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Search Results: 1 - 10 of 120076 matches for " Huaqing Wang "
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A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery
Huaqing Wang,Peng Chen
Sensors , 2009, DOI: 10.3390/s90402415
Abstract: This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to.
Highly Efficient Method for Preparing Homogeneous and Stable Colloids Containing Graphene Oxide
Yu Wei,Xie Huaqing,Wang Xinwei,Wang Xiaoping
Nanoscale Research Letters , 2011,
Abstract: Phase transfer method has been developed for preparing homogeneous and stable graphene oxide colloids. Graphene oxide nanosheets (GONs) were successfully transferred from water to n-octane after modification by oleylamine. Corrugation and scrolling exist dominantly in the modified GONs. GONs were single layered with the maximum solubility in n-octane up to 3.82 mg mL-1. Oleylamine molecules chemically attach onto the GONs. Compared with traditional strategies, the phase transfer method has the features of simplicity and high efficiency.
The Application of Hadoop in Natural Risk Prevention and Control of Rural Microcredit  [PDF]
Huaqing Mao, Li Zhu
American Journal of Industrial and Business Management (AJIBM) , 2015, DOI: 10.4236/ajibm.2015.53011
Abstract: Rural microcredit means that the loan institutions extend the small amount of loans to the farmers. The purpose of rural microcredit is to meet the increasing needs of agriculture, animal husbandry, aquaculture, and the other business activities associated with the rural economic development. However, the rural microcredit is currently facing severe problems, such as operation risk, business risk and natural risk. Of those risks, the natural risk of rural microcredit has the most different forms and complex relationships, and the effective coping strategies lack of controllability. In the event that we can’t control and make up the losses from natural risks, it will cause the rural incomes and productions stepping down; and there is no way to get any compensation from the other capital, and this will cause the farmers can’t pay the principal and interest. As a result, natural risk prevention and control become a very important issue in rural microcredit. This paper analyzed the original cause of formation and characteristic of natural risk, and discussed how to predict the natural risk in rural microcredit. Finally, we gave the result and performance evaluation, and provided various methods to defend against the natural risk.
Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR
Lixin Gao,Zhiqiang Ren,Wenliang Tang,Huaqing Wang,Peng Chen
Sensors , 2010, DOI: 10.3390/s100504602
Abstract: Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis.
Roller Bearing Fault Diagnosis Based on Nonlinear Redundant Lifting Wavelet Packet Analysis
Lixin Gao,Zijing Yang,Ligang Cai,Huaqing Wang,Peng Chen
Sensors , 2011, DOI: 10.3390/s110100260
Abstract: A nonlinear redundant lifting wavelet packet algorithm was put forward in this study. For the node signals to be decomposed in different layers, predicting operators and updating operators with different orders of vanishing moments were chosen to take norm ?of the scale coefficient and wavelet coefficient acquired from decomposition, the predicting operator and updating operator corresponding to the minimal norm value were used as the optimal operators to match the information characteristics of a node. With the problems of frequency alias and band interlacing in the analysis of redundant lifting wavelet packet being investigated, an improved algorithm for decomposition and node single-branch reconstruction was put forward. The normalized energy of the bottommost decomposition node coefficient was calculated, and the node signals with the maximal energy were extracted for demodulation. The roller bearing faults were detected successfully with the improved analysis on nonlinear redundant lifting wavelet packet being applied to the fault diagnosis of the roller bearings of the finishing mills in a plant. This application proved the validity and practicality of this method.
Adaptive Redundant Lifting Wavelet Transform Based on Fitting for Fault Feature Extraction of Roller Bearings
Zijing Yang,Ligang Cai,Lixin Gao,Huaqing Wang
Sensors , 2012, DOI: 10.3390/s120404381
Abstract: A least square method based on data fitting is proposed to construct a new lifting wavelet, together with the nonlinear idea and redundant algorithm, the adaptive redundant lifting transform based on fitting is firstly stated in this paper. By variable combination selections of basis function, sample number and dimension of basis function, a total of nine wavelets with different characteristics are constructed, which are respectively adopted to perform redundant lifting wavelet transforms on low-frequency approximate signals at each layer. Then the normalized lP norms of the new node-signal obtained through decomposition are calculated to adaptively determine the optimal wavelet for the decomposed approximate signal. Next, the original signal is taken for subsection power spectrum analysis to choose the node-signal for single branch reconstruction and demodulation. Experiment signals and engineering signals are respectively used to verify the above method and the results show that bearing faults can be diagnosed more effectively by the method presented here than by both spectrum analysis and demodulation analysis. Meanwhile, compared with the symmetrical wavelets constructed with Lagrange interpolation algorithm, the asymmetrical wavelets constructed based on data fitting are more suitable in feature extraction of fault signal of roller bearings.
Application of Composite Dictionary Multi-Atom Matching in Gear Fault Diagnosis
Lingli Cui,Chenhui Kang,Huaqing Wang,Peng Chen
Sensors , 2011, DOI: 10.3390/s110605981
Abstract: The sparse decomposition based on matching pursuit is an adaptive sparse expression method for signals. This paper proposes an idea concerning a composite dictionary multi-atom matching decomposition and reconstruction algorithm, and the introduction of threshold de-noising in the reconstruction algorithm. Based on the structural characteristics of gear fault signals, a composite dictionary combining the impulse time-frequency dictionary and the Fourier dictionary was constituted, and a genetic algorithm was applied to search for the best matching atom. The analysis results of gear fault simulation signals indicated the effectiveness of the hard threshold, and the impulse or harmonic characteristic components could be separately extracted. Meanwhile, the robustness of the composite dictionary multi-atom matching algorithm at different noise levels was investigated. Aiming at the effects of data lengths on the calculation efficiency of the algorithm, an improved segmented decomposition and reconstruction algorithm was proposed, and the calculation efficiency of the decomposition algorithm was significantly enhanced. In addition it is shown that the multi-atom matching algorithm was superior to the single-atom matching algorithm in both calculation efficiency and algorithm robustness. Finally, the above algorithm was applied to gear fault engineering signals, and achieved good results.
Up-regulation and subcellular localization of hnRNP A2/B1 in the development of hepatocellular carcinoma
Huaqing Cui, Feng Wu, Yanling Sun, Guocai Fan, Qingming Wang
BMC Cancer , 2010, DOI: 10.1186/1471-2407-10-356
Abstract: Recombinant scFv N14 antibody was expressed as an active antibody. Using this antibody with a combination of immunological and proteomic approaches, we identified the antigen of scFv N14 antibody as the heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNP A2/B1). The expression of hnRNP A2/B1 in HCC cells was then investigated by semi-quantitative RT-PCR and immunohistochemistry.We found that the up-regulation of hnRNP A2/B1 was measured at both transcriptional and translational levels in rat HCC cells but not in rat hepatic cells. We also found that in various human hepatic tissues, hnRNP A2/B1 was highly expressed in both human hepatitis virus positive liver tissues and human HCC tissues but not in normal liver tissues. Interestingly, we observed that the localization of hnRNP A2/B1 in HCC cells was altered during the development of HCC. In human hepatitis virus infected tissues hnRNP A2/B1 resides exclusively in the nuclei of hepatocytes. However, when the HCC progressed from a well differentiated to a poorly differentiated stage, hnRNP A2/B1 was increasingly localized in the cytoplasm. In contrast, the HCC tissues with hnRNP A2/B1 highly expressed in the nucleus decreased.This work is the first to show that hnRNP A2/B1 is the antigen specifically recognized by the scFv N14 antibody in HCC cells. The over-expression of hnRNP A2/B1 was confirmed in cultured human and rat HCC cell lines, human virus related hepatitis liver tissues and human HCC tissues. The increased localization of hnRNP A2/B1 in the cytoplasm of HCC cells was revealed during the dedifferentiation of hepatocellular carcinoma. Therefore, we suggest that the increased expression and cytoplasmic localization of hnRNP A2/B1 can be used as a diagnostic biomarker to assess the risk of human liver cancer.Hepatocellular carcinoma (HCC) is one of the world's most common types of cancer, and an estimated 500,000 to 1,000,000 patients die of HCC each year [1]. HCC diagnosis is a multistage process, which inc
Population Dynamics of Citrus Rhizosphere Microorganisms and Rhizosphere Effect

Zuo Huaqing,Wang Zishun,

中国生态农业学报 , 1995,
Abstract: The primary composition of citrus rhizosphere microorganisms is bacteria,whose number reaches up to 76871×107 per gram dry soil,nest is fungi with 17549 numbers per gram dry soil,the least is actinomyces,the number is 12462 per gram dry soil.Those quantity are 67.6,12.4 and 26.9 times higher than those in no-root soils in the citrus field,respectively. The rhizosphere effect is very remarkable.Rhizosphere bacteria tends to be more abundant in Citrus ushiu mare soil.Quantity of those rhizosphere microorganisms are influenced by soil physical and chemical characters and changing with citrus variety stock as well as season. There are also close relation between disease enduring and susceptibility of citrus root and root stem to some diseases with the quantity,type and distribution of beneficial and harmful rhizosphere microorganisms.
Bortezomib plus rituximab versus rituximab in patients with high-risk, relapsed, rituximab-na ve or rituximab-sensitive follicular lymphoma: subgroup analysis of a randomized phase 3 trial
Zinzani Pier,Khuageva Nuriet K,Wang Huaqing,Garicochea Bernardo
Journal of Hematology & Oncology , 2012, DOI: 10.1186/1756-8722-5-67
Abstract: Background The randomized phase 3 LYM3001 trial in relapsed follicular lymphoma (FL) demonstrated higher overall (ORR) and complete response (CR) rates and prolonged progression-free survival (PFS) with bortezomib-rituximab versus rituximab. We report findings in high-risk patients (FL International Prognostic Index [FLIPI] score ≥3, and high tumor burden by modified Groupe d’Etude des Lymphomas Folliculaires [GELF] criteria). Methods Patients aged ≥18 years with grade 1/2 FL, ≥1 measurable lesion, and documented relapse or progression following prior therapy, rituximab-na ve or rituximab-sensitive, were enrolled at 164 centers in 29 countries across Europe, the Americas, and Asia-Pacific. Patients were randomized (1:1) to five 5-week cycles of bortezomib-rituximab (bortezomib 1.6 mg/m2, days 1, 8, 15, and 22, all cycles; rituximab 375 mg/m2, days 1, 8, 15, and 22, cycle 1, and day 1, cycles 2–5; N=336) or rituximab alone (N=340). Randomization was stratified by FLIPI score, prior rituximab, time since last dose of anti-lymphoma therapy, and geographical region. The primary endpoint of the study was PFS. Results 103 bortezomib-rituximab and 98 rituximab patients had high-risk FL. The ORR was 59% versus 37% (p=0.002), the CR/CRu rate was 13% versus 6% (p=0.145), and the durable response rate was 45% versus 26% (p=0.008) with bortezomib-rituximab versus rituximab. Median PFS was 9.5 versus 6.7 months (hazard ratio [HR] 0.667, p=0.012) with bortezomib-rituximab versus rituximab; median time to progression was 10.9 versus 6.8 months (HR 0.656, p=0.009); median time to next anti-lymphoma treatment was 14.8 versus 9.1 months (HR 0.762, p=0.103); and the 1-year Overall Survival rate was 83.1% versus 76.6%. Overall, 51% of bortezomib-rituximab and 32% of rituximab patients reported grade ≥3 adverse events, including neutropenia (18%, 6%), anemia (4%, 5%), diarrhea (8%, 0%), thrombocytopenia (5%, 2%), and sensory neuropathy (1%, 0%). Conclusions High-risk FL patients treated with bortezomib-rituximab had significantly higher ORR and longer PFS than patients receiving rituximab alone, with greater clinical benefit than in the overall study population; additional toxicity was acceptable and did not affect treatment feasibility. Trial registration The phase 3 LYM3001 trial is registered with ClinicalTrials.gov, with the identifier NCT00312845.
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