Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing
<p dir="ltr">Hydrogen sulfide (H<sub>2</sub>S) presents many hazardous traits such as corrosive, explosive, toxic, and flammable. It is slightly denser than air, and a mixture of H<sub>2</sub>S and air can be volatile. Therefore, a reliable and robust measurem...
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2021
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| _version_ | 1864513561664946176 |
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| author | Ahmed Alsarraj (16876014) |
| author2 | Atiq ur Rehman (14153391) Samir Brahim Belhaouari (9427347) Khaled M. Saoud (16876017) Amine Bermak (1895947) |
| author2_role | author author author author |
| author_facet | Ahmed Alsarraj (16876014) Atiq ur Rehman (14153391) Samir Brahim Belhaouari (9427347) Khaled M. Saoud (16876017) Amine Bermak (1895947) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ahmed Alsarraj (16876014) Atiq ur Rehman (14153391) Samir Brahim Belhaouari (9427347) Khaled M. Saoud (16876017) Amine Bermak (1895947) |
| dc.date.none.fl_str_mv | 2021-10-26T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/tim.2021.3120150 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Hydrogen_Sulfide_H_sub_2_sub_S_Sensor_A_Concept_of_Physical_Versus_Virtual_Sensing/24025251 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electronics, sensors and digital hardware Information and computing sciences Machine learning Sensor arrays Sensors Temperature sensors Mathematical models Costs Atmospheric modeling Tungsten Electronic nose Gas estimation Mathematical modeling Neural networks (NNs) Virtual sensing |
| dc.title.none.fl_str_mv | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Hydrogen sulfide (H<sub>2</sub>S) presents many hazardous traits such as corrosive, explosive, toxic, and flammable. It is slightly denser than air, and a mixture of H<sub>2</sub>S and air can be volatile. Therefore, a reliable and robust measurement system is required to effectively detect and quantify H<sub>2</sub>S in many applications, such as oil and gas industries. There are several methods available in the literature to quantify H<sub>2</sub>S in fuel gases; however, only a few are available in case of air samples. Furthermore, array-based sensors are more reliable in the detection of volatile organic compounds (VOCs); however, sensor arrays are more expensive and challenging to produce. To overcome the limitations of producing physical sensor arrays, this article proposes a concept of virtual sensing that enables to augment a single sensing platform into a virtual array, thus, increasing the detection accuracy at no extra cost of producing a large physical sensors array. The merits of the proposed system are as follows: 1) a virtual sensing concept is combined with a physical sensing platform to enhance the proposed model’s estimation power in quantifying H<sub>2</sub>S in air samples; 2) a new feature extraction method based on fractional derivatives is proposed to further enhance the model’s learning capabilities; 3) an array of four gas sensors is fabricated in the in-house foundry to record and analyze the signature of H<sub>2</sub>S at various concentration levels; 4) a shallow neural network (NN) model is trained and tested on the recorded data, and based on the NN’s input–output relation, a mathematical model is presented for the quantification of H<sub>2</sub>S; and 5) the proposed model is a highly sensitive and reliable H<sub>2</sub>S gas sensing scheme with the ability to detect the gas instantaneously. The proposed gas quantification model has the advantages of being low cost, easy to implement, and fast operation compared with the analytical solutions. Furthermore, it is extensively tested and validated using real gas data.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Transactions on Instrumentation and Measurement<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/tim.2021.3120150" target="_blank">https://dx.doi.org/10.1109/tim.2021.3120150</a></p><p dir="ltr">Additional institutions affiliated with: Liberal Arts and Science Program - VCUarts Qatar</p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_0d388810b14fc4f575a008f307767f52 |
| identifier_str_mv | 10.1109/tim.2021.3120150 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24025251 |
| publishDate | 2021 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual SensingAhmed Alsarraj (16876014)Atiq ur Rehman (14153391)Samir Brahim Belhaouari (9427347)Khaled M. Saoud (16876017)Amine Bermak (1895947)EngineeringElectronics, sensors and digital hardwareInformation and computing sciencesMachine learningSensor arraysSensorsTemperature sensorsMathematical modelsCostsAtmospheric modelingTungstenElectronic noseGas estimationMathematical modelingNeural networks (NNs)Virtual sensing<p dir="ltr">Hydrogen sulfide (H<sub>2</sub>S) presents many hazardous traits such as corrosive, explosive, toxic, and flammable. It is slightly denser than air, and a mixture of H<sub>2</sub>S and air can be volatile. Therefore, a reliable and robust measurement system is required to effectively detect and quantify H<sub>2</sub>S in many applications, such as oil and gas industries. There are several methods available in the literature to quantify H<sub>2</sub>S in fuel gases; however, only a few are available in case of air samples. Furthermore, array-based sensors are more reliable in the detection of volatile organic compounds (VOCs); however, sensor arrays are more expensive and challenging to produce. To overcome the limitations of producing physical sensor arrays, this article proposes a concept of virtual sensing that enables to augment a single sensing platform into a virtual array, thus, increasing the detection accuracy at no extra cost of producing a large physical sensors array. The merits of the proposed system are as follows: 1) a virtual sensing concept is combined with a physical sensing platform to enhance the proposed model’s estimation power in quantifying H<sub>2</sub>S in air samples; 2) a new feature extraction method based on fractional derivatives is proposed to further enhance the model’s learning capabilities; 3) an array of four gas sensors is fabricated in the in-house foundry to record and analyze the signature of H<sub>2</sub>S at various concentration levels; 4) a shallow neural network (NN) model is trained and tested on the recorded data, and based on the NN’s input–output relation, a mathematical model is presented for the quantification of H<sub>2</sub>S; and 5) the proposed model is a highly sensitive and reliable H<sub>2</sub>S gas sensing scheme with the ability to detect the gas instantaneously. The proposed gas quantification model has the advantages of being low cost, easy to implement, and fast operation compared with the analytical solutions. Furthermore, it is extensively tested and validated using real gas data.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Transactions on Instrumentation and Measurement<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/tim.2021.3120150" target="_blank">https://dx.doi.org/10.1109/tim.2021.3120150</a></p><p dir="ltr">Additional institutions affiliated with: Liberal Arts and Science Program - VCUarts Qatar</p>2021-10-26T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/tim.2021.3120150https://figshare.com/articles/journal_contribution/Hydrogen_Sulfide_H_sub_2_sub_S_Sensor_A_Concept_of_Physical_Versus_Virtual_Sensing/24025251CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240252512021-10-26T00:00:00Z |
| spellingShingle | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing Ahmed Alsarraj (16876014) Engineering Electronics, sensors and digital hardware Information and computing sciences Machine learning Sensor arrays Sensors Temperature sensors Mathematical models Costs Atmospheric modeling Tungsten Electronic nose Gas estimation Mathematical modeling Neural networks (NNs) Virtual sensing |
| status_str | publishedVersion |
| title | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| title_full | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| title_fullStr | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| title_full_unstemmed | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| title_short | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| title_sort | Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing |
| topic | Engineering Electronics, sensors and digital hardware Information and computing sciences Machine learning Sensor arrays Sensors Temperature sensors Mathematical models Costs Atmospheric modeling Tungsten Electronic nose Gas estimation Mathematical modeling Neural networks (NNs) Virtual sensing |