Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304508
Inho Kim, K. Seo
We report a metal oxide chemiresistive gas sensor with ultra-thin filmed Au decorated SnO2 as a sensing material on a micro-machined hotplate that combines a micro-heater and interdigitated electrodes. We designed and fabricated the hot plate by micro-electro-mechanical system (MEMS) processes and Au decorated SnO2 thin filmed layer by ion-beam sputtering methods, and investigated gas sensing performance for carbon monoxide and methane gas detection. The gas sensor with 20 nm thickness of SnO2 thin film was operated 100 °C for carbon monoxide and 250 °C for methane detection. The power consumptions were 20 mW and 80 mW for carbon monoxide and methane operating temperature, respectively. Microstructures of material were systemically characterized by FESEM, analytic STEM and AFM. We also discussed the effect of microstructure to gas sensing properties.
{"title":"Ultra-thin filmed SnO2 gas sensor with a low-power micromachined hotplate for selective dual gas detection of carbon monoxide and methane","authors":"Inho Kim, K. Seo","doi":"10.1109/ICSENST.2017.8304508","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304508","url":null,"abstract":"We report a metal oxide chemiresistive gas sensor with ultra-thin filmed Au decorated SnO2 as a sensing material on a micro-machined hotplate that combines a micro-heater and interdigitated electrodes. We designed and fabricated the hot plate by micro-electro-mechanical system (MEMS) processes and Au decorated SnO2 thin filmed layer by ion-beam sputtering methods, and investigated gas sensing performance for carbon monoxide and methane gas detection. The gas sensor with 20 nm thickness of SnO2 thin film was operated 100 °C for carbon monoxide and 250 °C for methane detection. The power consumptions were 20 mW and 80 mW for carbon monoxide and methane operating temperature, respectively. Microstructures of material were systemically characterized by FESEM, analytic STEM and AFM. We also discussed the effect of microstructure to gas sensing properties.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125655050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304431
Niall O' Mahony, Trevor Murphy, Krishna Panduru, D. Riordan, Joseph Walsh
Near Infrared Spectroscopy (NIRS) is a very powerful utility in a Process Analytical Technology (PAT) system because it can be used to monitor a multitude of process parameters non-invasively, non-destructively in real time and in hazardous environments. A catch to the versatility of NIRS is the requirement for Multi-Variate Data Analysis (MVDA) to calibrate the measurement of the parameter of interest. This paper presents a NIRS based real time continuous monitoring of powder blend composition which has widespread applications such as the pharmaceutical industry. The proposed system design enables reduction of optical path length so that the sensors can be successfully installed into powder conveyance systems. Sensor signal processing techniques were developed in this work to improve accuracy while minimizing pre-processing steps. The paper presents the implementation of several parameter estimation methodologies applied to sensor data collected using MATLAB® software for a model powder blending process. Several techniques were examined for the development of chemometric models of the multi-sensor data, including Principal Component Analysis (PCA), Partial Least Squares Regression (PLSR), Support Vector Machines (SVM) and Artificial Neural Networks (ANN). The performances of each of the models were compared in terms of accuracy (MSE) in predicting blend composition. The results obtained show that machine learning-based approaches produce process models of similar accuracy and robustness compared to models developed by PLSR while requiring minimal pre-processing and also being more adaptable to new data.
{"title":"Real-time monitoring of powder blend composition using near infrared spectroscopy","authors":"Niall O' Mahony, Trevor Murphy, Krishna Panduru, D. Riordan, Joseph Walsh","doi":"10.1109/ICSENST.2017.8304431","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304431","url":null,"abstract":"Near Infrared Spectroscopy (NIRS) is a very powerful utility in a Process Analytical Technology (PAT) system because it can be used to monitor a multitude of process parameters non-invasively, non-destructively in real time and in hazardous environments. A catch to the versatility of NIRS is the requirement for Multi-Variate Data Analysis (MVDA) to calibrate the measurement of the parameter of interest. This paper presents a NIRS based real time continuous monitoring of powder blend composition which has widespread applications such as the pharmaceutical industry. The proposed system design enables reduction of optical path length so that the sensors can be successfully installed into powder conveyance systems. Sensor signal processing techniques were developed in this work to improve accuracy while minimizing pre-processing steps. The paper presents the implementation of several parameter estimation methodologies applied to sensor data collected using MATLAB® software for a model powder blending process. Several techniques were examined for the development of chemometric models of the multi-sensor data, including Principal Component Analysis (PCA), Partial Least Squares Regression (PLSR), Support Vector Machines (SVM) and Artificial Neural Networks (ANN). The performances of each of the models were compared in terms of accuracy (MSE) in predicting blend composition. The results obtained show that machine learning-based approaches produce process models of similar accuracy and robustness compared to models developed by PLSR while requiring minimal pre-processing and also being more adaptable to new data.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115814921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304420
Muhammad Farooq, E. Sazonov
Motion artifacts and speech have been found to degrade the accuracy of wearable device used for detection and recognition of food intake. Thus, there is a need to investigate and develop systems which are impervious to these artifacts. For these systems to be practical in daily living, it is necessary to evaluate their ability to monitor food intake in real-time. This study presents results of real-time testing of a wearable device for real-time classification of multiclass activities. The device consists of a sensor for chewing detection (piezoelectric film sensor) and an accelerometer for physical activity monitoring. The device is in the form of eyeglasses. The strain sensor is attached to the temporalis muscle for chewing detection. Ten participants tested the system while performing activities including eating at rest, talking, walking and eating while walking. For 5-second epochs, ten features were extracted from both sensor signals. A communication protocol was implemented where sensor data were uploaded to a remote server for real-time data processing. Data processing was performed in two steps. In the first step, a multiclass decision tree model was trained offline with data from seven participants to differentiate among eating/chewing and non-eating and two levels of physical activity (sedentary and physically active). In the second step, the trained model was used on remaining three participants to predict the activity label in real-time. Offline classification and real-time online classification achieved average F1-scores of 93.15% and 94.65% respectively. These results indicate that the device can accurately differentiate between epochs of eating and non-eating as well as epochs of two different physical activity levels; in real-time.
{"title":"Real time monitoring and recognition of eating and physical activity with a wearable device connected to the eyeglass","authors":"Muhammad Farooq, E. Sazonov","doi":"10.1109/ICSENST.2017.8304420","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304420","url":null,"abstract":"Motion artifacts and speech have been found to degrade the accuracy of wearable device used for detection and recognition of food intake. Thus, there is a need to investigate and develop systems which are impervious to these artifacts. For these systems to be practical in daily living, it is necessary to evaluate their ability to monitor food intake in real-time. This study presents results of real-time testing of a wearable device for real-time classification of multiclass activities. The device consists of a sensor for chewing detection (piezoelectric film sensor) and an accelerometer for physical activity monitoring. The device is in the form of eyeglasses. The strain sensor is attached to the temporalis muscle for chewing detection. Ten participants tested the system while performing activities including eating at rest, talking, walking and eating while walking. For 5-second epochs, ten features were extracted from both sensor signals. A communication protocol was implemented where sensor data were uploaded to a remote server for real-time data processing. Data processing was performed in two steps. In the first step, a multiclass decision tree model was trained offline with data from seven participants to differentiate among eating/chewing and non-eating and two levels of physical activity (sedentary and physically active). In the second step, the trained model was used on remaining three participants to predict the activity label in real-time. Offline classification and real-time online classification achieved average F1-scores of 93.15% and 94.65% respectively. These results indicate that the device can accurately differentiate between epochs of eating and non-eating as well as epochs of two different physical activity levels; in real-time.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133243261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304512
Diogo Ferreira, Raúl Oliveira, O. Postolache
This article presents a serious game framework developed using Unity 3D game engine and Kinect V2 sensor as a natural user interface. The developed serious games are used for objective evaluation of physical rehabilitation considering the Kinect V2 sensors for 3D motion detection of different body joints training and provide different types of data, such as angles velocities, for physiotherapists and patients during the rehabilitation process. The framework provide data storage capability in a remote database thus patient's biometric data, patients' medical record, obtained scores during serious game based training and values of metrics such as the distance between feet during game, left right feet usage frequency and execution time for imposed movement associated with game mechanics. A general description of the applied technologies on serious game for lower limb rehabilitation developments as so as the experimental results obtained for a set of volunteers are included in the paper.
{"title":"Physical rehabilitation based on kinect serious games","authors":"Diogo Ferreira, Raúl Oliveira, O. Postolache","doi":"10.1109/ICSENST.2017.8304512","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304512","url":null,"abstract":"This article presents a serious game framework developed using Unity 3D game engine and Kinect V2 sensor as a natural user interface. The developed serious games are used for objective evaluation of physical rehabilitation considering the Kinect V2 sensors for 3D motion detection of different body joints training and provide different types of data, such as angles velocities, for physiotherapists and patients during the rehabilitation process. The framework provide data storage capability in a remote database thus patient's biometric data, patients' medical record, obtained scores during serious game based training and values of metrics such as the distance between feet during game, left right feet usage frequency and execution time for imposed movement associated with game mechanics. A general description of the applied technologies on serious game for lower limb rehabilitation developments as so as the experimental results obtained for a set of volunteers are included in the paper.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130529800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304462
A. Nag, S. Mukhopadhyay, J. Kosel
This paper presents the response of two different types of novel printed sensors towards the change in temperature and humidity. The electrodes of all the sensors were based on carbon materials. Followed by the design and fabrication of the sensors, the responses of the sensors were analyzed for different temperature and humidity conditions in an incubator. These results provide a podium to enhance the alternation of the fabrication procedure of carbon-based printed sensors.
{"title":"Influence of temperature and humidity on carbon based printed flexible sensors","authors":"A. Nag, S. Mukhopadhyay, J. Kosel","doi":"10.1109/ICSENST.2017.8304462","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304462","url":null,"abstract":"This paper presents the response of two different types of novel printed sensors towards the change in temperature and humidity. The electrodes of all the sensors were based on carbon materials. Followed by the design and fabrication of the sensors, the responses of the sensors were analyzed for different temperature and humidity conditions in an incubator. These results provide a podium to enhance the alternation of the fabrication procedure of carbon-based printed sensors.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131704849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304469
S. Dey, N. Karmakar
This paper exemplifies the design and analysis of an inexpensive, compact high data capacity chipless RFID tag on flexible paper substrate. The size of the overall tag with integrated antennas is similar to that of a credit card. The designed tag uses polarization diversity to provide a bit capacity of up to 30 bits in the short range UWB band of 22–26.5 GHz. A systematic progression on to the incorporation of increased number of bit capacity is depicted hereby. Along with frequency variation, this paper also proposes the scheme for bit detection using phase difference determination in order to increase robustness. An interrogation process of the proposed tag to extract the encoded information is demonstrated here and the resulting analysis establishes the reliability of the designed tag.
{"title":"Towards an inexpensive paper based flexible chipless RFID tag with increased data capacity","authors":"S. Dey, N. Karmakar","doi":"10.1109/ICSENST.2017.8304469","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304469","url":null,"abstract":"This paper exemplifies the design and analysis of an inexpensive, compact high data capacity chipless RFID tag on flexible paper substrate. The size of the overall tag with integrated antennas is similar to that of a credit card. The designed tag uses polarization diversity to provide a bit capacity of up to 30 bits in the short range UWB band of 22–26.5 GHz. A systematic progression on to the incorporation of increased number of bit capacity is depicted hereby. Along with frequency variation, this paper also proposes the scheme for bit detection using phase difference determination in order to increase robustness. An interrogation process of the proposed tag to extract the encoded information is demonstrated here and the resulting analysis establishes the reliability of the designed tag.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133881360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304518
Jeong-Kyun Kim, K. Lee, S. Hong
This study presents a biometrie identification based on gait (with shoe wearable sensors). Biometrie identification is an excellent method to often alternate inconvenient interaction such as PIN and patterns in smart device. To help elderly person who cannot control smart devices by themselves, it is required to assist automatic personalization by identifying users sharing a device. In this study, we proposed an algorithm combined the discrete cosine transform for detecting frequency feature and random forest which classifies subjects. We performed an experiment for 8 subjects by walking with the smart shoes. Finally, the result demonstrates a user recognition accuracy of 97.9 % and an equal error rate of 2.4%.
{"title":"Random forest based-biometric identification using smart shoes","authors":"Jeong-Kyun Kim, K. Lee, S. Hong","doi":"10.1109/ICSENST.2017.8304518","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304518","url":null,"abstract":"This study presents a biometrie identification based on gait (with shoe wearable sensors). Biometrie identification is an excellent method to often alternate inconvenient interaction such as PIN and patterns in smart device. To help elderly person who cannot control smart devices by themselves, it is required to assist automatic personalization by identifying users sharing a device. In this study, we proposed an algorithm combined the discrete cosine transform for detecting frequency feature and random forest which classifies subjects. We performed an experiment for 8 subjects by walking with the smart shoes. Finally, the result demonstrates a user recognition accuracy of 97.9 % and an equal error rate of 2.4%.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"75 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131878048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304515
S. Sabrin, S. Kharkovsky, Robert Salama
This paper presents a two-antenna setup based on dielectric resonator antenna (DRA) and used as a sensing system for characterization of construction materials such as concrete. In this two-antenna setup, a DRA that acts as a receiving sensor-integrated antenna is embedded inside concrete and another external DRA (placed in free space) transmits wireless power to the embedded antenna. Both antennas are fed by X-band (8.2–12.4 GHz) open ended waveguide antennas (OEWAs). Transmission coefficients, reflection coefficients and electric-field distributions of these setups are investigated in the frequency range from 8 to 15 GHz. These investigations are performed with relatively long and short DRAs, and with OEWAs (without DRAs). In addition, sensitivity of the two-antenna sensing system to changes in values of the dielectric constants and loss tangent of concrete with the three antennas are analyzed. It is shown that the two-antenna sensing system with the long DRA and OEWA are more sensitive to the changes of both the loss tangent and dielectric constant of concrete than with the short DRA. However, the short DRA had a better performance with a magnitude of transmission coefficient that is significantly higher than those of the long DRA and the OEWA.
{"title":"Dielectric resonator antenna integrated sensors for characterization of concrete","authors":"S. Sabrin, S. Kharkovsky, Robert Salama","doi":"10.1109/ICSENST.2017.8304515","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304515","url":null,"abstract":"This paper presents a two-antenna setup based on dielectric resonator antenna (DRA) and used as a sensing system for characterization of construction materials such as concrete. In this two-antenna setup, a DRA that acts as a receiving sensor-integrated antenna is embedded inside concrete and another external DRA (placed in free space) transmits wireless power to the embedded antenna. Both antennas are fed by X-band (8.2–12.4 GHz) open ended waveguide antennas (OEWAs). Transmission coefficients, reflection coefficients and electric-field distributions of these setups are investigated in the frequency range from 8 to 15 GHz. These investigations are performed with relatively long and short DRAs, and with OEWAs (without DRAs). In addition, sensitivity of the two-antenna sensing system to changes in values of the dielectric constants and loss tangent of concrete with the three antennas are analyzed. It is shown that the two-antenna sensing system with the long DRA and OEWA are more sensitive to the changes of both the loss tangent and dielectric constant of concrete than with the short DRA. However, the short DRA had a better performance with a magnitude of transmission coefficient that is significantly higher than those of the long DRA and the OEWA.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133963749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304485
Baji Babu Palagarla, N. Das, M. Razaghi
This paper mainly focuses on nonlinear pulse propagation and four-wave mixing (FWM) characteristics in semiconductor optical amplifiers (SOAs). For simulation, modified nonlinear Schrödinger equation (MNLSE) is used for the modelling of pulse propagation in SOA. In this model, we have included the gain dynamics and all nonlinear effects of the SOAs for simulation. Finite-difference beam propagation method is adopted to solve the MNLSE, obtained nonlinear pulse propagation and FWM characteristics in SOA. The nonlinear pulse propagation characteristics show that the output full width at half maximum (FWHM) is linearly increases with increase of input FWHM. Output pulse energy also increases with the increase of input pulse energy. There are some dips occur at the output spectrum which is due to the gain saturation and self-phase modulation (SPM) effects. The FWM conversion efficiency is good if the detuning is <1 THz Finally, the FWM signal energy highly dependent on the input pump and probe energies. The FWM signal peak power increases exponentially with the increase of SOA length. Our simulation results are suitable for the design of SOAs those are using in high-speed communication systems and sensor network systems.
{"title":"Analysis of nonlinear pulse propagation and wave-mixing characteristics in SOAs","authors":"Baji Babu Palagarla, N. Das, M. Razaghi","doi":"10.1109/ICSENST.2017.8304485","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304485","url":null,"abstract":"This paper mainly focuses on nonlinear pulse propagation and four-wave mixing (FWM) characteristics in semiconductor optical amplifiers (SOAs). For simulation, modified nonlinear Schrödinger equation (MNLSE) is used for the modelling of pulse propagation in SOA. In this model, we have included the gain dynamics and all nonlinear effects of the SOAs for simulation. Finite-difference beam propagation method is adopted to solve the MNLSE, obtained nonlinear pulse propagation and FWM characteristics in SOA. The nonlinear pulse propagation characteristics show that the output full width at half maximum (FWHM) is linearly increases with increase of input FWHM. Output pulse energy also increases with the increase of input pulse energy. There are some dips occur at the output spectrum which is due to the gain saturation and self-phase modulation (SPM) effects. The FWM conversion efficiency is good if the detuning is <1 THz Finally, the FWM signal energy highly dependent on the input pump and probe energies. The FWM signal peak power increases exponentially with the increase of SOA length. Our simulation results are suitable for the design of SOAs those are using in high-speed communication systems and sensor network systems.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131254519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ICSENST.2017.8304459
M. Degner, H. Ewald
A cost effective and compact sensor system is described that provides an online measurement of combustion gases. Based on UV-VIS-absorption spectroscopy the most important hazardous emission gases nitrogen oxide (NO), nitrogen dioxide (NO2) and sulfur dioxide (SO2) are measured individually and quasi simultaneous with high temporal resolution. A demonstrator device was set up that utilizes only one measurement chamber so the detection of all gases takes place in the same measurement volume. The demonstrator shows a wide concentration dynamic range of some 1000 ppm and a resolution of below 1 ppm for all three gases. Such a sensor system can be used for online emission monitoring of combustion engines in transportation area as well as in stationary industry application. Especially because of the selective detection of the critical emission gas components NO and NO2 the system can also be used for a well-directed engine and after treatment system control to optimize the catalyzers reactions to efficiently reduce harmful emissions of combustion engines.
{"title":"Demonstrator for online measurement of combustion gases NO, NO2 and SO2: A compact sensor system for highly resolved detection of hazardous emission gases","authors":"M. Degner, H. Ewald","doi":"10.1109/ICSENST.2017.8304459","DOIUrl":"https://doi.org/10.1109/ICSENST.2017.8304459","url":null,"abstract":"A cost effective and compact sensor system is described that provides an online measurement of combustion gases. Based on UV-VIS-absorption spectroscopy the most important hazardous emission gases nitrogen oxide (NO), nitrogen dioxide (NO2) and sulfur dioxide (SO2) are measured individually and quasi simultaneous with high temporal resolution. A demonstrator device was set up that utilizes only one measurement chamber so the detection of all gases takes place in the same measurement volume. The demonstrator shows a wide concentration dynamic range of some 1000 ppm and a resolution of below 1 ppm for all three gases. Such a sensor system can be used for online emission monitoring of combustion engines in transportation area as well as in stationary industry application. Especially because of the selective detection of the critical emission gas components NO and NO2 the system can also be used for a well-directed engine and after treatment system control to optimize the catalyzers reactions to efficiently reduce harmful emissions of combustion engines.","PeriodicalId":289209,"journal":{"name":"2017 Eleventh International Conference on Sensing Technology (ICST)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114220794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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