Wind turbine prognostics and maintenance management based on a hybrid approach of neural networks and a proportional hazards model

2017 ◽  
Vol 231 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Peyman Mazidi ◽  
Lina Bertling Tjernberg ◽  
Miguel A Sanz Bobi
Keyword(s):  
Condition Monitoring ◽  
Wind Farm ◽  
Stress Condition ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Hybrid Approach ◽  
Principal Component ◽  
Mathematical Form ◽  
Hazards Model ◽  
Normal Behavior

This paper proposes an approach for stress condition monitoring and maintenance assessment in wind turbines (WTs) through large amounts of collected data from the supervisory control and data acquisition (SCADA) system. The objectives of the proposed approach are to provide a stress condition model for health monitoring, to assess the WT’s maintenance strategies, and to provide recommendations on current maintenance schemes for future operations of the wind farm. At first, several statistical techniques, namely principal component analysis, Pearson, Spearman and Kendall correlations, mutual information, regressional ReliefF and decision trees are used and compared to assess the data for dimensionality reduction and parameter selection. Next, a normal behavior model is constructed by an artificial neural network which performs condition monitoring analysis. Then, a model based on the mathematical form of a proportional hazards model is developed where it represents the stress condition of the WT. Finally, those two models are jointly employed in order to analyze the overall performance of the WT over the study period. Several cases are analyzed with five-year SCADA data and maintenance information is utilized to develop and validate the proposed approach.

Remaining useful life prediction of lubricating oil with dynamic principal component analysis and proportional hazards model

2019 ◽  
Vol 234 (6) ◽  
pp. 964-971
Author(s):  
Ying Du ◽  
Tonghai Wu ◽  
Shengxi Zhou ◽  
Viliam Makis
Keyword(s):  
Condition Monitoring ◽  
Life Prediction ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Principal Component ◽  
Remaining Useful Life ◽  
Lubricating Oil ◽  
Hazards Model ◽  
Dynamic Principal Component Analysis ◽  
Useful Life

Lubricating oil contains a lot of tribological information of the machine and plays an important role in machine health. Oil degrades with serving time and causes severe wear afterwards, which is a complex dynamic process, and difficult to be accurately described by a single property. Therefore, the main purpose of deterioration prediction is to estimate the remaining useful life that the oil can still fulfill its functions by analyzing oil condition monitoring data. With a large amount of oil condition monitoring data collected, a vector autoregressive model is applied to the original oil data to describe the dynamic deterioration process. Then dynamic principal component analysis, an effective dimensionality reduction method, is employed to obtain the principal components capturing the most information of the oil data. The proportional hazards model is then built to calculate the failure risk of the lubricating oil based on the condition monitoring information, where its baseline function represents the aging process assuming to follow the Weibull distribution and its positive link function represents the influence of covariates (the principal components) on the failure risk. Finally, the remaining useful life prediction of lubricating oil can be obtained by explicit formulas of the characteristics such as the conditional reliability function and the mean residual life function. This work provides an approach to assess the health of lubricating oil, and a guidance for oil maintenance strategy.

HRA Model for Hypercholesterolemia Based on a Longitudinal Health Database

1998 ◽  
Vol 37 (02) ◽  
pp. 130-133
Author(s):  
T. Kishimoto ◽  
Y. Iida ◽  
K. Yoshida ◽  
M. Miyakawa ◽  
H. Sugimori ◽  
...  
Keyword(s):  
Total Cholesterol ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Model Analysis ◽  
Serum Total Cholesterol ◽  
Hazards Model ◽  
The Mean ◽  
Health Database ◽  
Observation Period

AbstractTo evaluate the risk factors for hypercholesterolemia, we examined 4,371 subjects (3,207 males and 1,164 females) who received medical checkups more than twice at an AMHTS in Tokyo during the period from 1976 through 1991; and whose serum total cholesterol was under 250 mg/dl. The mean follow-up duration was 6.6 years. A self-registering questionnaire was administered at the time of the health checkup. The endpoint of this study was the onset of hypercholesterolemia when the level of serum total cholesterol was 250 mg/dl and over. We compared two prognosis groups (normal and hypercholesterol) in terms of age, examination findings and lifestyle. After assessing each variable, we employed Cox's proportional hazards model analysis to determine the factors related to the occurrence of hypercholesterolemia. According to proportional hazards model analysis, total cholesterol, triglyceride and smoking at the beginning, and hypertension during the observation period were selected in males; and total cholesterol at the beginning and age were selected in females to determine the factors related to the occurrence of hypercholesterolemia.

Correlates of Child Mortality in Pakistan: A Hazards Model Analysis

1999 ◽  
Vol 38 (1) ◽  
pp. 85-118 ◽  
Author(s):  
Jennifer Benneti
Keyword(s):  
Child Mortality ◽  
Proportional Hazards ◽  
Contraceptive Use ◽  
Proportional Hazards Model ◽  
Economic Status ◽  
Model Analysis ◽  
Health Seeking ◽  
Large Cities ◽  
Number Of Children ◽  
Hazards Model

This study investigated factors associated with child mortality in an area in Rawalpindi, one of the large cities of Pakistan. Using both demographic and anthropological methods, the research was conducted to specifically examine the processes and mechanisms whereby a link is established between child mortality and its covariates. Controlling for the socio-economic status as a determinant of child mortality, the study population was limited to a lower income stratum living in a homogeneous environment where all households had equal access to health-related and other facilities. Results of the proportional hazards model analysis on 130I index children suggest that non-economic factors like maternal health-seeking behaviour were related to high child mortality. The cultural norm of bearing a large number of children was the most significant correlate. In order of significance, this was followed by contraceptive use, current age of the mother, age at marriage and the hygienic conditions of the household. The study provides strong evidence of familial clustering of mortality by order of the household.

scholarly journals Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maryam Farhadian ◽  
Sahar Dehdar Karsidani ◽  
Azadeh Mozayanimonfared ◽  
Hossein Mahjub
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Coronary Intervention ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Cerebrovascular Events ◽  
Long Term Follow Up ◽  
Stent Length

Abstract Background Due to the limited number of studies with long term follow-up of patients undergoing Percutaneous Coronary Intervention (PCI), we investigated the occurrence of Major Adverse Cardiac and Cerebrovascular Events (MACCE) during 10 years of follow-up after coronary angioplasty using Random Survival Forest (RSF) and Cox proportional hazards models. Methods The current retrospective cohort study was performed on 220 patients (69 women and 151 men) undergoing coronary angioplasty from March 2009 to March 2012 in Farchshian Medical Center in Hamadan city, Iran. Survival time (month) as the response variable was considered from the date of angioplasty to the main endpoint or the end of the follow-up period (September 2019). To identify the factors influencing the occurrence of MACCE, the performance of Cox and RSF models were investigated in terms of C index, Integrated Brier Score (IBS) and prediction error criteria. Results Ninety-six patients (43.7%) experienced MACCE by the end of the follow-up period, and the median survival time was estimated to be 98 months. Survival decreased from 99% during the first year to 39% at 10 years' follow-up. By applying the Cox model, the predictors were identified as follows: age (HR = 1.03, 95% CI 1.01–1.05), diabetes (HR = 2.17, 95% CI 1.29–3.66), smoking (HR = 2.41, 95% CI 1.46–3.98), and stent length (HR = 1.74, 95% CI 1.11–2.75). The predictive performance was slightly better by the RSF model (IBS of 0.124 vs. 0.135, C index of 0.648 vs. 0.626 and out-of-bag error rate of 0.352 vs. 0.374 for RSF). In addition to age, diabetes, smoking, and stent length, RSF also included coronary artery disease (acute or chronic) and hyperlipidemia as the most important variables. Conclusion Machine-learning prediction models such as RSF showed better performance than the Cox proportional hazards model for the prediction of MACCE during long-term follow-up after PCI.

scholarly journals Influence of Tourism Seasonality and Financial Ratios on Hotels’ Exit Risk

2021 ◽  
pp. 109634802110160
Author(s):  
Dengjun Zhang ◽  
Jinghua Xie
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Hotel Industry ◽  
Financial Ratios ◽  
Market Segment ◽  
Tourism Demand ◽  
Hazards Model ◽  
Two Measures ◽  
The Impact

Tourism seasonality negatively affects hotels’ operational and financial performance and then survival probabilities. Several studies have evaluated the impact of tourism seasonality on hotels’ exit risk. However, the empirical findings are ambiguous, probably due to the overall seasonality and different measures used in these studies. Against this background, this study explores the impact of tourism seasonality on hotel firms’ exit risk, using a proportional hazards model. We controlled for financial ratios, the main factors influencing the exit risk, and used two measures of tourism seasonality by market segment, namely, leisure, business, and conference tourism. The case study is the Norwegian hotel industry. The empirical results suggest that the different seasonal patterns of tourism demand in the market segments mitigate the impact of the overall seasonality on hotels’ exit risk, and that seasonality measures of various tourism segments affect the exit risk in different ways.

scholarly journals Elevated plasma growth and differentiation factor 15 predicts incident anemia in older adults aged 60 years and older

2020 ◽  
Author(s):  
Yuko Yamaguchi ◽  
Marta Zampino ◽  
Toshiko Tanaka ◽  
Stefania Bandinelli ◽  
Yusuke Osawa ◽  
...  
Keyword(s):  
Older Adults ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Differentiation Factor ◽  
Hazards Model ◽  
Increased Risk ◽  
The Relationship

Abstract Background Anemia is common in older adults and associated with greater morbidity and mortality. The causes of anemia in older adults have not been completely characterized. Although elevated circulating growth and differentiation factor 15 (GDF-15) has been associated with anemia in older adults, it is not known whether elevated GDF-15 predicts the development of anemia. Methods We examined the relationship between plasma GDF-15 concentrations at baseline in 708 non-anemic adults, aged 60 years and older, with incident anemia during 15 years of follow-up among participants in the Invecchiare in Chianti (InCHIANTI) Study. Results During follow-up, 179 (25.3%) participants developed anemia. The proportion of participants who developed anemia from the lowest to highest quartile of plasma GDF-15 was 12.9%, 20.1%, 21.2%, and 45.8%, respectively. Adults in the highest quartile of plasma GDF-15 had an increased risk of developing anemia (Hazards Ratio 1.15, 95% Confidence Interval 1.09, 1.21, P<.0001) compared to those in the lower three quartiles in a multivariable Cox proportional hazards model adjusting for age, sex, serum iron, soluble transferrin receptor, ferritin, vitamin B12, congestive heart failure, diabetes mellitus, and cancer. Conclusions Circulating GDF-15 is an independent predictor for the development of anemia in older adults.

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