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Shijiazhuang, China

Shijiazhuang Tiedao University is a university in Hebei, China under the provincial government. The campus is located at No.17 East Bei'erhuan Road Qiaodong district Shijiazhaung City Hebei Province P.O: 050041Shijiazhuang Tiedao University is a prestigious university of applied engineering. It excels in the fields of humanities, science, economics and management. S.T.D.U. is under the supervision of central and local governments, mainly of Hebei Province. S.T.D.U. was founded in 1950, originally named Shijiazhuang Railway Institute. It was one of the key railway engineering universities in Hebei Province as well as in the whole country. In 2010, the university was renamed as Shijiazhuang Tiedao University.Currently, the university has a faculty staff of 1,414, of which there are more than 844 full-time teachers and scientific researchers, including 193 professors and 414 vice professors of equal qualifications, 300 Doctor and Master tutors, 23792 full-time students, including 10,070 college students from the Si-Fang Campus and 1,067 graduate students. S.T.D.U. has 2 National Teaching Groups, 1 Innovation Group named by the Ministry of Education, 1 Cheung Kong Scholar, 1 winner of National Science Fund for Distinguished Young Scholars, 1 National Outstanding Professional and Technical Personnel winner, 1 Nationally Known Teacher; 2 Yanzhao Scholars; 2 Candidates of Academia of Hebei Province; 2 Candidates of Hundred, Thousand and Ten thousand Talents Program; and more than 10 "National Model Teachers" and "Teachers of Exemplary Moral Conduct", 50 experts who enjoy the Subsidy Award for Experts with Outstanding Contribution to Hebei Province issued by the State Council. In addition, S.T.D.U. has invited more than 120 academic and reputable scholars as part-time professors.S.T.D.U. has been enrolling students from all over the country who are qualified for first-batch enrollment based on their performance in the College Entrance Examination. Now it consists of 46 undergraduate majors, 10 master degree disciplines, 44 postgraduate majors, 5 provincial key disciplines, 4 provincial or ministerial key engineering laboratory centers. Our University has 15 institutional departments, such as the Schools of Civil Engineering, School of Traffic and Transportation Engineering, School of Mechanical Engineering, School of Economics, School of Materials Science and Engineering, School of Computer Technology, School of Electronics and Information, School of Mechanics, Department of Mathematics & Physics, etc. It also possesses 25 research centers, such as Research Centers of Transportation, of Health Monitoring and Control of Building Structural and of Traffic Safety Engineering and others.In 2003, S.T.D.U. started the cooperative PhD program granted by the Ministry of Education of China. In 2009, STDU was selected as an intellectual construction station for cultivating future PhDs by the Academic Degree Commission of the State Council. In 2011 S.T.D.U. was selected to participate in the "National Excellent Engineers" program by the Ministry of Education. Wikipedia.


Li H.,Shijiazhuang Railway Institute
Key Engineering Materials | Year: 2011

Gearbox vibrations are random cyclostationary signals which are a combination of periodic and random processes due to the machine's rotation cycle and interaction with the real world. The combinations of such components are best considered as cyclostationary. This paper discusses which second order cyclostationary statistics should be used for fault diagnosis of gear crack. The second order cyclostationary statistical methods are firstly introduced and then applied to fault diagnosis of gear crack. This approach is capable of completely extracting the characteristic fault frequencies related to the defect. Experiment results show that the second order cyclostationary statistics is powerful and effective in feature extracting and fault detecting for gearbox. The experimental result shows that the second order cyclostationary statistics can effectively diagnosis gear localized crack fault. © (2011) Trans Tech Publications.


Wang L.,Beijing Institute of Technology | Wang L.,Shijiazhuang Railway Institute | Cui L.,Beijing Institute of Technology
Mathematical and Computer Modelling | Year: 2011

Some states in the aggregated semi-Markov repairable system with history-dependent up and down states are changeable in the sense that whether those physical states are up and down depends on the immediately preceding state of the system evolution process. Two reliability indices of the system, the frequency of failures and the time to the first system failure are given. The Laplace-Stieltjes transforms of several time distributions in a cycle, such as the up and down time, the total time the system is in the up, down and changeable states, the length of a single sojourn in the up, down and changeable states are derived. The means of them are also presented. Markov renewal theory, transform and matrix methods are employed for getting these performance measures. A numerical example is given to illustrate the results in the paper. © 2011.


Li H.,Shijiazhuang Railway Institute
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2010

The continuous wavelet transform enables one to look at the evolution in the time scale joint representation plane. This advantage makes it very suitable for the detection of singularity generated by localized defects in mechanical system. The Fourier spectrum of complex Morlet wavelet is real, which the Fourier spectrum has no complex phase, the complex Morlet wavelet does not affect the phase of a signal in complex domain. This gives a desirable ability to detect the singularity characteristic of a signal precisely. In this study, the complex Morlet wavelet amplitude and phase map are used in conjunction to detect and diagnose the bearing fault. The complex Morlet wavelet amplitude and phase map are found to show distinctive signatures in the presence of bearing inner race or outer race damage. The experimental results show that the Morlet wavelet amplitude and phase map can extract the transients from strong noise signals and can effectively diagnose the faults of bearing. © 2010 IEEE.


Liu Q.-K.,Shijiazhuang Railway Institute
Gongcheng Lixue/Engineering Mechanics | Year: 2010

Our country has a vast territory, and wind circumstance is very complicated. With the development of High Speed Passenger Lines and speed up of trains, the security of train operation in strong wind is becoming serious and remarkable, and it is very important and necessary to establish an effective system to prevent wind induced accidents and ensure safety of train operation under strong winds. In this paper, it is indicate that the system consists of software measures and hardware measures. For software measures (operation regulation), the methods to get a regulation wind velocity were analyzed, the measurement and forecast procedures of the wind velocity along railway were indicated, the necessary wind tunnel experiments and field observation were analyzed. For hardware measures, experiments and setting procedures of a wind barrier were indicated; the optimum design procedure of a train aerodynamic shape and route selection of railway were pointed out. At last, the whole procedure to establish the system and necessary experiment work were shown by a flowchart.


Li H.,Shijiazhuang Railway Institute
Advanced Materials Research | Year: 2012

A new approach to fault diagnosis of gear wear based on Local mean decomposition (LMD) is proposed. Local mean decomposition can adaptively decomposes the vibration signal into a series of product functions (PFs), which is the product of an envelope signal and a frequency modulated signal. LMD is capable of revealing interesting feature embedded in the signal. The experimental examples are conducted to evaluate the effectiveness of the proposed approach. The experimental results provide strong evidence that the performance of the approach based on local mean decomposition is better to extract the fault characteristics of the faulty gear and can effectively diagnose the gear wear fault. © (2012) Trans Tech Publications, Switzerland.

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