Comprehensive health condition assessment on partial sewers in a southern Chinese city based on fuzzy mathematic methods

2013 ◽  
Vol 8 (1) ◽  
pp. 144-150 ◽  
Author(s):  
Lili Gan ◽  
Jiane Zuo ◽  
Yajiao Wang ◽  
Thong Soon Low ◽  
Kaijun Wang
2019 ◽  
Vol 2019 ◽  
pp. 1-21
Author(s):  
X.-M. Zhang ◽  
D. X. Zhou ◽  
M. Chen

The idea of diesel engine health evaluation is put forward, and the calculation flow, fast algorithm, and influencing factors of wavelet fractal dimension are analyzed. Through the real vehicle experiment, the corresponding relationship between the fractal dimension of the wavelet and the health condition of the diesel engine is calculated and analyzed. Three quantitative expression parameters, age health degree, dimension health degree, and comprehensive health degree, are defined considering the age and working condition of diesel engine. Finally, the consistency of health degree with vibration intensity, acceleration time, deceleration time, and fuel consumption was confirmed. It has been proved that it is feasible to evaluate the health of diesel engine with health degree.


2018 ◽  
Vol 62 (16) ◽  
pp. 4923-4941 ◽  
Author(s):  
Ruohui Zhao ◽  
Hongwei Zhang ◽  
Yong Jiang ◽  
Xuening Yao

The present study examines police officer attitudes and responses to domestic violence on a sample of 520 officers in a southern Chinese city. The police officers were asked to respond to two vignette scenarios depicting husbands assaulting their wives. The results show high correlations between officer responses to the two vignettes: Husbands are much more likely to be arrested than wives. The results of logistic regression analysis reveal that officers who view their profession as that of a law enforcer are more likely to arrest either husbands or wives. Officers who believe domestic violence to be a private matter are less inclined to arrest husbands, while those who hold profeminist attitudes are more inclined to do so. Finally, the implications are considered for further understanding of police responses to domestic violence in the Chinese context.


2014 ◽  
Vol 643 ◽  
pp. 363-367
Author(s):  
Yu Hang Zheng ◽  
Zi Cheng Ning

According to exist problem of servomechanism health condition assessment because of complicated measurement data, a method that based on grey target theory is proposed. By combining the principal component analysis (PCA) and correlation analysis to filter index and determine index weight, then target correlation was obtained by weighting the coefficient of correlation between measurement sequence and standard model that determined by required figure and measurement data, at last, health condition of servomechanism was assessed by matching health condition degree. Experiment shows that this method with clear procedure can exactly evaluate the servomechanism health condition.


2013 ◽  
Vol 558 ◽  
pp. 546-553
Author(s):  
Gayan C. Kahandawa ◽  
Jayantha Ananda Epaarachchi ◽  
Hao Wang ◽  
Kin Tak Lau

ncreased use of FRP composites for critical load bearing components and structures in recent years has raised the alarm for urgent need of a comprehensive health mentoring system to alert users about integrity and the health condition of advanced composite structures. A few decades of research and development work on structural health monitoring systems using Fibre Bragg Grating (FBG) sensors have come to an accelerated phase at the moment to address these demands in advanced composite industries. However, there are many unresolved problems with identification of damage status of composite structures using FBG spectra and many engineering challenges for implementation of such FBG based SHM system in real life situations. This paper details a research work that was conducted to address one of the critical problems of FBG network, the procedures for immediate rehabilitation of FBG sensor networks due to obsolete/broken sensors. In this study an artificial neural network (ANN) was developed and successfully deployed to virtually simulate the broken/obsolete sensors in a FBG sensor network. It has been found that the prediction of ANN network was within 0.1% error levels.


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