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Analysis of the Tire-Pavement Contact Stress Characteristics during Vehicle Maneuvering
Haiqi He,Rui Li,Qihui Yang,Jianzhong Pei,Fucheng Guo 대한토목학회 2021 KSCE Journal of Civil Engineering Vol.25 No.7
The vehicle maneuvering condition plays an important role in the analysis of the contact stress characteristics of the tire-pavement interaction. A reliable three-dimensional (3D) tire-pavement interaction model was developed to simulate the interface contact stress at static and various rolling conditions (free rolling, acceleration and braking). First, the 205-55-R16 radial tire was modeled accurately comprised of its special pattern and materials in the finite element software ABAQUS. Next, we analyzed and compared these contact stress characteristics,including the distribution of contact stress, the peak contact stress and the variation of stress with time at free rolling, acceleration and braking conditions. Results showed that under the same vehicle load and inflation pressure, the tire-pavement contact stresses at free rolling condition are always much larger than those at static loading condition. At acceleration condition, the peak contact stress occurs at the inner edge of the tire outermost ribs. At deceleration condition, the stress concentration on the tire tread is weakened with the extension of time. The peak contact stress increases with time at acceleration and braking conditions. But the peak contact stress at braking is much larger than that at acceleration condition under the same load and inflation pressure.
Haiqi Song,Nian Li,Wenjie Yang,Miaomiao Wu,Xiaoyang Liao,Yonggang Zhang 한국한의학연구원 2022 Integrative Medicine Research Vol.11 No.4
Background In traditional Chinese medicine (TCM) field, the benefits of observational studies was more significant. Whether the evidence from observational studies agreed with RCTs in the field of TCM was still unclear. Methods A meta-epidemiological study was conducted. Meta-analyses and systematic reviews including cohort studies and case-control studies of TCM were included. Ratio of odds ratio (ROR) of randomized controlled trials and observational studies were calculated individually and intercomparisons were conducted by pool analysis. Results A total of 11 studies and 30 outcome pairs were included in the pool analysis. Using results from the observational studies as the reference group, the polled ROR comparing randomized controlled trials with observational studies was 1.23 (95% confidence interval 1.05 to 1.44, and 95% prediction interval 0.90 to 1.68). The ROR by subgroup analysis were 1.15 (95% confidence interval 0.96 to 1.38; 95% prediction interval 0.95 to 1.39) and 1.12 (95% confidence interval 0.86 to 1.46; 95% prediction interval 0.51 to 2.47) for cohort studies and case-control studies, respectively. Conclusions There is difference in pooled results between randomized controlled studies and observational studies on TCM. However, the prediction interval shows the difference is small, which suggests observational studies of TCM can be included in data analysis to provide evidence for TCM. Future studies are needed to verify the above conclusion.
Hui Li,Haiqi Zheng,Liwei Tang 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.11
In the present work, cutting-force models of single-tooth and multi-teeth face-milling cutters were set up. Based on a spectrum analysis of cutting force, the vibration mechanism of a face-milling cutter of irregular pitch was investigated theoretically. The single-objective function and constraint conditions were derived. A general-purpose irregular-pitch face-milling cutter subsequently was designed and tested, and its performance was compared with that of a regular-pitch cutter. The experimental results showed that the irregular-pitch face-milling cutter not only reduces vibration and noise but also enhances surface-finish quality.
Wear Detection in Gear System Using Hilbert-Huang Transform
Hui Li,Yuping Zhang,Haiqi Zheng 대한기계학회 2006 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.20 No.11
Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of gear. The Empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the wear fault of the gear can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of the gear.
Bearing fault detection and diagnosis based on order tracking and Teager-Huang transform
Hui Li,Yuping Zhang,Haiqi Zheng 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.3
The vibration signal of the run-up or run-down process is more complex than that of the stationary process. A novel approach to fault diagnosis of roller bearing under run-up condition based on order tracking and Teager-Huang transform (THT) is presented. This method is based on order tracking, empirical mode decomposition (EMD) and Teager Kaiser energy operator (TKEO) technique. The nonstationary vibration signals are transformed from the time domain transient signal to angle domain stationary one using order tracking. EMD can adaptively decompose the vibration signal into a series of zero mean amplitude modulation-frequency modulation (AM-FM)intrinsic mode functions (IMFs). TKEO can track the instantaneous amplitude and instantaneous frequency of the AM-FM component at any instant. Experimental examples are conducted to evaluate the effectiveness of the proposed approach. The experimental results provide strong evidence that the performance of the Teager-Huang transform approach is better to that of the Hilbert-Huang transform approach for bearing fault detection and diagnosis. The Teager-Huang transform has better resolution than that of Hilbert-Huang transform. Teager-Huang transform can effectively diagnose the faults of the bearing, thus providing a viable processing tool for gearbox defect monitoring.
Hui Li,Yuping Zhang,Haiqi Zheng 대한기계학회 2009 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.23 No.10
Varying speed machinery condition detection and fault diagnosis are more difficult due to non-stationary machine dynamics and vibration. Therefore, most conventional signal processing methods based on time invariant carried out in constant time interval are frequently unable to provide meaningful results. In this paper, a study is presented to apply order cepstrum and radial basis function (RBF) artificial neural network (ANN) for gear fault detection during speedup process. This method combines computed order tracking, cepstrum analysis with ANN. First, the vibration signal during speed-up process of the gearbox is sampled at constant time increments and then is re-sampled at constant angle increments. Second, the re-sampled signals are processed by cepstrum analysis. The order cepstrum with normal, wear and crack fault are processed for feature extracting. In the end, the extracted features are used as inputs to RBF for recognition. The RBF is trained with a subset of the experimental data for known machine conditions. The ANN is tested by using the remaining set of data. The procedure is illustrated with the experimental vibration data of a gearbox. The results show the effectiveness of order cepstrum and RBF in detection and diagnosis of the gear condition.
Hui Li,Yuping Zhang,Haiqi Zheng 대한기계학회 2009 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.23 No.2
This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and fault diagnosis of roller bearings. The empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. First, the vibration signals are separated into several intrinsic mode functions (IMFs) by using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the localized fault in a roller bearing can be detected and fault patterns can be identified. The experimental results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the fault detection and diagnosis of roller bearings.
Dynamics modeling and simulation of a new nine-bar press with hybrid-driven mechanism
Hui Li,Yuping Zhang,Haiqi Zheng 대한기계학회 2008 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.22 No.12
A novel hybrid-driven mechanical press for precision drawing is presented. This new press is composed of a ninebar linkage which has two degrees of freedom determined by inputs from a dc constant speed motor and a dc servomotor. Therefore, the generalized coordinates are the angular displacement of two cranks. The kinetic energy, potential energy and generalized torques are analyzed. According to the equivalent circuit of the dc motor and the brushless servomotor, their dynamical model and position negative feedback model are developed separately. Then, a dynamical model for the hybrid-driven press is developed by using Lagrange’s formulation. The dynamical equation is then transformed into a system of first order equations. Six first order differential equations are obtained in the state variables. In the end, the fourth fourth order Runge-Kutta method, an explicit method, is chosen as the integration technique of computer simulation. Two motors’ current, two cranks’ position and two cranks’ angular velocity are treated as unknowns and the time response of the hybrid-driven press is obtained by integrating the system of first order equations through time.
Bearing fault diagnosis based on amplitude and phase map of Hermitian wavelet transform
Hui Li,Lihui Fu,Haiqi Zheng 대한기계학회 2011 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.25 No.11
The rolling element bearing characteristic frequencies contain very little energy and are usually overwhelmed by noise and higher level of structural vibrations. The continuous wavelet transform enables one to look at the evolution in the time scale joint representation plane. This makes it very suitable for the detection of singularity generated by localized defects in a mechanical system. However, most applications of the continuous wavelet transform have widely focused on the use of the Morlet wavelet transform. The complex Hermitian wavelet is constructed based on the first and the second derivatives of the Gaussian function to detect signal singularities. The Fourier spectrum of Hermitian wavelet is real, which the Fourier spectrum has no complex phase and the Hermitian wavelet does not affect the phase of a signal in complex domain. This gives the desirable ability to detect the singularity characteristic of a signal precisely. In this study, the Hermitian wavelet amplitude and phase map are used in conjunction to detect and diagnose the bearing fault. The Hermitian wavelet amplitude and phase map are found to show distinctive signatures in the presence of bearing inner race or outer race damage. The simulative and experimental results show that the Hermitian wavelet amplitude and phase map can extract the transients from strong noise signals and can effectively diagnose bearing faults.
Wear Detection in Gear System Using Hilbert-Huang Transform
Li, Hui,Zhang, Yuping,Zheng, Haiqi The Korean Society of Mechanical Engineers 2006 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.20 No.11
Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of gear. The Empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the wear fault of the gear can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of the gear.