S. Narayan^1,*, M. U. Kaisan², Shitu Abubakar², Faisal O. Mahroogi³, Vipul Gupta⁴

Sound & Vibration, Vol.55, No.3, pp. 221-234, 2021, DOI:10.32604/sv.2021.016539 - 15 July 2021

Abstract The health monitoring has been studied to ensure integrity of design of engine structure by detection, quantification, and prediction of damages. Early detection of faults may allow the downtime of maintenance to be rescheduled, thus preventing sudden shutdown of machines. In cylinder pressure developed, vibrations and noise emissions data provide a rich source of information about condition of engines. Monitoring of vibrations and noise emissions are novel non-intrusive methodologies for which positioning of various transducers are important issue. The presented work shows applicability of these diagnosis methodologies adopted in case of diesel engines. The effects More >

Jesus Hamilton Ortiz¹, Javier Ferney Castillo García², Osamah Ibrahim Khalaf³, Fernando Velez Varela^2,*, Pedro Jefferson Barragan Baron², Jhon Hadder Guzmán Atehortúa²

Journal on Internet of Things, Vol.3, No.2, pp. 53-63, 2021, DOI:10.32604/jiot.2021.014736 - 15 July 2021

Abstract This work shows the development of a module that performs measurements of electrical variables in a low voltage power transformer. These variables are sent by means of the IEEE802.11 standard, connecting to a database stored in the cloud; associating with the meter IoT concepts, this to allow a client to perform an analysis, monitoring and management of their electrical network. For the construction of this module, non-invasive current sensors connected to a three-phase meter are used and a communication card is used that allows data to be extracted from the meter and sent to the More >

Jie Li¹, Ziyu Zhou², Yun Chen², Qiusheng Yang^1,*, Carlos Alberto Busso^3,*

Phyton-International Journal of Experimental Botany, Vol.90, No.6, pp. 1633-1644, 2021, DOI:10.32604/phyton.2021.016795 - 28 June 2021

Abstract The spatial-temporal variation of understory light availability has important influences on species diversity and community assembly. However, the distribution characteristics and influencing factors of understory light availability have not been fully elucidated, especially in temperate deciduous, broad-leaved forests. In this study, the understory light availability was monitored monthly (May–October) in a temperate deciduous, broad-leaved forest in Henan Province, China. Differences in the light availability among different months and habitat types were statistically analyzed using Kruskal–Wallis method, respectively. Partial least squares path modeling (PLS-PM) was used to explore the direct and/or indirect effects of stand structure,… More >

Dileep Kumar^1,*, Imtiaz Hussain Kalwar², Tanweer Hussain¹, Bhawani Shankar Chowdhry¹, Sanaullah Mehran Ujjan¹, Tayab Din Memon³

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 393-408, 2021, DOI:10.32604/cmc.2021.014941 - 04 June 2021

Abstract Reliability of rotating machines is highly dependent on the smooth rolling of bearings. Thus, it is very essential for reliable operation of rotating machines to monitor the working condition of bearings using suitable fault diagnosis and condition monitoring approach. In the recent past, Deep Learning (DL) has become applicable in condition monitoring of rotating machines owing to its performance. This paper proposes a novel bearing fault diagnosis method based on the processing and analysis of the vibration images. The proposed method is the UNET model that is a recent development in DL models. The model More >

Yihua Wang¹, Zhenhuan Zhou¹, Hao Xu^1,*, Shuai Li², Zhanjun Wu¹

Structural Durability & Health Monitoring, Vol.15, No.2, pp. 85-101, 2021, DOI:10.32604/sdhm.2021.014256 - 03 June 2021

Abstract For practical engineering structures, it is usually difficult to measure external load distribution in a direct manner, which makes inverse load identification important. Specifically, load identification is a typical inverse problem, for which the models (e.g., response matrix) are often ill-posed, resulting in degraded accuracy and impaired noise immunity of load identification. This study aims at identifying external loads in a stiffened plate structure, through comparing the effectiveness of different methods for parameter selection in regulation problems, including the Generalized Cross Validation (GCV) method, the Ordinary Cross Validation method and the truncated singular value decomposition… More >

Abdoullah Namdar^1,2,3,*

Structural Durability & Health Monitoring, Vol.15, No.2, pp. 167-182, 2021, DOI:10.32604/sdhm.2021.011127 - 03 June 2021

Abstract The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely. The nonlinear stress and strain analysis of an embankment is needed to evaluate by using a combination of suitable methods. In this study, a large-scale geostructure was seismically simulated and analyzed using the nonlinear finite element method (NFEM), and linear regression method which is a soft computing technique (SC) was applied for evaluating the results of NFEM, and it supports engineering judgment because the design… More >

Heonmoo Kim, Yosoon Choi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 943-964, 2021, DOI:10.32604/cmes.2021.015300 - 24 May 2021

Abstract In underground mine environments where various hazards exist, such as tunnel collapse, toxic gases, the application of autonomous robots can improve the stability of exploration and efficiently perform repetitive exploratory operations. In this study, we developed a small autonomous driving robot for unmanned environmental monitoring in underground mines. The developed autonomous driving robot controls the steering according to the distance to the tunnel wall measured using the light detection and ranging sensor mounted on the robot to estimate its location by simultaneously considering the measured values of the inertial measurement unit and encoder sensors. In… More >

Fawaz Jaber Alsolami¹, Abdullah Saad Al-Malaise ALGhamdi², Asif Irshad Khan^1,*, Yoosef B. Abushark¹, Abdulmohsen Almalawi¹, Farrukh Saleem², Alka Agrawal³, Rajeev Kumar^3,4, Raees Ahmad Khan³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2895-2912, 2021, DOI:10.32604/cmc.2021.017469 - 06 May 2021

Abstract Ever since its outbreak in the Wuhan city of China, COVID-19 pandemic has engulfed more than 211 countries in the world, leaving a trail of unprecedented fatalities. Even more debilitating than the infection itself, were the restrictions like lockdowns and quarantine measures taken to contain the spread of Coronavirus. Such enforced alienation affected both the mental and social condition of people significantly. Social interactions and congregations are not only integral part of work life but also form the basis of human evolvement. However, COVID-19 brought all such communication to a grinding halt. Digital interactions have… More >

Zhengzheng Li¹, Jiancheng Zou^2,*, Peizhou Yan¹, Don Hong³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 811-822, 2021, DOI:10.32604/iasc.2021.016516 - 20 April 2021

Abstract Real-time and effective monitoring of a driver’s physiological parameters and psychological states can provide early warnings and help avoid traffic accidents. In this paper, we propose a non-contact real-time monitoring algorithm for physiological parameters of drivers under ambient light conditions. First, video sequences of the driver’s head are obtained by an ordinary USB camera and the AdaBoost algorithm is used to locate the driver’s facial region. Second, a face expression recognition algorithm based on an improved convolutional neural network (CNN) is proposed to recognize the driver’s facial expression. The forehead region is divided into three… More >

Xiang Wang^1,2, Jingxian Liu¹, Osamah Ibrahim Khalaf^3,*, Zhao Liu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 801-818, 2021, DOI:10.32604/cmes.2021.013568 - 19 April 2021

Abstract Complicated sea conditions have a serious impact on ship navigation safety and even maritime accidents. Accordingly, this paper proposes a remote sensing monitoring method based on the Beidou Navigation Satellite System (BDS) maritime joint positioning model. This method is mainly based on the BDS and multiple Global Navigation Satellite Systems (GNSS) to build a data fusion model, which can capture more steady positioning, navigation, and timing (PNT) data. Compared with the current Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) mandatory used by the International Maritime Organization (IMO), this model has the characteristics More >