 $a Water treatment. $3 3683746
650 4 $a Feedback. $3 677181
650 4 $a Sensors. $3 3549539
650 4 $a Water resources management. $3 794747
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690 $a 0595
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Malardalen University (Sweden). $3 3695531
773 0 $t Masters Abstracts International $g 84-09.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30415269 $z click for full text (PQDT)