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Search Results: 1 - 10 of 12690 matches for " Tianhong Luo "
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Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model
Shaojiang Dong,Shirong Yin,Baoping Tang,Lili Chen,Tianhong Luo
Shock and Vibration , 2014, DOI: 10.1155/2014/717465
Abstract: Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM) and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology. 1. Introduction Bearing is one of the most important components in rotating machinery. Accurate bearing degradation process prediction is the key to effective implement of condition based maintenance and can prevent unexpected failures and minimize overall maintenance costs [1, 2]. To achieve effective degradation process prediction of the bearing, firstly, the features should be extracted from the collected vibration data. Then, based on the extracted features effectively prediction models should be selected [3]. Feature extraction is the process of transforming the raw vibration data collected from running equipment to relevant information of health condition. There are three types of methods to deal with the raw vibration data: time domain analysis, frequency domain analysis, and time-frequency domain analysis. The three types of methods are often chosen to extract the feature. For example, Yu [4] chose the time domain and the frequency domain transform to describe the characteristics of the vibration signals. Yan et al. [5] chose the short-time Fourier transform to extract the features. Ocak et al. [6] chose the wavelet packet transform to extract the feature of bearing wear information. Because the frequency features from FFT analysis results often tend to average out transient vibrations and thus not providing a wholesome measure of the bearing health status, in this paper, the time domain and the time-frequency domain characteristics are used to extract the original features. Although the original features can be extracted, they are still with high dimension and include
Large-scale patterns in species diversity of fishes in the Yangtze River Basin

Xiaodong Yu,Tianhong Luo,Hongzhang Zhou,

生物多样性 , 2005,
Abstract: We synthesized the information on fish diversity in the Yangtze River Basin, documenting 378 species/subspecies that had been recorded and described from the basin, belonging to 14 orders, 32 families and 144 genera. Of these, 338 species/subspecies are freshwater fishes, of which 269 species/subspecies are from the Cypriniformes. Of the total, 11 species are migratory fishes, and 29 are species of brackish water of the estuary. A total of 162 species/subspecies are endemic to the river and 69 are threatened. We divided the Yangtze River Basin into 19 sub-basins. Except for the two sub-basins of the headwaters and the upper and middle reaches of Jinshajiang River, the other 17 sub-basins showed similar values in species richness and G-F diversity indices, although the values were higher in the upper reaches than in the middle and lower reaches. However, the proportion of endemic species decreased gradually from the headwater to the estuary of the basin in parallel with the gradient of elevation. Jaccard similarity analysis showed that the 19 sub-basins were clustered into three groups: (1) the headwaters and the upper and middle reaches of Jinshajiang River, located in the eastern Qinghai-Xizang Plateau and Hengduan Mountains; (2) the other sub-basins of the upper reaches, located in Western Sichuan Plateau, Yungui Plateau, Sichuan Basin, and Qinling-Daba Mountains; (3) the middle and lower reaches, belonging to the Huaiyang Mountains, Jiangnan Hills and the plain along the middle and lower reaches of the Yangtze River. This grouping reflects the environmental characteristics of the basins and the three large topographic platforms of the Chinese mainland.
The Linear Formulation of Thermal Unit Commitment Problem with Uncertainties through a Computational Mixed Integer  [PDF]
Mian Khuram Ahsan, Tianhong Pan, Zhengming Li
Journal of Power and Energy Engineering (JPEE) , 2018, DOI: 10.4236/jpee.2018.66001
Abstract: The solar and wind renewable energy is developing very rapidly to fulfill the energy gap. This specific increasing share of renewable energy is a reaction to the ecological trepidations to conciliate economics with security due to the new challenges in power system supply. In solar and wind renewable energy, the only partially predictable is the output with very low controllability which creates unit commitment problems in thermal units. In this research paper, a different linear formulation via mixed integer is presented that only requires “binary variables” and restraints concerning earlier stated models. The framework of this model allows precisely the costs of time-dependent startup & intertemporal limitations, for example, minimum up & down times and a ramping limit. To solve the unit commitment problem efficiently, a commercially available linear programming of mixed-integer is applied for sizeable practical scale. The results of the simulation are shown in conclusions.
A Three Decades of Marvellous Significant Review of Power Quality Events Regarding Detection & Classification  [PDF]
Mian Khuram Ahsan, Tianhong Pan, Zhengming Li
Journal of Power and Energy Engineering (JPEE) , 2018, DOI: 10.4236/jpee.2018.68001
Abstract: Around the globe, the necessity of green supply with a dedicated standard quality thrust of consumers is increasing day by day. The advancement in technology urges the electrical power system to deliver a high-quality rated undistorted sinusoidal current, the voltage at a constant desired standard frequency to its consumers. The present paper reveals a complete and inclusive study of power quality events, such as automatic classification and signal processing via creative techniques and the noises effect on the detection and classification of power quality disturbances. It’s planned to make a possible list for quick reference to obtain an extensive variety on the condition & status of available research for detection and classification for young engineers, designers and researchers who enter in the power quality field. The current extensive study is supported by a critical review of more than 200 publications on detection and classification techniques of power quality disturbances.
OSBP-Related Protein 8 (ORP8) Regulates Plasma and Liver Tissue Lipid Levels and Interacts with the Nucleoporin Nup62
Tianhong Zhou,Shiqian Li,Wenbin Zhong,Terhi Vihervaara,Olivier Béaslas,Julia Perttil?,Wei Luo,Yingliang Jiang,Markku Lehto,Vesa M. Olkkonen,Daoguang Yan
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0021078
Abstract: We earlier identified OSBP-related protein 8 (ORP8) as an endoplasmic reticulum oxysterol-binding protein implicated in cellular lipid homeostasis. We now investigated its action in hepatic cells in vivo and in vitro. Adenoviral overexpression of ORP8 in mouse liver induced a decrease of cholesterol, phospholipids, and triglycerides in serum (?34%, ?26%, ?37%, respectively) and liver tissue (?40%, ?12%, ?24%), coinciding with reduction of nuclear (n)SREBP-1 and -2 and mRNA levels of their target genes. Consistently, excess ORP8 reduced nSREBPs in HuH7 cells, and ORP8 overexpression or silencing by RNA interference moderately suppressed or induced the expression of SREBP-1 and SREBP-2 target genes, respectively. In accordance, cholesterol biosynthesis was reduced by ORP8 overexpression and enhanced by ORP8 silencing in [3H]acetate pulse-labeling experiments. ORP8, previously shown to bind 25-hydroxycholesterol, was now shown to bind also cholesterol in vitro. Yeast two-hybrid, bimolecular fluorescence complementation (BiFC), and co-immunoprecipitation analyses revealed the nuclear pore component Nup62 as an interaction partner of ORP8. Co-localization of ORP8 and Nup62 at the nuclear envelope was demonstrated by BiFC and confocal immunofluorescence microscopy. Furthermore, the impact of overexpressed ORP8 on nSREBPs and their target mRNAs was inhibited in cells depleted of Nup62. Our results reveal that ORP8 has the capacity to modulate lipid homeostasis and SREBP activity, probably through an indirect mechanism, and provide clues of an entirely new mode of ORP action.
A large-scale pattern in species diversity of reptiles in the Yangtze River Basin

Yu XiaoDong,Luo TianHong,Dai Jiang,Wu YuMing,Zhou GongZhang,

生物多样性 , 2005,
Abstract: We synthesized information on reptile biodiversity in the Yangtze River Basin. We documented 166 species that had been recorded and described from the basin. There are 3 orders,18 families and 68 gen- era. Of these,24 species are endemic and 54 endangered. Since the distribution patterns of terrestrial reptiles are determined by the deep rivers and high mountains to a great extent,we divided the Yangtze River Basin into 19 sub-regions. Except the headwater of the basin,the other 18 sub-regions show similar values in spe- cies richness and G-F index. However,the proportion of endemic species decreased gradually from the headwater to the estuary of the basin with the gradient of elevation. Based on the species distribution in 19 sub-regions (Jaccard similarity),cluster analysis was used to analyze the similarity of reptiles in the 19 sub-regions. The 19 sub-regions were clustered into five groups:(1) The headwaters of the basin,(2) Heng- duan Mountains and Yunnan Plateau,(3) Sichuan Basin and Qinling-Dabashan Mountains,(4) Guizhou Pla- teau,Jiangnan hills,the Two-Lake Plain and the delta of the Yangtze River Basin,(5) Poyang Lake Plain,lower reaches of the basin,and Huaiyang Mountains (from Hanjiang River to Dabieshan Mountain). This grouping reflects the environmental characteristics of the total basin and the three large topographic plat- forms of the Chinese mainland.
Robust Stability of Uncertain Systems over Network with Bounded Packet Loss
Yafeng Guo,Tianhong Pan
Journal of Applied Mathematics , 2012, DOI: 10.1155/2012/945240
Abstract: This paper investigates the problem of robust stability of uncertain linear discrete-time system over network with bounded packet loss. A new Lyapunov functional is constructed. It can more fully utilize the characteristics of the packet loss; hence the established stability criterion is more effective to deal with the effect of packet loss on the stability. Numerical examples are given to illustrate the effectiveness and advantage of the proposed methods.
Aero-engine Thrust Estimation Based on Ensemble of Improved Wavelet Extreme Learning Machine
Zhou Jun, Zhang Tianhong
- , 2018, DOI: 10.16356/j.1005-1120.2018.02.290
Abstract: Aero-engine direct thrust control can not only improve the thrust control precision but also save the operating cost by reducing the reserved margin in design and making full use of aircraft engine potential performance. However, it is a big challenge to estimate engine thrust accurately. To tackle this problem, this paper proposes an ensemble of improved wavelet extreme learning machine (EW-ELM) for aircraft engine thrust estimation. Extreme learning machine (ELM) has been proved as an emerging learning technique with high efficiency. Since the combination of ELM and wavelet theory has the both excellent properties, wavelet activation functions are used in the hidden nodes to enhance non-linearity dealing ability. Besides, as original ELM may result in ill-condition and robustness problems due to the random determination of the parameters for hidden nodes, particle swarm optimization (PSO) algorithm is adopted to select the input weights and hidden biases. Furthermore, the ensemble of the improved wavelet ELM is utilized to construct the relationship between the sensor measurements and thrust. The simulation results verify the effectiveness and efficiency of the developed method and show that aero-engine thrust estimation using EW-ELM can satisfy the requirements of direct thrust control in terms of estimation accuracy and computation time.
Fault Diagnosis for Micro-Gas Turbine Engine Sensors via Wavelet Entropy
Bing Yu,Dongdong Liu,Tianhong Zhang
Sensors , 2011, DOI: 10.3390/s111009928
Abstract: Sensor fault diagnosis is necessary to ensure the normal operation of a gas turbine system. However, the existing methods require too many resources and this need can’t be satisfied in some occasions. Since the sensor readings are directly affected by sensor state, sensor fault diagnosis can be performed by extracting features of the measured signals. This paper proposes a novel fault diagnosis method for sensors based on wavelet entropy. Based on the wavelet theory, wavelet decomposition is utilized to decompose the signal in different scales. Then the instantaneous wavelet energy entropy (IWEE) and instantaneous wavelet singular entropy (IWSE) are defined based on the previous wavelet entropy theory. Subsequently, a fault diagnosis method for gas turbine sensors is proposed based on the results of a numerically simulated example. Then, experiments on this method are carried out on a real micro gas turbine engine. In the experiment, four types of faults with different magnitudes are presented. The experimental results show that the proposed method for sensor fault diagnosis is efficient.
A Conductometric Indium Oxide Semiconducting Nanoparticle Enzymatic Biosensor Array
Dongjin Lee,Janet Ondrake,Tianhong Cui
Sensors , 2011, DOI: 10.3390/s111009300
Abstract: We report a conductometric nanoparticle biosensor array to address the significant variation of electrical property in nanomaterial biosensors due to the random network nature of nanoparticle thin-film. Indium oxide and silica nanoparticles (SNP) are assembled selectively on the multi-site channel area of the resistors using layer-by-layer self-assembly. To demonstrate enzymatic biosensing capability, glucose oxidase is immobilized on the SNP layer for glucose detection. The packaged sensor chip onto a ceramic pin grid array is tested using syringe pump driven feed and multi-channel I–V measurement system. It is successfully demonstrated that glucose is detected in many different sensing sites within a chip, leading to concentration dependent currents. The sensitivity has been found to be dependent on the channel length of the resistor, 4–12 nA/mM for channel lengths of 5–20 μm, while the apparent Michaelis-Menten constant is 20 mM. By using sensor array, analytical data could be obtained with a single step of sample solution feeding. This work sheds light on the applicability of the developed nanoparticle microsensor array to multi-analyte sensors, novel bioassay platforms, and sensing components in a lab-on-a-chip.
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