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127 results on '"Wang, Zhenheng"'

22. Power Load Disaggregation of Households with Solar Panels Based on an Improved Long Short-term Memory Network

Author

Junnian Wang, Sun Jiaxuan, Wang Yanghua, Wang Zhenheng, and Wenxin Yu

Subjects
Mains electricity, Wind power, Electrical load, business.industry, Computer science, 020209 energy, 020208 electrical & electronic engineering, 02 engineering and technology, Solar energy, Automotive engineering, Renewable energy, Electric power system, Electricity generation, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, business, Solar power
Abstract

With the increasing application of small distributed renewable energy systems in household power supplies, when a large number of distributed renewable energy power generation systems are connected to the power grid, the time-varying output power of small solar energy, wind turbines, etc. Disaggregation and analysis of regional household electricity and renewable energy power supply systems connected to household electricity will help grid companies to conduct power dispatch management. This paper employed a two-way two-layer Long Short-term Memory deep learning network with improved input form to perform non-intrusive load disaggregation on household power with solar panels, which can monitor the load status of household electrical appliances and the output power of solar power generation system in real time. The power situation provides a decision basis for optimizing the response value of household energy demand and improving the demand of the power system from the response management level. The combined dataset from UK-DALE and kaggle’solar panel power generation data is adopted to train and test the proposed improved Long Short-term Memory network. The test results show that the proposed algorithm is applied to the household electric load disaggregation with solar panels, with high accuracy and reliability.

Published
2020
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23. Multi-fault diagnosis method for wind power generation system based on recurrent neural network

Author

Wang Junnian, Dou Yao, Wang Zhenheng, and Jiang Dan

Subjects
Wind power generation, Wind power, Scale (ratio), Computer science, business.industry, 020209 energy, Mechanical Engineering, Deep learning, 020208 electrical & electronic engineering, Energy Engineering and Power Technology, 02 engineering and technology, Fault (power engineering), Turbine, Automotive engineering, Data-driven, Recurrent neural network, 0202 electrical engineering, electronic engineering, information engineering, Artificial intelligence, business
Abstract

With the continuous expansion of the scale of wind turbine system, wind power production, operation and equipment control of wind turbine have become more and more significant. To improve the reliability of wind turbine systems fault diagnosis, combining with data-driven technology, this paper proposes a multi-fault diagnosis method for wind power system based on recurrent neural network. According to the actual wind speed data, the normal operation and fault data of the wind turbine system are obtained by system modeling, and the classification and prediction model based on the recurrent neural network algorithm is established, which takes 30 characteristic parameters such as wind speed, rotor speed, generator speed and power generation as input, and 10 different types faults labels of the wind turbine as output. Specific rules formed inside the sample data of the wind turbine system are learned intelligently by the model which is continuously trained, optimized and tested to verify the feasibility of the algorithm. The results of evaluation standards such as accuracy rate, missed detection rate and F1-measure that compared with other related algorithms such as deep belief network show that the proposed algorithm can solve the problem of multi-classification fault diagnosis for wind power generation system efficiently.

Published
2019
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30. Flowering characteristics and mating system of Fritillaria cirrhosa(Liliaceae),an endangered plant in China

Author

Ma, Yanzhu, Cui, Zhijia, Cheng, Chun Ya, Li, Ran, Wu, Haixu, Jin, Ling, Ma, Yi, and Wang, Zhenheng

Abstract

Fritillaria cirrhosaD. Don is an endangered species of the family Liliaceae that has economic, medicinal, and ecological values, as well as the source of the traditional Chinese medicine ‘Fritillariae Cirrhosae Bulbus.’ Fritillariae Cirrhosae Bulbus is one of the traditional precious Chinese medicines in China, which has the medicinal value of clearing away heat and moistening the lungs, resolving phlegm and relieving cough, dispelling knots, and eliminating carbuncle. In this study, the phenology, flowering dynamics, and floral traits of F. cirrhosawere observed in the field, and the related morphological indicators were measured. The pollen viability and stigma receptivity during flowering of F. cirrhosawere measured by MTT method and benzidine–hydrogen peroxide method, respectively, and the microstructures of pollen grains were observed using scanning electron microscopy. At the same time, the mating system of F. cirrhosawas evaluated by measuring the pollen and ovule ratio (P:O), determining the outcrossing index (OCI), and performing bagging experiments. Based on these observations, we found that the phenology of F. cirrhosawas from late April to mid-August, the average duration of 117 days, divided into eight stages from germination to fructescence, of which the population flowering lasted 31 days. The flowering period of F. cirrhosais divided into initial budding stage, middle budding stage, late budding stage, initial bloom stage, full bloom stage, and final bloom stage. Most of the anthers of F. cirrhosawere longitudinally split and released pollens from the proximal end of the anthers to the top from the second day of flowering, and the anthers corresponding to the outer corolla began to release pollens first. As the anthers dehisced and pollens were released, and the stamens were gradually lower than the pistils. The pollen grains of F. cirrhosawere prolate, which had the reticulated surface and various mesh sizes. The pollen viability and stigma receptivity of F. cirrhosaincreased at first and then decreased with the flowering stage. Combined with P:O = 2891.6 ± 373.4, OCI = 4 and the results of the bagging experiments, we determined that F. cirrhosawas generally outcrossing. These results provide the basis for the cultivation, breeding, and conservation of this rare and charismatic plant, helping to reveal the nature of its sexual reproduction process, explore the possible endangerment reasons from the perspective of reproductive biology, and provide a scientific basis for its protection and utilization.

Published
2022
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33. Hydrogen sulfide protects against particle‐induced inflammatory response and osteolysis via SIRT1 pathway in prosthesis loosening

Author

Liu, Lei, primary, Zhou, Ming, additional, Zhu, Ruofu, additional, Zhou, Jun, additional, Ni, Li, additional, Wang, Zhidong, additional, Liu, Naicheng, additional, Zhu, Feng, additional, Shi, Tongguo, additional, Deng, Zhantao, additional, Wang, Yong, additional, Tian, Yixing, additional, Li, Rongqun, additional, Yang, Huilin, additional, Wang, Zhenheng, additional, Jiang, Jiannong, additional, and Xu, Yaozeng, additional

Published
2020
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34. Open-circuit fault diagnosis of traction inverter based on improved convolutional neural network

Author

Wenxin Yu, Wang Zhenheng, Guang’an Zhong, Wang Junnian, and Liu Jun

Subjects
History, Control theory, Computer science, medicine.medical_treatment, medicine, Inverter, Hardware_PERFORMANCEANDRELIABILITY, Traction (orthopedics), Convolutional neural network, Computer Science Applications, Education
Abstract

In the traction system of high-speed EMUs, the inverter’s Insulated Gate Bipolar Transistor (IGBT) often occurs open-circuit (OC) faults. However, traditional fault diagnosis relies mainly on signal processing to extract fault features, which is susceptible to environmental interference, resulting in poor generalization ability of the model. Aiming at this problem, a fault diagnosis method based on an improved convolutional neural network is proposed. Firstly, the three-phase stator current signal is preprocessed by wavelet domain denoising. Secondly, fault features are independently learned through a convolutional network. Finally, a fully-connected layer is used for fault diagnosis. The experimental results show that this method could resolve the OC fault diagnosis problem of the inverter’s IGBT effectively, and also achieve higher accuracy under the interference of noise, and the diagnosis can be made at 0.01s after the fault occurs.

Published
2020
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38. Probiotics protect mice from CoCrMo particles-induced osteolysis

Author

Wang,Zhenheng, Xue,Kaiwen, Bai,Maosheng, Deng,Zhantao, Gan,Jingjing, Zhou,Gang, Qian,Hongbo, Bao,Nirong, Zhao,Jianning, Wang,Zhenheng, Xue,Kaiwen, Bai,Maosheng, Deng,Zhantao, Gan,Jingjing, Zhou,Gang, Qian,Hongbo, Bao,Nirong, and Zhao,Jianning

Abstract

Zhenheng Wang,* Kaiwen Xue,* Maosheng Bai, Zhantao Deng, Jingjing Gan, Gang Zhou, Hongbo Qian,* Nirong Bao, Jianning Zhao Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, People’s Republic of China *These authors contributed equally to this work Abstract: Wear particle-induced inflammatory osteolysis is the primary cause of aseptic loosening, which is the most common reason for total hip arthroplasty (THA) failure in the med- and long term. Recent studies have suggested an important role of gut microbiota (GM) in modulating the host metabolism and immune system, leading to alterations in bone mass. Probiotic bacteria administered in adequate amounts can alter the composition of GM and confer health benefits to the host. Given the inflammatory osteolysis that occurs in wear debris-induced prosthesis loosening, we examined whether the probiotic Lactobacillus casei could reduce osteolysis in a mouse calvarial resorption model. In this study, L. casei markedly protected mice from CoCrMo particles (CoPs)-induced osteolysis. Osteoclast gene markers and the number of osteoclasts were significantly decreased in L. casei-treated mice. Probiotic treatment decreased the M1-like macrophage phenotype indicated by downregulation of tumor necrosis factor α (TNF-α), interleukin (IL)-6 and inducible nitric oxide synthase (iNOS) and increased the M2-like macrophage phenotype indicated by upregulation of IL-4, IL-10 and arginase. Collectively, these results indicated that the L. casei treatment modulated the immune status and suppressed wear particle-induced osteolysis in vivo. Thus, probiotic treatment may represent a potential preventive and therapeutic approach to reduced wear debris-induced osteolysis. Keywords: wear particles, gut microbiota, nanotoxicity, macrophage polarization, inflammatory cytokines, aseptic loosening

Published
2017

39. The metal nanoparticle-induced inflammatory response is regulated by SIRT1 through NF-κB deacetylation in aseptic loosening

Author

Deng,Zhantao, Jin,Jiewen, Wang,Zhenheng, Wang,Yong, Gao,Qian, Zhao,Jianning, Deng,Zhantao, Jin,Jiewen, Wang,Zhenheng, Wang,Yong, Gao,Qian, and Zhao,Jianning

Abstract

Zhantao Deng,1–3,* Jiewen Jin,2,3,* Zhenheng Wang,1 Yong Wang,2,3 Qian Gao,2,3 Jianning Zhao1 1Department of Orthopedics, Jinling Hospital, School of Medicine, Nanjing University, 2Center for Translational Medicine, Nanjing University Medical School, 3Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, Jiangsu, People’s Republic of China *These authors contributed equally to this work Abstract: Aseptic loosening is the most common cause of total hip arthroplasty (THA) failure, and osteolysis induced by wear particles plays a major role in aseptic loosening. Various pathways in multiple cell types contribute to the pathogenesis of osteolysis, but the role of Sirtuin 1 (SIRT1), which can regulate inflammatory responses through its deacetylation, has never been investigated. We hypothesized that the downregulation of SIRT1 in macrophages induced by metal nanoparticles was one of the reasons for osteolysis in THA failure. In this study, the expression of SIRT1 was examined in macrophages stimulated with metal nanoparticles from materials used in prosthetics and in specimens from patients suffering from aseptic loosening. To address whether SIRT1 downregulation triggers these inflammatory responses, the effects of the SIRT1 activator resveratrol on the expression of inflammatory cytokines in metal nanoparticle-stimulated macrophages were tested. The results demonstrated that SIRT1 expression was significantly downregulated in metal nanoparticle-stimulated macrophages and clinical specimens of prosthesis loosening. Pharmacological activation of SIRT1 dramatically reduced the particle-induced expression of inflammatory cytokines in vitro and osteolysis in vivo. Furthermore, SIRT1 regulated particle-induced inflammatory responses through nuclear factor kappa B (NF-κB) acetylation. Thus, the results of this study suggest that SIRT1 plays a key role in metal nanoparticle-induced inflammatory responses and th

Published
2017

40. A Nonlinear System Stable Control Design by Firefly Algorithm and Extreme Learning Machine

Author

Wang Zhenheng, Jiang Dan, Wenxin Yu, Wang Junnian, Bo Xianglei, Mu Li, and Juan Chen

Subjects
Controllability, History, Nonlinear system, Series (mathematics), Iterative method, Control theory, Computer science, Firefly algorithm, Construct (python library), Fixed point, Computer Science Applications, Education, Extreme learning machine
Abstract

In this paper, we introduce a novel iterative method for finding a series of fixed point and design a steady controllability approach for nonlinear systems by using Firefly algorithm and ELM. First, we construct a fixed-point search model, but it is just only looking for a fixed point. Because of the need of non-linear dynamic systems, we need to find a series of fixed point under certain circumstances. Then, we apply the Firefly Algorithm and ELM to design a steady controllability approach. Finally, we have an example to verify the method we have proposed. Through the method, we get a series of fixed point, which make dynamic Nonlinear Systems or nonlinear circuit is under a relatively stable state.

Published
2018
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47. Byakangelicol suppresses TiPs-stimulated osteoclastogenesis and bone destruction via COX-2/NF-κB signaling pathway

Author

Wang, Zhidong, Tao, Huaqiang, Chu, Miao, Yu, Lei, Yang, Peng, Wang, Qiufei, Lu, Jun, Yang, Huilin, Wang, Zhenheng, Zhang, Hailin, and Geng, Dechun

Abstract

Aseptic loosening (AL) is considered a significant cause of prosthesis revision after arthroplasty and a crucial factor in the longevity of an artificial joint prosthesis. The development of AL is primarily attributed to a series of biological reactions, such as peri-prosthetic osteolysis (PPO) induced by wear particles around the prosthesis. Chronic inflammation of the peri-prosthetic border tissue and hyperactivation of osteoclasts are key factors in this process, which are induced by metallic wear particles like Ti particles (TiPs). In our in vitrostudy, we observed that TiPs significantly enhanced the expression of inflammation-related genes, including COX-2, IL-1β and IL-6. Through screening a traditional Chinese medicine database, we identified byakangelicol, a traditional Chinese medicine molecule that targets COX-2. Our results demonstrated that byakangelicol effectively inhibited TiPs-stimulated osteoclast activation. Mechanistically, we found that byakangelicol suppressed the expression of COX-2 and related pro-inflammatory factors by modulating macrophage polarization status and NF-κB signaling pathway. The in vivoresults also demonstrated that byakangelicol effectively inhibited the expression of inflammation-related factors, thereby significantly alleviating TiPs-induced cranial osteolysis. These findings suggested that byakangelicol could potentially be a promising therapeutic approach for preventing PPO.

Published
2024
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50. Autophagy mediated CoCrMo particle-induced peri-implant osteolysis by promoting osteoblast apoptosis

Author

Wang, Zhenheng, primary, Liu, Naicheng, additional, Liu, Kang, additional, Zhou, Gang, additional, Gan, Jingjing, additional, Wang, Zhenzhen, additional, Shi, Tongguo, additional, He, Wei, additional, Wang, Lintao, additional, Guo, Ting, additional, Bao, Nirong, additional, Wang, Rui, additional, Huang, Zhen, additional, Chen, Jiangning, additional, Dong, Lei, additional, Zhao, Jianning, additional, and Zhang, Junfeng, additional

Published
2015
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