Applied Mechanics and Materials Vols. 764-765

Abstract: In this paper, hybrid weights-utility and Taguchi method is proposed to solve multi-objective optimization problems. The new method combines the Taguchi method and the weights-utility concept. The weights of the objective function and overall utility values are very important for the weights-utility, and must be set correctly in order to obtain an optimal solution. Application of this method to engineering design problems is illustrated with the aid of one case study, and the result shows that the weights-utlity method is able to handle multi-objective optimization problems, with an optimal solution which better meets the demand of multi-objective optimization problems than the utility concept does.

Abstract: Envelope analysis is a popular incipient fault identification tool for rolling element bearings (REBs) and gears. However, in some harsh conditions where more than one fault of REBs and gears exists simultaneously in a gearbox. In general, only the characteristic frequencies of the stronger vibration can be exposed clearly, and the others may be missed by conventional envelope analysis. To address this issue, an incipient faults detection scheme combining the kurtogram and independent component analysis (ICA) for gearbox faults diagnosis is proposed in this paper. In the proposed scheme, multi-channel vibrations are acquired from the gearbox synchronously at first. Subsequently, the vibration envelopes from each channel are extracted by the novel fast kurtogram algorithm. Then, the independent component analysis algorithm is utilized to separate the envelopes. As a result, the independent envelope components corresponding to different sources are obtained. Finally, the characteristic frequencies of the incipient faults of rolling element bearings and/or gears in a gearbox can be clearly exposed in envelope spectral plots. An experiment on a gearbox test rig which has both a REB fault and a gear fault is conducted to compare the conventional envelope analysis scheme and the proposed scheme. Test results show that the proposed scheme is more effective to identify the incipient faults of REBs and gears simultaneously existing in a gearbox.

Abstract: Due to shortage of energy, the meshing efficiency of gear train becomes an important factor of power system. This paper focuses on the meshing efficiency of straight spur gear pair. The analysis of gear meshing efficiency involves the involute theorem of gears, friction and lubrication, and other related issues. According to Buckingham’s research, the theoretical meshing efficiency equation of straight spur gear pair is proposed. One straight spur gear pair (15, 79) is proposed to be the example for analyzing meshing efficiencies at each rotation speed. The theoretical meshing efficiencies for the straight spur gear pair (15, 79) are between 98.36% ~ 99.79 %. Its best meshing efficiency occurs at pinion speed 600 rpm.

Abstract: The purpose of this work is to improve flow-induced noise for the centrifugal fan with quarter-wave resonator by design scheme, mockup fabrication, and experimental test. At first, the cascade theory is utilized to generate the three-dimensional fan configuration which is fabricated for performance and acoustic tests later. Next, FFT is applied to measure the noise for comparison and evaluating the effect of quarter-wave resonator. To reduce the fan noise, a set of quarter-wave resonator of this centrifugal fan are designed and fabricated on the centrifugal fan. Consequently, the flow-induced-noise reduction due to the aerodynamics is examined and discussed in details. In conclusions, a comprehensive parametric study on quarter-wave resonator is carried out and summarized for attaining a design guideline for its application on centrifugal fan. The accomplishment of this study provides a systematic scheme of noise reduction for a centrifugal fan with the addition of quarter-wave resonator design.

Abstract: This study uses a nonlinear transient finite element method (FEM) to simulate the mechanism and structural behavior of a 5.56 mm rifle’s multi-body power transmission system after being fired. Specifically, this study uses the Vallier-Heydenreich formula to calculate the chamber pressure, and uses the result as the input loading for the FEM model. The analysis in this study considers elastic deformation, joint clearance, and impact effects. The proposed simulation is capable of simultaneously obtaining the kinematic status, transient stresses, and strain history of a rifle. The results of shooting experiments verified the accuracy of the numerical model. The difference in the bolt carrier’s operation cycle between experimental and numerical data was only 1.9%, indicating that this simulation method is credible.

Abstract: This study investigates the performance of a new lead rubber damper (LRD), which is more advanced than existing lead-rubber based isolation devices. In contrast to the existing devices, multiple lead cores are installed in the LRD in order to optimize the behavior of the laminated rubber and lead. It is able to perform effectively under the application of shear force. An experiment was performed to investigate its dependency on the level of shear strain and frequency. The damping ratio, energy dissipation capacity and effective stiffness of the device were also evaluated.

Abstract: This paper presents kinematic analysis and power-flow analysis of an existing 8-speed bicycle drive hub by using the fundamental circuit method. First, a planetary gear mechanism, which consists of three basic planetary gear trains connected in series, and its clutching sequence table are introduced. Based on the fundamental circuits, six kinematic equations of the drive hub are derived. Then, the power-flow diagrams at related gears are illustrated based on the clutching sequence table, and the power-flow paths of the bicycle drive hub can be identified. The results of this study are beneficial to the development of multi-speed drive hubs for bicycles.

Abstract: Surface interaction is now one of the important engineering problems and methodologies to minimize wear can save large sums of money for repairing the machine parts. We try to minimize the number of experiment about the relations of normal load, lateral force, rotation speed, and resistance by grey theorem. Based on this, GM(1,1) model and RGM(1,1) model are constructed to predict the resistance under different controlled variables. And local grey analysis is for finding the degree of these variables affecting the value of resistance. Moreover, residual test is used to estimate the precision of the prediction. Results show that two models have good performance for prediction about 94% more accuracy. As for grey relation analysis, normal force is the most important variable to affect the resistance value. It also finds that increasing normal stress causes more friction loss of the parts. Since grey prediction has good performance in this study, we will combine Taguchi method and grey methodology to do more detail research on other tribological problems in the forth coming papers. Keywords: Tribological, Grey Theorem, Experiment Factors.

Abstract: Most of the existing methods for bearing real-time reliability evaluation employ real-time transformation of traditional reliability indices, performance degradation trajectory analysis, and performance degradation distribution, which are usually limited in terms of accuracy and applicability. A method for real-time reliability evaluation and life prediction for bearings based on normalized individual state deviation is proposed in this study. First, a self-organizing map neural network is utilized to obtain the individual state deviation of a running rolling bearing. Second, individual state deviation is normalized into a state deviation degree, which is used to formulate a modified real-time reliability model for the realization of real-time reliability evaluation and residual life prediction. The proposed method combines population information with real-time monitoring information of individual bearings, and thus avoids the negligence of the real-time transformation of the monitored individual. The errors caused by the randomness of the individual bearing operational process are also reduced. Finally, the feasibility and efficiency of the proposed method is validated by performing run-to-failure experiments on bearings.

Abstract: The traditional signal processing methods are difficult to accurately extract fault information, because mechanical fault vibration signals have non-stationary, which will cause system instability. Local mean decomposition is adaptive signal processing method. However, in the local mean decomposition of the signal, the trend of the endpoint can not be predicted which cause contaminating the entire signal sequence, the original moving average of the signal used over-smoothing treatment, resulting in fault characteristics can not accurately extract. The article introduces waveform matching to solve the original features of signals at the endpoints, using linear interpolation to get local mean and envelope function, then obtain production function PF vector through making use of the local mean decomposition. The energy entropy of PF vector take as identification input vectors. These vectors are respectively inputted BP neural networks, support vector machines, least squares support vector machines to identify faults. Experimental result show that the accuracy of least squares support vector machine with higher classification accuracy has been improved.