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Zhang Y.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Zhang Y.,Yanshan University | Sun S.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Sun S.,Yanshan University | And 6 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

In the high speed sliding electrical contact with large current, the temperature of contact area rises quickly under the coupling action of the friction heating, the Joule heating and electric arc heating. The rising temperature seriously affects the conductivity of the components and the yield strength of materials, as well affects the contact state and lead to damage, so as to shorten the service life of the contact elements. Therefore, there is vital significance to measure the temperature accurately and investigate the temperature effect on damage of rail surface. Aiming at the problem of components damage in high speed sliding electrical contact, the transient heat effect on the contact surface was explored and its influence and regularity on the sliding components damage was obtained. A kind of real-time temperature measurement method on rail surface of high speed sliding electrical contact is proposed. Under the condition of 2.5 kA current load, based on the principle of infrared radiation non-contact temperature sensor was used to measure the rail temperature. The dynamic distribution of temperature field was obtained through the simulation analysis, further, the connection between temperature changes and the rail surface damage morphology, the damage volume was analyzed and established. Finally, the method to reduce rail damage and improve the life of components by changing the temperature field was discussed. © 2016 SPIE.


Meng Z.,Yanshan University | Meng Z.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Liang Z.,Yanshan University | Liang Z.,Guangxi Special Equipment Supervision and Inspection Institute
Jiliang Xuebao/Acta Metrologica Sinica | Year: 2015

The accurate AR model can reveal the changing state characteristics inherent in the signal, however the AR model is sensitive to the changes in the state of the system, and the multiple of dynamic source signal coupling is bound to affect the estimated results. The method of blind source separation is reconstruct mechanical vibration source signals. Then the non-stationary fault signal is decomposed into several stationary signals which suit to establish AR model. Finally, the AR model of stationary intrinsic mode function is constructed to extract the characteristics of fault vibration signal. The results of simulation and experiment are presented to verify the theory analysis. ©, 2015, Chinese Society for Measurement. All right reserved.


Wen Y.,Yanshan University | Liu S.,Yanshan University | Liu S.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Zhang Y.,Yanshan University | And 5 more authors.
Measurement: Journal of the International Measurement Confederation | Year: 2016

During the electromagnetic launching (EML) process, rail vibrations occur due to the electromagnetic force generated by an acute current. These vibrations result in a reduced launch velocity and decreased launch efficiency. To measure the vibration amplitude of a rail accurately and to analyze the internal relationships between current strength, rail material and vibrations, a small transient vibration in a strong electromagnetic field was studied in this paper. Related experiments were also performed on the test system. Fiber-optic displacement sensors were used to collect vibration data at key locations along the rail. Using virtual instrument technology, a software platform was designed that displayed the vibration waveform and analyzed the time, frequency domain and other parameters. We collected data on the vibration response and the modal parameters of the rail and determined the natural frequencies of the electromagnetic launch system by performing a modal analysis of its vibrations and dynamic responses that combined experimental and theoretical methods. Methods of optimizing the structure's vibration and dynamic response and of assessing the damage to it could be studied further on the basis of the results described in this paper. © 2016 Elsevier Ltd. All rights reserved.


Zhang Y.-Y.,Yanshan University | Zhang Y.-Y.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Yan M.-S.,Yanshan University | Yan M.-S.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | And 4 more authors.
Jiliang Xuebao/Acta Metrologica Sinica | Year: 2015

A method of non-contact on-line measurement for testing roller wears based on the measuring principle of laser self-mixing interference was put forward. The principle and project of roller wear testing is investigated. A self-mixing interference displacement detector was used for multi-point measurement and translating the roll wear quantity into micro displacement to get the wearing capacity of the roll. In signal processing, the phase unwrapping method is used to extract phase and the interpolation method is used to improve the test resolution and accuracy. The result of the experiment shows that the resolution of this measuring method is refined to micron. ©, 2015, Chinese Society for Measurement. All right reserved.


Meng Z.,Yanshan University | Meng Z.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Li S.-S.,Yanshan University | Li S.-S.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | And 2 more authors.
Jiliang Xuebao/Acta Metrologica Sinica | Year: 2015

A method based on LMD (Local Mean Decomposition) and local time-frequency entropy in rotating machinery fault diagnosis is proposed. Aiming at bearing, the vibrating signal is decomposed into PFs (Product Functions) by LMD, and then Hilbert transformation is applied to every PF to get time-frequency distribution. The local time-frequency entropy is introduced to study the energy in time-frequency distribution quantitatively. In detail, according to the spectrum characteristic of bearing fault, the whole time-frequency plane is divided into some segments, and whose entropies are calculated to extract the fault feature of the bearing. By the method of fault feature extraction based on local time-frequency entropy, differences among the segments could be reflected in large. Also the computational complexity is reduced at the same time. The results of simulation and experiment are presented to verify the theory analysis. ©, 2015, Chinese Society for Measurement. All right reserved.


Pan Z.,Yanshan University | Pan Z.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Wang Y.,Yanshan University | Wang Y.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | And 3 more authors.
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | Year: 2013

In this paper, adopting the micellar fluorometry sensitization method, taking sodium dodecyl sulfate, a kind of surfactant, as the fluorescence sensitizing reagent, the fluorescence emission spectra of different oil samples in the micellar solution environment are measured. The concentration of the oil sample in the micellar solution has good linear relationship with its fluorescence peak intensity in a certain range, which can be used to solve the problem of the low water solubility of petroleum substances and the difficulty in accurately determining their concentration. The mixed solution sample set with known concentration is obtained by mixing the micellar solutions of diesel and kerosene samples in the linear range. The fluorescence spectra of different samples are measured and a three dimensional data matrix is constructed by measuring the fluorescence spectra of different samples. The parallel factor analysis method is adopted to accurately estimate the concentrations of diesel and kerosene of the samples in the prediction set through choosing appropriate factor. Experiment results indicate that the parallel factor (PARAFAC) analysis method can overcome the influences of the similarity and overlap of the fluorescence spectra of various petroleum substances in a certain extent and realize the overall qualitative and quantitative measurement of the petroleum substances in mixed micelles.


Zhang Y.-Y.,Yanshan University | Zhang Y.-Y.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Zhou H.,Yanshan University | Zhou H.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | And 2 more authors.
Wuli Xuebao/Acta Physica Sinica | Year: 2015

In order to achieve precise extraction of the phase with a light feedback mechanism, based on empirical mode decomposition (EMD) algorithm, an adaptive phase extraction method is proposed in this paper. First of all, the EMD algorithm is acted on the self-mixing interference (SMI) mixed noise signals, then using the principle of HHT to extract the instantaneous phase information in the SMI signal in time and retrieve the true phase of the object from the wrapped phase. In this paper, the phase extraction algorithm based on EMD are simulated under different optical feedback conditions. Finally, an experimental setup based on SMI has been given for demonstration. Experimental results show that this method is correct in principle and can be used in the precise extraction and its maximum error is less than 1.6 rad. The simulation results are consistent with the experimental data, which show the effectiveness of the proposed method. ©, 2015, Institute of Physics, Chinese Academy of Sciences. All right reserved.


Meng Z.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Meng Z.,National Engineering Research Center for Eqpt & Technology of Cold Rolling Strip | Ji Y.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Yan X.-L.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province
Jiliang Xuebao/Acta Metrologica Sinica | Year: 2016

A comprehensive rolling bearing fault diagnosis method combining differential-based empirical mode decomposition (DEMD) with fuzzy entropy and support vector machine (SVM) is proposed. Firstly, mechanical vibration signal is decomposed with differential-based empirical mode decomposition (DEMD) to obtain a certain number of intrinsic mode functions (IMFs) that have physical meaning. With a mutual relationship rule, the IMF components that have largest correlation coefficients with the original signal are sifted out. The fuzzy entropies of these IMFs are calculated and use as eigenvectors of fault signals, then the eigenvectors are put into SVM to identify the state of the rolling bearing. Compared with the method based on empirical mode decomposition (EMD) combined with fuzzy entropy and SVM, the experimental results show that the method of mechanical failure signals can accurately identify classification effectively. © 2016, Acta Metrologica Sinica Press. All right reserved.


Sun J.,Yanshan University | Li Y.,Yanshan University | Wen J.,Key Laboratory of Measurement Technology and Instrumentation of HeBei Province | Yan S.,Yanshan University
Neurocomputing | Year: 2015

This paper proposes the use of density-based spatial clustering of application with noise (DBSCAN) and the Hough transform to estimate the mixing matrix in underdetermined blind source separation. First, phase-angle-based single source time-frequency point detection is employed to improve signal sparsity. To overcome the limitation of the K-means clustering algorithm, which requires prior knowledge of the number of sources, the DBSCAN classification algorithm is adopted to automatically estimate the number of sources and then further estimate the mixing matrix. The Hough transform is employed to modify the cluster center in order to enhance the estimation accuracy of the mixing matrix. Simulation results show that the proposed approach can effectively estimate the number of sources and the mixing matrix with high accuracy. The proposed approach performs better than the K-means method and the DBSCAN algorithm alone. © 2015 Elsevier B.V.


Meng Z.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province | Meng Z.,National Engineering Research Center for Equipment & Technology of Cold Rolling Strip | Yan X.-L.,Key Laboratory of Measurement Technology and Instrumentation of Hebei Province
Jiliang Xuebao/Acta Metrologica Sinica | Year: 2015

Based on the differential-based empirical mode decomposition (DEMD) and hidden Markov model (HMM), a new method for rotating machinery fault diagnosis is proposed. The method is applied to rolling bearing fault diagnosis. First of all, fault signals are decomposed by DEMD, the instantaneous energy distribution of each signal is extracted to form the fault feature vectors, and then input the feature vectors into the HMM classifier for malfunction recognition, the maximum likelihood probability which is output by HMM classifier is in the fault state. Finally, different fault types are recognized. A practical fault signal of a rolling bearing with corrosive pitting is applied to test the method. Experimental result showed that the method of DEMD-HMM is superior to the method of EMD-HMM and can identify the rolling bearing fault accurately and effectively. © 2015, Chinese Society for Measurement. All right reserved.

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