Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm
Without integrating various sensor data sets, sensing information in the presence of leakage for large-scale pipeline systems is very challenging. A data fusion methodology, wherein more sensor data is merged to give relevant information, is necessary to transform the challenging process into a stra...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-10-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917422000393 |
| _version_ | 1811281069682458624 |
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| author | Hariprasath Manoharan S. Shitharth K. Sangeetha B. Praveen Kumar Mustapha Hedabou |
| author_facet | Hariprasath Manoharan S. Shitharth K. Sangeetha B. Praveen Kumar Mustapha Hedabou |
| author_sort | Hariprasath Manoharan |
| collection | DOAJ |
| description | Without integrating various sensor data sets, sensing information in the presence of leakage for large-scale pipeline systems is very challenging. A data fusion methodology, wherein more sensor data is merged to give relevant information, is necessary to transform the challenging process into a straightforward step-by-step operation. Ultrasonic sensors are used in stage 1 to identify any ambiguities in pipeline systems, and various sites are used to gauge the rate of leak detection. As a result, a novel model for estimating various types of gas leakage in pipeline systems is examined, put to the test, and contrasted. Five distinct scenarios are seen during the leakage testing procedure using data fusion, where the optimization is done using the fuzzy interface technique. This integration procedure detects leakage rates with high accuracy, and in every test instance, the best outcomes are obtained. Additionally, the predicted model can be used in real-time with a low failure rate of numerous sensors, with MATLAB being used to simulate the results. |
| first_indexed | 2024-04-13T01:25:53Z |
| format | Article |
| id | doaj.art-d38262545ffb47a6af31d1caa3acc4d8 |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2024-04-13T01:25:53Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-d38262545ffb47a6af31d1caa3acc4d82022-12-22T03:08:38ZengElsevierMeasurement: Sensors2665-91742022-10-0123100405Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithmHariprasath Manoharan0S. Shitharth1K. Sangeetha2B. Praveen Kumar3Mustapha Hedabou4Department of Electronics and Communication Engineering, Panimalar Engineering College, Poonamallee, Chennai, IndiaDepartment of Computer Science & Engineering, Kebri Dehar University, Kebri Dehar, Ethiopia; Corresponding author.Department of Computer Science & Engineering, Kebri Dehar University, Kebri Dehar, EthiopiaDepartment of Electrical and Electronics Engineering, Vardhaman College of Engineering, Hyderabad, 501218, IndiaSchool of Computer Science, University Mohammed VI Polytechnic, Benguerir, MoroccoWithout integrating various sensor data sets, sensing information in the presence of leakage for large-scale pipeline systems is very challenging. A data fusion methodology, wherein more sensor data is merged to give relevant information, is necessary to transform the challenging process into a straightforward step-by-step operation. Ultrasonic sensors are used in stage 1 to identify any ambiguities in pipeline systems, and various sites are used to gauge the rate of leak detection. As a result, a novel model for estimating various types of gas leakage in pipeline systems is examined, put to the test, and contrasted. Five distinct scenarios are seen during the leakage testing procedure using data fusion, where the optimization is done using the fuzzy interface technique. This integration procedure detects leakage rates with high accuracy, and in every test instance, the best outcomes are obtained. Additionally, the predicted model can be used in real-time with a low failure rate of numerous sensors, with MATLAB being used to simulate the results.http://www.sciencedirect.com/science/article/pii/S2665917422000393Data fusionMultiple sensorsLeakageFuzzy interface |
| spellingShingle | Hariprasath Manoharan S. Shitharth K. Sangeetha B. Praveen Kumar Mustapha Hedabou Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm Measurement: Sensors Data fusion Multiple sensors Leakage Fuzzy interface |
| title | Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm |
| title_full | Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm |
| title_fullStr | Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm |
| title_full_unstemmed | Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm |
| title_short | Detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm |
| title_sort | detection of superfluous in channels using data fusion with wireless sensors and fuzzy interface algorithm |
| topic | Data fusion Multiple sensors Leakage Fuzzy interface |
| url | http://www.sciencedirect.com/science/article/pii/S2665917422000393 |
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