Chengdu, China
Chengdu, China

Time filter

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Liu Y.,University of Sichuan | Yin G.,University of Sichuan | Du J.,Sichuan University | Zhang Z.,Sichuan Sunny Seal Co.
Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) | Year: 2016

For the stability of gas film thickness and multistage regulation operating conditions leading to failure in dry gas seal, the dynamic characteristics of dry gas seal with spiral groove were analyzed based on Workbench. A model of axial vibration of a floating ring(static ring) was established, and the expression of axial vibration amplitude was derived. Workbench was applied to finish prestressed modal analysis and harmonic response analysis of the floating ring system under working conditions. The simulation was compared with the results of theoretical derivation. The change trend of axial vibration amplitude of the floating ring was got under the same parameters with different values, and the main and minor factors affecting the axial vibration amplitude of the floating ring were distinguished. This approach not only obtained the values of the amplitude of floating ring under different conditions flexibly, but also explained the trend of vibration from the relationship between vibration frequency and inherent frequency. © 2016, Editorial Department of Journal of Sichuan University (Engineering Science Edition). All right reserved.


Zhang E.,Southwest Jiaotong University | Fu P.,Southwest Jiaotong University | Ge Z.,Southwest Jiaotong University | Zhang Z.,Sichuan Sunny Seal Co. | Huang Z.,Sichuan Sunny Seal Co.
Sensors and Transducers | Year: 2014

For the problem of the determination of lift-off position and the measurement of end face thickness for mechanical seal more difficult, the method based on acoustic emission signal end face lift-off condition monitoring technology for mechanical seal was proposed. The electric eddy current sensor made direct measurement in the internal of mechanical seal device, and the acoustic emission sensor was fixed in the outside for indirect measurement. The acoustic emission signals were de-noised by wavelet threshold de-noising method. The representative energy features were selected by wavelet packet energy spectrum algorithm. It was established that the Radial Basis Function neural network model used for identification of the mechanical seal lift-off position, and the extracted wavelet energy features as its input. It was confirmed accurate and effective that the acoustic emission identification technology through comparing with the data detected by electric eddy current sensor. So using the acoustic emission technology realized the identification of the mechanical seal liftoff position of mechanical main shaft from inside to outside. It is convenient to be used and promotion in industrial field. © 2014 IFSA Publishing, S. L.


Zhang E.,Southwest Jiaotong University | Fu P.,Southwest Jiaotong University | Ge Z.,Southwest Jiaotong University | Zhang Z.,Sichuan Sunny Seal Co. | Zhang J.,Sichuan Sunny Seal Co.
Sensors and Transducers | Year: 2014

Since the measurement of mechanical sealing film thickness and just-lift-off time is very difficult, the sealing film condition monitoring method based on acoustic emission signal is proposed. The mechanical seal acoustic emission signal present obvious characteristics of time-varying nonlinear and pulsating. In this paper, the acoustic emission signal is used to monitor the seal end faces just-lift-off time and friction condition. The acoustic emission signal is decomposed by empirical mode decomposition into a series of intrinsic mode function with independent characteristics of different time scales and different frequency band. The acoustic emission signal only generated by end faces friction is obtained by eliminating the false intrinsic mode function components. The correlation coefficient of acoustic emission signal and Multi-scale Laplace Wavelet is calculated. It is proved that the maximum frequency (8000 Hz) of the correlation coefficient is appeared at the spindle speed of 300 rpm. And at this time (300 rpm) the end faces have just lifted off. By a set of mechanical oil seal running test, it is demonstrated that this method could accurately identify mechanical seal end faces just-lift-off time and friction condition. © 2014 IFSA Publishing, S. L.


Li X.-H.,Southwest Jiaotong University | Fu P.,Southwest Jiaotong University | Cao W.-Q.,Southwest Jiaotong University | Chen K.,Sichuan Sunny Seal Co.
Zhendong yu Chongji/Journal of Vibration and Shock | Year: 2016

Monitoring the contact state of seal-end faces would help to the early warning of the seal failure. For the problem of the difficulty in seal signal denoising, a new approach based on particle filtering with artificial neural network (ANN-PF) and least square support vector machine (LS-SVM) is presented for acoustic emission (AE) modeling. After measuring seal film thickness, variations of the AE energy during the seal startup are studied. Then, Elman ANN is used to build the dynamic state space (DSS) of the AE signal, and PF is used for signal filtering. Finally, multiple features are extracted and a classification model based on LS-SVM is constructed for state monitoring. Experimental data shows that the proposed method can detect the seal face contact effectively and non-destructively, and it has extensive industrial prospects. © 2016, Editorial Office of Journal of Vibration and Shock. All right reserved.


Zhi Z.,Sichuan Sunny Seal Co. | Xiaohui L.,Southwest Jiaotong University
Proceedings - 2014 6th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2014 | Year: 2014

Mechanical seals operates by a thin fluid film to separate the pair of seal faces. The thickness of this film must be optimized for preventing the friction of two end faces and minimizing the leakage. In this study, the fluid film is measured by eddy current and acoustic emission techniques, and the data of eddy current are used to direct the processing of acoustic emission signal. To decrease the noise, wavelet packet and kernel principal component analysis are used to extract the data features. Then cascaded decision is presented to improve the recognition rate of artificial neural network, by which the film thickness can be estimated. © 2014 IEEE.


Li X.,Southwest Jiaotong University | Fu P.,Southwest Jiaotong University | Chen K.,Sichuan Sunny Seal Co. | Lin Z.,Southwest Jiaotong University | Zhang E.,Southwest Jiaotong University
Shock and Vibration | Year: 2016

Monitoring the contact state of seal end faces would help the early warning of the seal failure. In the acoustic emission (AE) detection for mechanical seal, the main difficulty is to reduce the background noise and to classify the dispersed features. To solve these problems and achieve higher detection rates, a new approach based on genetic particle filter with autoregression (AR-GPF) and hypersphere support vector machine (HSSVM) is presented. First, AR model is used to build the dynamic state space (DSS) of the AE signal, and GPF is used for signal filtering. Then, multiple features are extracted, and a classification model based on HSSVM is constructed for state recognition. In this approach, AR-GPF is an excellent time-domain method for noise reduction, and HSSVM has advantage on those dispersed features. Finally experimental data shows that the proposed method can effectively detect the contact state of the seal end faces and has higher accuracy rates than some other existing methods. © 2016 Xiaohui Li et al.


Huang Z.P.,Sichuan Sunny Seal Co. | Zhang Z.,Sichuan Sunny Seal Co. | Zhang J.K.,Sichuan Sunny Seal Co. | Chen K.,Sichuan Sunny Seal Co. | And 2 more authors.
Advanced Materials Research | Year: 2014

A method for measuring the thickness of liquid-lubricated film of end face and detecting the friction of end face of mechanical seals has been presented in this article. Eddy current sensors installed on the inner ring embedded in the stationary ring of mechanical seals are used to measure the thickness of the liquid-lubricated film. Acoustic emission sensor placed on the stationary ring base is used to detect the friction of end face. The micro scope condition monitoring of end face is of importance to ensure mechanical seals run normally. With a set of tests, the results demonstrate that the method is effective. © (2014) Trans Tech Publications, Switzerland.


Zhang Z.,Sichuan sunny seal co. | Chen K.,Sichuan sunny seal co. | Zhang E.Q.,Southwest Jiaotong University | Fu P.,Southwest Jiaotong University
Applied Mechanics and Materials | Year: 2014

Since the measurement of mechanical seals film thickness is difficult, the condition monitoring method based on empirical mode decomposition(EMD)is proposed. EMD is a time-frequency analysis method. It is adaptive and does not need predefined decomposition basis function. The AE signal is decomposed into a series of Intrinsic mode function (IMF) with independent characteristics of different time scales and different frequency band. It is realized that the mechanical seal contact status is accurately identified through extracting the feature of correlation coefficient which is calculated between original AE signal and multi-scale Laplace wavelet. © (2014) Trans Tech Publications, Switzerland.


Li X.,Southwest Jiaotong University | Fu P.,Southwest Jiaotong University | Zhang Z.,Sichuan Sunny Seal Co.
Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) | Year: 2014

Mechanical seals is operated by a thin fluid film to separate the pair of seal faces for lubricating and sealing, so the film thickness needs to be measured. Because the current technique is not suit for industry, a method for measurement of film thickness of mechanical seals based on acoustic emission technique was presented. Through the direction of direct measurement, a detection model based on acoustic emission signal was built. First, the signal was processed by empirical mode decomposition, and kernel principal component analysis was used to optimize data features. Then, a cascaded decision model based on artificial neural network was presented to estimate the film thickness. The model has better recognition rate than a single neural network, and has a wide industrial prospect. ©, 2014, Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition). All right reserved.


Chen K.,Sichuan Sunny Seal Co. | Huang Z.,University of Sichuan | Yao J.,University of Sichuan | Zhang Z.,Sichuan Sunny Seal Co.
Paiguan Jixie Gongcheng Xuebao/Journal of Drainage and Irrigation Machinery Engineering | Year: 2013

The analytical methods for estimating pressure distribution on the end face of a dry gas seal (DGS) were reviewed, and then a novel algorithm for non-isothermal conditions was proposed in this paper based on the Whipple infinite narrow-groove theory. The Tripp function was used to get a temperature profile along the radius on the end face. The heat conductivity angle of gas was selected to be 3 times the conductivity angle of liquid based on experience. To solve the adjusted Gabriel differential functions more conveniently, a curve fitting method was applied to obtain an approximate analytical function of temperature profile T(r). The differential equations were solved by using 4th-order Rung-Kutta method. Compared with the results in literature, the pressures at groove bottom pg obtained by the present method are increased by 6.8%, 5.0%, 2.7% when the film thicknesses are 5.08, 3.05, 2.03 μm, respectively. And this result is consistent with the existing pressure distribution characteristic on a DGS end face. Compared with FEA (finite element analysis), the present novel method can easily be applied in engineering.

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