Identification of defected sensors in an array of amperometric gas sensors

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marta Dmitrzak ◽  
Pawel Kalinowski ◽  
Piotr Jasinski ◽  
Grzegorz Jasinski
Keyword(s):  
Gas Sensors ◽  
Sensor Response ◽  
Content Type ◽  
Power Failure ◽  
A Value ◽  
Detection And Identification ◽  
Baseline Shift ◽  
The Matrix ◽  
Pca Method ◽  
Damage Simulation

Purpose Amperometric gas sensors are commonly used in air quality monitoring in long-term measurements. Baseline shift of sensor responses and power failure may occur over time, which is an obstacle for reliable operation of the entire system. The purpose of this study is to check the possibility of using PCA method to detect defected samples, identify faulty sensor and correct the responses of the sensor identified as faulty. Design/methodology/approach In this work, the authors present the results obtained with six amperometric sensors. An array of sensors was exposed to sulfur dioxide at the following concentrations: 0 ppm (synthetic air), 50 ppb, 100 ppb, 250 ppb, 500 ppb and 1000 ppb. The damage simulation consisted in adding to the sensor response a value of 0.05 and 0.1 µA and replacing the responses of one of sensors with a constant value of 0 and 0.15 µA. Sensor validity index was used to identify a damaged sensor in the matrix, and its responses were corrected via iteration method. Findings The results show that the methods used in this work can be potentially applied to detect faulty sensor responses. In the case of simulation of damage by baseline shift, it was possible to achieve 100% accuracy in damage detection and identification of the damaged sensor. The method was not very successful in simulating faults by replacing the sensor response with a value of 0 µA, due to the fact that the sensors mostly gave responses close to 0 µA, as long as they did not detect SO2 concentrations below 250 ppb and the failure was treated as a correct response. Originality/value This work was inspired by methods of simulating the most common failures that occurs in amperometric gas sensors. For this purpose, simulations of the baseline shift and faults related to a power failure or a decrease in sensitivity were performed.

Study on high-temperature wear and mechanism of Al-Si/graphite composites prepared by the die-casting process

2020 ◽  
Vol 72 (10) ◽  
pp. 1153-1158 ◽  
Author(s):  
Yafei Deng ◽  
Xiaotao Pan ◽  
Guoxun Zeng ◽  
Jie Liu ◽  
Sinong Xiao ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Wear Rate ◽  
Peer Review ◽  
Die Casting ◽  
Casting Machine ◽  
Injection Pressure ◽  
Casting Process ◽  
Matrix Alloy ◽  
Content Type ◽  
The Matrix

Purpose This paper aims to improve the tribological properties of aluminum alloys and reduce their wear rate. Design/methodology/approach Carbon is placed in the model at room temperature, pour 680°C of molten aluminum into the pressure chamber, and then pressed it into the mold containing carbon felt through a die casting machine, and waited for it to cool, which used an injection pressure of 52.8 MPa and held the same pressure for 15 s. Findings The result indicated that the mechanical properties of matrix and composite are similar, and the compressive strength of the composite is only 95% of the matrix alloy. However, the composite showed a low friction coefficient, the friction coefficient of Gr/Al composite is only 0.15, which just is two-third than that of the matrix alloy. Similarly, the wear rate of the composite is less than 4% of the matrix. In addition, the composite can avoid severe wear before 200°C, but the matrix alloy only 100°C. Originality/value This material has excellent friction properties and is able to maintain this excellent performance at high temperatures. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0454/

Graduates giving back – a mentoring program for MBA students

2015 ◽  
Vol 4 (3) ◽  
pp. 200-212 ◽  
Author(s):  
Ann Darwin
Keyword(s):  
Higher Education ◽  
South Australia ◽  
Value Added ◽  
Master Of Business Administration ◽  
Mentoring Program ◽  
Education Students ◽  
Content Type ◽  
Mba Students ◽  
A Value ◽  
The University

Purpose – The purpose of this paper is to discuss the challenges and obstacles encountered in the implementation of a mentoring program for Master of Business Administration (MBA) students at the University of South Australia (UniSA) Business School. The paper starts with an exploration into the need for a mentoring program, the trial and subsequent four years of implementation. The paper also explores the network model of mentoring and the reasons why this, rather than a more traditional model, was chosen for the program’s implementation. Design/methodology/approach – This exploratory case study uses data from over 600 students and their alumni mentors over a five-year period to evaluate and improve the program as well as cultivating a critical community of adult learners. Findings – Feedback from students indicates that the mentoring program is regarded by most as a value-added feature of their early learning as it offers support, if and when it is required, from those who have been there before. Research limitations/implications – Results are limited to one institution. However, as research into mentoring for higher education students is thin on the ground, this study contributes to our understanding of the positive impacts of mentoring on student success. Practical implications – This paper emphasizes the importance of business leaders giving back to their alma mater through mentoring current MBA students. It shows how mentoring can support learning and management development. Originality/value – This is an original study which explores ways to increase the learning of higher education students for positive social outcomes.

Fatigue behavior of precipitation strengthened Cu–Ni–Si alloy modified by Cr and Zr addition

2020 ◽  
Vol 11 (6) ◽  
pp. 861-873
Author(s):  
Ş. Hakan Atapek ◽  
Spiros Pantelakis ◽  
Şeyda Polat ◽  
Apostolos Chamos ◽  
Gülşah Aktaş Çelik
Keyword(s):  
Design Methodology ◽  
Fatigue Behavior ◽  
Fatigue Tests ◽  
Lower Stress ◽  
Content Type ◽  
Hardened Alloy ◽  
Zr Addition ◽  
Nucleation Sites ◽  
The Matrix ◽  
Lower Stress Level

Purpose The purpose of this paper is to investigate the fatigue behavior of precipitation-strengthened Cu‒2.55Ni‒0.55Si alloy, modified by the addition of 0.25 Cr and 0.25 Zr (wt%), using mechanical and fractographical studies to reveal the effect of microstructural features on the fracture. Design/methodology/approach For strengthening, cast and hot forged alloy was subjected to solution annealing at 900°C for 60 min, followed by quenching in water and then aging at 490°C for 180 min. Precipitation-hardened alloy was exposed to fatigue tests at R=−1 and different stress levels. All fracture surfaces were examined within the frame of fractographical analysis. Findings Fine Ni-rich silicides responsible for the precipitation strengthening were observed within the matrix and their interactions with the dislocations at lower stress level resulted in localized shearing and fine striations. Although, by the addition of Cr and Zr, the matrix consisted of hard Ni, Zr-rich and Cr-rich silicides, these precipitates adversely affected the fatigue behavior acting as nucleation sites for cracks. Originality/value These findings contribute to the present knowledge by revealing the effect of microstructural features on the mechanical behavior of precipitation-hardened Cu‒Ni‒Si alloy modified by Cr and Zr addition.

scholarly journals Strategic account management as a value co-creation selling model in the pharmaceutical industry

2017 ◽  
Vol 32 (2) ◽  
pp. 310-325 ◽  
Author(s):  
Francois Pilon ◽  
Elias Hadjielias
Keyword(s):  
Pharmaceutical Industry ◽  
Pharmaceutical Company ◽  
Value Added ◽  
Pharmaceutical Companies ◽  
Design Data ◽  
Content Type ◽  
Qualitative Research Design ◽  
Account Management ◽  
A Value ◽  
Key Accounts

Purpose This study aims to explore the dynamics enabling strategic account management (SAM) to function as a value co-creation selling model in the pharmaceutical industry. Design/methodology/approach Using an inductive qualitative research design, data are collected within 11 industry customers in Canada. This work focuses on hospitals as strategic accounts of pharmaceutical companies, exploring SAM value co-creation in the “hospital-pharmaceutical company” relationship. Findings The findings suggest the presence of two key dimensions that can enable a value co-creation SAM model in the hospital-pharmaceutical relationship: “customer-tailored value-added initiatives” and “relationship enhancers”. Customer-tailored value-added initiatives explain the activities that are central to the hospital-pharmaceutical company relationship and can lead to the provision of value added that is unique to the hospital. Relationship enhancers explain the activities that can help strengthen hospital-pharmaceutical company relations in the pursuit of enhanced value-added interactions between the two parties. The research demonstrates a cyclical relationship between “customer-tailored value-added initiatives” and “relationship enhancers”, leading to value co-creation through a SAM model. Practical implications The study informs pharmaceutical industry practitioners on how to improve their value proposition through new, more sustainable selling practices. It offers information on implementing a value co-creation SAM model, which can enable pharmaceutical companies to sustain long-lasting value-added relationships with key accounts such as hospitals. Originality/value The study contributes to the field of SAM by conceptualizing SAM as a value co-creation system. It introduces new knowledge in pharmaceutical marketing by offering empirical insight on the applicability and use of SAM in the hospital-pharmaceutical company dyad.

scholarly journals Value-driven engineering of E-maintenance platforms

2014 ◽  
Vol 25 (4) ◽  
pp. 568-598 ◽  
Author(s):  
Marco Macchi ◽  
Adolfo Crespo Márquez ◽  
Maria Holgado ◽  
Luca Fumagalli ◽  
Luis Barberá Martínez
Keyword(s):  
Information And Communication Technologies ◽  
Cost Benefit ◽  
Communication Technologies ◽  
Industrial Applications ◽  
Maintenance Management ◽  
Content Type ◽  
Positive Effects ◽  
A Value ◽  
New Information ◽  
Information And Communication

Purpose – The purpose of this paper is to propose a methodology for the engineering of E-maintenance platforms that is based on a value-driven approach. Design/methodology/approach – The methodology assumes that a value-driven engineering approach would help foster technological innovation for maintenance management. Indeed, value-driven engineering could be easily adopted at the business level, with subsequent positive effects on the industrial applications of new information and communication technologies solutions. Findings – The methodology combines a value-driven approach with the engineering in the maintenance scope. The methodology is tested in a manufacturing case to prove its potential to support the engineering of E-maintenance solutions. In particular, the case study concerns the investment in E-maintenance solutions developed in the framework of a Supervisory Control and Data Acquisition system originally implemented for production purposes. Originality/value – Based on literature research, the paper presents a methodology that is implemented considering three different approaches (business theories, value-driven engineering and maintenance management). The combination of these approaches is novel and overcomes the traditional view of maintenance as an issue evaluated from a cost-benefit perspective.

scholarly journals Short-Time Fourier Transform and Decision Tree-Based Pattern Recognition for Gas Identification Using Temperature Modulated Microhotplate Gas Sensors

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Aixiang He ◽  
Jun Yu ◽  
Guangfen Wei ◽  
Yi Chen ◽  
Hao Wu ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Fourier Transform ◽  
Decision Tree ◽  
Gas Sensors ◽  
Operating Temperature ◽  
Ambient Air ◽  
Sensor Response ◽  
Short Time Fourier Transform ◽  
Short Time ◽  
Different Gases

Because the sensor response is dependent on its operating temperature, modulated temperature operation is usually applied in gas sensors for the identification of different gases. In this paper, the modulated operating temperature of microhotplate gas sensors combined with a feature extraction method based on Short-Time Fourier Transform (STFT) is introduced. Because the gas concentration in the ambient air usually has high fluctuation, STFT is applied to extract transient features from time-frequency domain, and the relationship between the STFT spectrum and sensor response is further explored. Because of the low thermal time constant, the sufficient discriminatory information of different gases is preserved in the envelope of the response curve. Feature information tends to be contained in the lower frequencies, but not at higher frequencies. Therefore, features are extracted from the STFT amplitude values at the frequencies ranging from 0 Hz to the fundamental frequency to accomplish the identification task. These lower frequency features are extracted and further processed by decision tree-based pattern recognition. The proposed method shows high classification capability by the analysis of different concentration of carbon monoxide, methane, and ethanol.

Computational predictions for predicting the performance of steel 1 panel shear wall under explosive loads

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aydin Shishegaran ◽  
Behnam Karami ◽  
Elham Safari Danalou ◽  
Hesam Varaee ◽  
Timon Rabczuk
Keyword(s):  
Steel Plate ◽  
Plate Thickness ◽  
Ensemble Model ◽  
Maximum Deflection ◽  
Explosive Load ◽  
Statistical Parameters ◽  
Content Type ◽  
A Value ◽  
Error Terms ◽  
Better Than

Purpose The resistance of steel plate shear walls (SPSW) under explosive loads is evaluated using nonlinear FE analysis and surrogate methods. This study uses the conventional weapons effect program (CONWEP) model for the explosive load and the Johnson-Cook model for the steel plate. Based on the Taguchi method, 25 samples out of 100 samples are selected for a parametric study where we predict the damaged zones and the maximum deflection of SPSWs under explosive loads. Then, this study uses a multiple linear regression (MLR), multiple Ln equation regression (MLnER), gene expression programming (GEP), adaptive network-based fuzzy inference (ANFIS) and an ensemble model to predict the maximum detection of SPSWs. Several statistical parameters and error terms are used to evaluate the accuracy of the different surrogate models. The results show that the cross-section in the y-direction and the plate thickness have the most significant effects on the maximum deflection of SPSWs. The results also show that the maximum deflection is related to the scaled distance, i.e. for a value of 0.383. The ensemble model performs better than all other models for predicting the maximum deflection of SPSWs under explosive loads. Design/methodology/approach The SPSW under explosive loads is evaluated using nonlinear FE analysis and surrogate methods. This study uses the CONWEP model for the explosive load and the Johnson-Cook model for the steel plate. Based on the Taguchi method, 25 samples out of 100 samples are selected for a parametric study where we predict the damaged zones and the maximum deflection of SPSWs under explosive loads. Then, this study uses a MLR, MLnER, GEP, ANFIS and an ensemble model to predict the maximum detection of SPSWs. Several statistical parameters and error terms are used to evaluate the accuracy of the different surrogate models. The results show that the cross-section in the y-direction and the plate thickness have the most significant effects on the maximum deflection of SPSWs. The results also show that the maximum deflection is related to the scaled distance, i.e. for a value of 0.383. The ensemble model performs better than all other models for predicting the maximum deflection of SPSWs under explosive loads. Findings The resistance of SPSW under explosive loads is evaluated using nonlinear FE analysis and surrogate methods. This study uses the CONWEP model for the explosive load and the Johnson-Cook model for the steel plate. Based on the Taguchi method, 25 samples out of 100 samples are selected for a parametric study where we predict the damaged zones and the maximum deflection of SPSWs under explosive loads. Then, this study uses a MLR, MLnER, GEP, ANFIS and an ensemble model to predict the maximum detection of SPSWs. Several statistical parameters and error terms are used to evaluate the accuracy of the different surrogate models. The results show that the cross-section in the y-direction and the plate thickness have the most significant effects on the maximum deflection of SPSWs. The results also show that the maximum deflection is related to the scaled distance, i.e. for a value of 0.383. The ensemble model performs better than all other models for predicting the maximum deflection of SPSWs under explosive loads. Originality/value The resistance of SPSW under explosive loads is evaluated using nonlinear FE analysis and surrogate methods. This study uses the CONWEP model for the explosive load and the Johnson-Cook model for the steel plate. Based on the Taguchi method, 25 samples out of 100 samples are selected for a parametric study where we predict the damaged zones and the maximum deflection of SPSWs under explosive loads. Then, this study uses a MLR, MLnER, GEP, ANFIS and an ensemble model to predict the maximum detection of SPSWs. Several statistical parameters and error terms are used to evaluate the accuracy of the different surrogate models. The results show that the cross-section in the y-direction and the plate thickness have the most significant effects on the maximum deflection of SPSWs. The results also show that the maximum deflection is related to the scaled distance, i.e. for a value of 0.383. The ensemble model performs better than all other models for predicting the maximum deflection of SPSWs under explosive loads.

A new combined transient extraction method coupled with WO3 gas sensors for polluting gases classification

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rabeb Faleh ◽  
Sami Gomri ◽  
Khalifa Aguir ◽  
Abdennaceur Kachouri
Keyword(s):  
Feature Extraction ◽  
Gas Sensors ◽  
Classification Accuracy ◽  
Extraction Method ◽  
Support Vector ◽  
Classification Rate ◽  
Content Type ◽  
Feature Extraction Method ◽  
Combined Features ◽  
Discrimination Capacity

Purpose The purpose of this paper is to deal with the classification improvement of pollutant using WO3 gases sensors. To evaluate the discrimination capacity, some experiments were achieved using three gases: ozone, ethanol, acetone and a mixture of ozone and ethanol via four WO3 sensors. Design/methodology/approach To improve the classification accuracy and enhance selectivity, some combined features that were configured through the principal component analysis were used. First, evaluate the discrimination capacity; some experiments were performed using three gases: ozone, ethanol, acetone and a mixture of ozone and ethanol, via four WO3 sensors. To this end, three features that are derivate, integral and the time corresponding to the peak derivate have been extracted from each transient sensor response according to four WO3 gas sensors used. Then these extracted parameters were used in a combined array. Findings The results show that the proposed feature extraction method could extract robust information. The Extreme Learning Machine (ELM) was used to identify the studied gases. In addition, ELM was compared with the Support Vector Machine (SVM). The experimental results prove the superiority of the combined features method in our E-nose application, as this method achieves the highest classification rate of 90% using the ELM and 93.03% using the SVM based on Radial Basis Kernel Function SVM-RBF. Originality/value Combined features have been configured from transient response to improve the classification accuracy. The achieved results show that the proposed feature extraction method could extract robust information. The ELM and SVM were used to identify the studied gases.

A study on tribological behaviour and analysis of ZnO reinforced AA6061 matrix composites fabricated by stir casting route

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sakthi Sadhasivam RM ◽  
Ramanathan K. ◽  
Bhuvaneswari B.V. ◽  
Raja R.
Keyword(s):  
Wear Rate ◽  
Sliding Wear ◽  
Stir Casting ◽  
Industrial Applications ◽  
Wear Behaviour ◽  
Matrix Composites ◽  
Tribological Behaviour ◽  
Content Type ◽  
Zno Particles ◽  
The Matrix

Purpose The most promising replacements for the industrial applications are particle reinforced metal matrix composites because of their good and combined mechanical properties. Currently, the need of matrix materials for industrial applications is widely satisfied by aluminium alloys. The purpose of this paper is to evaluate the tribological behaviour of the zinc oxide (ZnO) particles reinforced AA6061 composites prepared by stir casting route. Design/methodology/approach In this study, AA6061 aluminium alloy matrix reinforced with varying weight percentages (3%, 4.5% and 6%) of ZnO particles, including monolithic AA6061 alloy samples, is cast by the most economical fabrication method, called stir casting. The prepared sample was subjected to X-ray photoelectron spectroscopy (XPS) analysis, experimental density measurement by Archimedian principle and theoretical density by rule of mixture and hardness test to investigate mechanical property. The dry sliding wear behaviour of the composites was investigated using pin-on-disc tribometer with various applied loads of 15 and 20 N, with constant sliding velocity and distance. The wear rate, coefficient of friction (COF) and worn surfaces of the composite specimens and their effects were also investigated in this work. Findings XPS results confirm the homogeneous distribution of ZnO microparticles in the Al matrix. The Vickers hardness result reveals that higher ZnO reinforced (6%) sample have 34.4% higher values of HV than the monolithic aluminium sample. The sliding wear tests similarly show that increasing the weight percentage of ZnO particles leads to a reduced wear rate and COF of 30.01% and 26.32% lower than unreinforced alloy for 15 N and 36.35% and 25% for 20 N applied load. From the worn surface morphological studies, it was evidently noticed that ZnO particles dispersed throughout the matrix and it had strong bonding between the reinforcement and the matrix, which significantly reduced the plastic deformation of the surfaces. Originality/value The uniqueness of this work is to use the reinforcement of ZnO particles with AA6061 matrix and preparing by stir casting route and to study and analyse the physical, hardness and tribological behaviour of the composite materials.

Enhancing the tensile strength of SiC reinforced aluminium- based functionally graded structure through the mixture design approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Poornesh ◽  
Shreeranga Bhat ◽  
E.V. Gijo ◽  
Pavana Kumara Bellairu
Keyword(s):  
Tensile Strength ◽  
Composite Structure ◽  
Centrifugal Casting ◽  
Matrix Material ◽  
Stir Casting ◽  
Mixture Design ◽  
Functionally Graded ◽  
Content Type ◽  
Functionally Graded Composite ◽  
The Matrix

PurposeThis article aims to study the tensile properties of a functionally graded composite structure with Al–18wt%Si alloy as the matrix material and silicon carbide (SiC) particles as the reinforcing element. More specifically, the study's primary objective is to optimize the composition of the material elements using a robust statistical approach.Design/methodology/approachIn this research, the composite material is fabricated using a combination of stir casting and the centrifugal casting technique. Moreover, the test specimen required to study the tensile strength are prepared according to the ASTM (American Society for Testing and Materials) standards. Eventually, optimal composition to maximize the tensile property of the material is determined using the mixture design approach.FindingsThe investigation results imply that the addition of the SiC plays a crucial role in increasing the tensile strength of the composite. The optical microstructural images of the composite show the adequate distribution of the reinforcing particles with the matrix. The proposed regression model shows better predictability of tensile strength. In addition, the methodology aids in optimizing the mixture component values to maximize the tensile strength of the produced functionally graded composite structure.Originality/valueLittle work has been reported so far where a hypereutectic Al–Si alloy is considered the matrix material to produce the composite structure. The article attempts to make a composite structure by using a combination of stir casting and centrifugal casting. Furthermore, it employs the mixture design to optimize the composition and predict the model of the study, which is one of a kind in the field of material science.

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