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Design and realization of a remote monitoring and diagnosis and prediction system for large rotating

Shaohong WANG, Tao CHEN, Jianghong SUN

《机械工程前沿（英文）》 2010年 第5卷 第2期   页码 165-170 doi: 10.1007/s11465-009-0090-1

摘要： Traditional on-site fault diagnosis means cannot meet the needs of large rotating machinery for its performance and complexity. Remote monitoring and diagnosis technology is a new fault diagnosis mode combining computer technology, communication technology, and fault diagnosis technology. The designed remote monitoring and diagnosis and prediction system for large rotating machinery integrates the distributed resources in different places and breaks through shortcomings as the offline and decentralized information. The system can make further implementation of equipment prediction technology research based on condition monitoring and fault diagnosis, provide on-site analysis results, and carry out online actual verification of the results. The system monitors real-time condition of the equipment and achieves early fault prediction with great significance to guarantee safe operation, saves maintenance costs, and improves utilization and management of the equipment.

关键词： large rotating machinery     remote monitoring     fault diagnosis     prediction system    

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Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

《能源前沿（英文）》 2013年 第7卷 第4期   页码 468-478 doi: 10.1007/s11708-013-0282-6

摘要： In a competitive and deregulated power scenario, the utilities try to maintain their real electric power generation in balance with the load demand, which creates a need for the precise real time generation scheduling (GS). In this paper, the GS problem is solved to perform the unit commitment (UC) based on frequency prediction by using artificial neural network (ANN) with the objective to minimize the overall system cost of the state utility. The introduction of availability-based tariff (ABT) signifies the importance of frequency in GS. Under-prediction or over-prediction will result in an unnecessary commitment of generating units or buying power from central generating units at a higher cost. Therefore, an accurate frequency prediction is the first step toward optimal GS. The dependency of frequency on various parameters such as actual generation, load demand, wind power and power deficit has been considered in this paper. The proposed technique provides a reliable solution for the input parameter different from the one presented in the training data. The performance of the frequency predictor model has been evaluated based on the absolute percentage error (APE) and the mean absolute percentage error (MAPE). The proposed predicted frequency sensitive GS model is applied to the system of Indian state of Tamilnadu, which reduces the overall system cost of the state utility by keeping off the dearer units selected based on the predicted frequency.

关键词： artificial neural network (ANN)     frequency prediction     availability-based tariff (ABT)     generation scheduling (GS)    

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

《结构与土木工程前沿（英文）》 2021年 第15卷 第1期   页码 61-79 doi: 10.1007/s11709-020-0684-6

摘要： Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

关键词： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive strength    

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中国气象预报业务工程体系建设和发展

颜宏,李泽椿,马清云,田翠英

《中国工程科学》 2000年 第2卷 第11期   页码 88-93

摘要：

文章介绍中国气象预报业务工程体系的建设和发展过程、现代气象预报业务所包含的子系统及其相 关技术以及21世纪气象预报业务建设的技术发展趋势和展望。

关键词： 气象预报     业务工程体系     发展    

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Optimization and performance prediction of a new near-zero emission coal utilization system with combined

GUAN Jian, WANG Qinhui, LI Xiaomin, LUO Zhongyang, CEN Kefa

《能源前沿（英文）》 2007年 第1卷 第1期   页码 113-119 doi: 10.1007/s11708-007-0013-y

摘要： In accordance with the new near-zero emission coal utilization system with combined gasification and combustion, which is based on the CO acceptor gasification process, the product gas composition of the gasifier and the combustor was calculated by means of thermodynamic equilibrium calculation software FactSage 5.2. Based on these calculations, the whole system efficiency calculation method that complies with the mass and energy conservation principle was established. To enhance the system efficiency, the system pressure and the gasifier carbon conversion ratio were optimized. The results indicate that the system efficiency increases with increasing pressure and gasifier carbon conversion ratio. After taking into consideration the influence of the pressure and carbon conversion ratio on the performance of the system, the gasifier and the combustor were synthetically studied. The optimum system pressure and carbon conversion ratio were obtained as 2.5 MPa and 0.7, respectively. The system efficiency could reach around 62.1% when operated in these two optimum parameters. If the advanced ion transport membrane (ITM) air separation technology is used, there would be an increase of another 1.3%.

关键词： influence     efficiency calculation     optimum     software FactSage     transport    

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A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Pengfei DU, Zhiyi LI, Jinliang HUANG

《环境科学与工程前沿（英文）》 2013年 第7卷 第5期   页码 735-745 doi: 10.1007/s11783-013-0560-x

摘要： Drinking water sources are highly valued by authorities for safeguarding the life of a city. Models are widely applied as important and effective tools in the management of water sources. However, it is difficult to apply models in water source management because water managers are often not equipped with the professional knowledge and operational skills necessary for making use of the models. This paper introduces a drinking water source simulation and prediction system that consists of a watershed model, a hydrological model and a water quality model. This system provides methods and technical guidance for the conventional management of water sources and emergency water event response. In this study, the sub-models of the system were developed based on the data of the Jiangdong Reservoir in Xiamen, and the model validation was based on local monitoring data. The hydrological model and water quality model were integrated by computer programming, and the watershed model was indirectly integrated into the system through a network platform. Furthermore, three applications for Jiangdong Reservoir water protection utilizing the system were introduced in this paper, including a conventional simulation, an emergency simulation, and an emergency measures evaluation.

关键词： water source     integrated modeling system     prediction     Jiulong River    

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A control scheme with performance prediction for a PV fed water pumping system

Ramesh K GOVINDARAJAN,Pankaj Raghav PARTHASARATHY,Saravana Ilango GANESAN

《能源前沿（英文）》 2014年 第8卷 第4期   页码 480-489 doi: 10.1007/s11708-014-0334-6

摘要： This paper focuses on modeling and performance predetermination of a photovoltaic (PV) system with a boost converter fed permanent magnet direct current (PMDC) motor-centrifugal pump load, taking the converter losses into account. Sizing is done based on the maximum power generated by the PV array at the average irradiation. Hence optimum sizing of the PV array for the given irradiation at the geographical location of interest is obtained using the predetermined values. The analysis presented here involves systems employing maximum power point tracking (MPPT) as they are more efficient than directly coupled systems. However, the voltage and power of the motor might rise above rated values for irradiations greater than the average when employing MPPT, hence a control scheme has been proposed to protect the PMDC motor from being damaged during these conditions. This control scheme appropriately chooses the optimum operating point of the system, ensuring long-term sustained operation. The numerical simulation of the system is performed in Matlab/Simulink and is validated with experimental results obtained from a 180 V, 0.5 hp PMDC motor coupled to a centrifugal pump. The operation of the system with the proposed control scheme is verified by varying the irradiation levels and the relevant results are presented.

关键词： photovoltaic system     boost converter     maximum power point tracking (MPPT)     DC permanent-magnet motor     centrifugal pump    

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面向维修的机械系统可靠度预测与仿真研究

黄良沛,尹喜云,岳文辉

《中国工程科学》 2007年 第9卷 第12期   页码 69-74

摘要： 机电产品在服役期间因零件失效而产生故障，重组维修破坏了原有的系统可靠性模型，因而需要对设备可靠性问题重新进行研究和评价。基于机电系统中零件的失效时间分布密度函数，研究了在重组维护过程中机电系统服役期间零件年龄结构的分布规律，发展了机电系统可靠性数学模型。通过仿真研究，探讨了系统服役期间年龄结构、可靠度和失效率的发展规律，定量地研究了失效时间分布密度函数的参数对系统可靠度的影响。这对于评估机械系统的可靠性和全生命周期的失效率，制定合理的维修策略具有重要意义。

关键词： 重组维修；可靠度预测；年龄分布；失效率    

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Construction risks of Huaying mount tunnel and countermeasures

Haibo YAO, Feng GAO, Shigang YU, Wei DANG

《结构与土木工程前沿（英文）》 2017年 第11卷 第3期   页码 279-285 doi: 10.1007/s11709-017-0414-x

摘要： The Chongqing-Guang’an motorway is planned to cross Huaying mount at Jingguan town of Chongqing city. The whole mount is a colossal anticline whose core is consisted of coal measure strata (upper Permian Longtan formation P l) and the limbs are limestone strata (middle Triassic Leikoupo formation T l and lower Triassic Jialingjiang formation T j). The tunneling is full of risks of collapse, gas explosion or gas outburst, water (mud) inrush, gas inrush because of existence of faults, high pressure gas, karst tectonics and coal goafs around the tunnel. In order to cope with the high risk, two main countermeasures were taken to ensure security of construction. One is geology prediction, and the other is automatic wireless real-time monitoring system, which contains monitoring of video, wind speed, poisonous gas (CH , CO, H S, SO ), people location, and automatic power-off equipment while gas contents being more than warning threshold. These ascertained the engineering safety effectively.

关键词： tunnel?construction     gas?outburst     geology?prediction     automatic?monitoring?system    

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Spatial prediction of soil contamination based on machine learning: a review

《环境科学与工程前沿（英文）》 2023年 第17卷 第8期 doi: 10.1007/s11783-023-1693-1

摘要：

● A review of machine learning (ML) for spatial prediction of soil contamination.

关键词： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

《医学前沿（英文）》 2022年 第16卷 第3期   页码 496-506 doi: 10.1007/s11684-021-0828-7

摘要： The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients’ physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

关键词： XGBoost     deep neural network     healthcare     risk prediction    

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Position-varying surface roughness prediction method considering compensated acceleration in milling

《机械工程前沿（英文）》 2021年 第16卷 第4期   页码 855-867 doi: 10.1007/s11465-021-0649-z

摘要： Machined surface roughness will affect parts’ service performance. Thus, predicting it in the machining is important to avoid rejects. Surface roughness will be affected by system position dependent vibration even under constant parameter with certain toolpath processing in the finishing. Aiming at surface roughness prediction in the machining process, this paper proposes a position-varying surface roughness prediction method based on compensated acceleration by using regression analysis. To reduce the stochastic error of measuring the machined surface profile height, the surface area is repeatedly measured three times, and Pauta criterion is adopted to eliminate abnormal points. The actual vibration state at any processing position is obtained through the single-point monitoring acceleration compensation model. Seven acceleration features are extracted, and valley, which has the highest R-square proving the effectiveness of the filtering features, is selected as the input of the prediction model by mutual information coefficients. Finally, by comparing the measured and predicted surface roughness curves, they have the same trends, with the average error of 16.28% and the minimum error of 0.16%. Moreover, the prediction curve matches and agrees well with the actual surface state, which verifies the accuracy and reliability of the model.

关键词： surface roughness prediction     compensated acceleration     milling     thin-walled workpiece    

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Improved prediction of pile bending moment and deflection due to adjacent braced excavation

《结构与土木工程前沿（英文）》 doi: 10.1007/s11709-023-0961-2

摘要： Deep excavations in dense urban areas have caused damage to nearby existing structures in numerous past construction cases. Proper assessment is crucial in the initial design stages. This study develops equations to predict the existing pile bending moment and deflection produced by adjacent braced excavations. Influential parameters (i.e., the excavation geometry, diaphragm wall thickness, pile geometry, strength and small-strain stiffness of the soil, and soft clay thickness) were considered and employed in the developed equations. It is practically unfeasible to obtain measurement data; hence, artificial data for the bending moment and deflection of existing piles were produced from well-calibrated numerical analyses of hypothetical cases, using the three-dimensional finite element method. The developed equations were established through a multiple linear regression analysis of the artificial data, using the transformation technique. In addition, the three-dimensional nature of the excavation work was characterized by considering the excavation corner effect, using the plane strain ratio parameter. The estimation results of the developed equations can provide satisfactory pile bending moment and deflection data and are more accurate than those found in previous studies.

关键词： pile responses     excavation     prediction     deflection     bending moments    

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Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

《能源前沿（英文）》 2016年 第10卷 第4期   页码 479-488 doi: 10.1007/s11708-016-0425-7

摘要： In this paper a novel method for reliability prediction and validation of nuclear power units in service is proposed. The equivalent availability factor is used to measure the reliability, and the equivalent availability factor deducting planed outage hours from period hours and maintenance factor are used for the measurement of inherent reliability. By statistical analysis of historical reliability data, the statistical maintenance factor and the undetermined parameter in its numerical model can be determined. The numerical model based on the maintenance factor predicts the equivalent availability factor deducting planed outage hours from period hours, and the planed outage factor can be obtained by using the planned maintenance days. Using these factors, the equivalent availability factor of nuclear power units in the following 3 years can be obtained. Besides, the equivalent availability factor can be predicted by using the historical statistics of planed outage factor and the predicted equivalent availability factor deducting planed outage hours from period hours. The accuracy of the reliability prediction can be evaluated according to the comparison between the predicted and statistical equivalent availability factors. Furthermore, the reliability prediction method is validated using the nuclear power units in North American Electric Reliability Council (NERC) and China. It is found that the relative errors of the predicted equivalent availability factors for nuclear power units of NERC and China are in the range of –2.16% to 5.23% and –2.15% to 3.71%, respectively. The method proposed can effectively predict the reliability index in the following 3 years, thus providing effective reliability management and maintenance optimization methods for nuclear power units.

关键词： nuclear power units in service     reliability     reliability prediction     equivalent availability factors    

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Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

《机械工程前沿（英文）》 2010年 第5卷 第2期   页码 171-175 doi: 10.1007/s11465-009-0091-0

摘要： Trend prediction technology is the key technology to achieve condition-based maintenance of mechanical equipment. Large-sized water injection units are key equipment in oilfields. The traditional preventive maintenance is not economical and cannot completely avoid vicious accidents. To ensure the normal operation of units and save maintenance costs, trend prediction technology is studied to achieve condition-based maintenance for water injection units. The main methods of the technology are given, the trend prediction method based on neural network is put forward, and the expert system based on the knowledge is developed. The industrial site verification shows that the proposed trend prediction technology can reflect the operating condition trend change of the water injection units and provide technical means to achieve condition-based predictive maintenance.

关键词： water injection units     condition-based maintenance     trend prediction    

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标题 作者 时间 类型 操作

Design and realization of a remote monitoring and diagnosis and prediction system for large rotating

Shaohong WANG, Tao CHEN, Jianghong SUN

期刊论文

Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

期刊论文

Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

期刊论文

中国气象预报业务工程体系建设和发展

颜宏,李泽椿,马清云,田翠英

期刊论文

Optimization and performance prediction of a new near-zero emission coal utilization system with combined

GUAN Jian, WANG Qinhui, LI Xiaomin, LUO Zhongyang, CEN Kefa

期刊论文

A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Pengfei DU, Zhiyi LI, Jinliang HUANG

期刊论文

A control scheme with performance prediction for a PV fed water pumping system

Ramesh K GOVINDARAJAN,Pankaj Raghav PARTHASARATHY,Saravana Ilango GANESAN

期刊论文

面向维修的机械系统可靠度预测与仿真研究

黄良沛,尹喜云,岳文辉

期刊论文

Construction risks of Huaying mount tunnel and countermeasures

Haibo YAO, Feng GAO, Shigang YU, Wei DANG

期刊论文

Spatial prediction of soil contamination based on machine learning: a review

期刊论文

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

期刊论文

Position-varying surface roughness prediction method considering compensated acceleration in milling

期刊论文

Improved prediction of pile bending moment and deflection due to adjacent braced excavation

期刊论文

Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

期刊论文

Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

期刊论文