Applied Mechanics and Materials Vols. 217-219

Abstract: With a wide range of applications of vibration technology in mechanical engineering, the vibratory mixing has been a hot topic and one of concrete mixing mechanical’s development directions. The author, in this text, introduces the methods of the vibratory mixing, and gives the comparison and evaluation of the existent vibratory mixing methods.

Abstract: The gear fault diagnosis system is proposed based on harmonic wavelet packet transform (WPT) and BP neural network techniques. The WPT is a well-known signal processing technique for fault detection and identification in mechanical system，In the preprocessing of vibration signals, WPT coefficients are used for evaluating their energy and treated as the features to distinguish the fault conditions.In the experimental work, the harmonic wavelets are used as mother wavelets to build and perform the proposed WPT technique. The experimental results showed that the proposed system achieved an average classification accuracy of over 95% for various gear working conditions.

Abstract: In the drilling process for deep hole, the continuous chips often jam up due to the difficulty of chip removal, and the chips cause problems such as tool breakage and deterioration of the surface quality. The measures of chip removal must be adopted, especially for small diameter deep hole, the chip removal space is limited and thickness and length of chips can directly influence the chip removal, the chip size are required as a precondition for chip removal. In this study, the feed is periodically varied in numerical control machine, and the length of chip can be controlled, then the chip breaking is realized with no addition special chip breaking mechanism, which combines with negative pressure suction mechanism for chips, and solves the problem of chip breaking and removal.

Abstract: Considering the difficulty of diagnosis signal de-noising and feature extraction problems, according to the characteristics of periodicity and shock attenuation respond of mechanical fault vibration signals, a method of improved sequential decomposition algorithm is proposed, it transforms an initial time series into a group of two-dimensional time series, prominent time series partial information, time series decomposition is reversible, can be used for filtering and feature extraction of time signal. Through the simulation and experiments, the validity of method for highlighting partial feature information of the signal is verified, helping to extract weak fault information in strong background noise environment.

Abstract: A/C axes bi-rotary CNC universal milling is the core components of five-axis linkage machine tools, the geometric error will impact on machining accuracy directly. The geometric error and its causes of A/C axes bi-notary milling head are studied, and laid the foundation for the bi-notary milling head precision testing and accuracy improvement. Brief introduction to the composition and working principle of the Renishaw laser interferometer, and put forward by using of Renishaw laser interferometer to detect the A axis and C axis position error.

Abstract: This paper selected the factors as the coal mining depth, coal seam thickness, the dips, partings, main roof of the top coal caving as indicators, used the categorical data of the steep seam from domestic mining area as training samples for training. Based on one to one classification of SVM, the top coal caving ability prediction model was established. The example results show that the model prediction method is feasible, the prediction results have very high accuracy and reliability, and has certain promotional value.

Abstract: Five-axis flank milling is an important machining technique, especially in machining of complex parts. Tool posture vector can change easily using two axes of rotation to achieve optimum cutting conditions. However, the tool posture vector may change beyond the interpolation plane. This will result in overcut or undercut. In this paper, an adaptive interpolation algorithm of tool posture vector is proposed. In the proposed algorithm, the commanded feedrate for linear axis is kept constant for most time and adaptively adjusted to confine the chord error within a specified tolerance range during the interpolation process. The tool posture vector changes in the interpolation plane with a constant rotation degree. Simulation results from example are provided to verify the feasibility and advantages of the proposed scheme.

Abstract: A piezoelectric vibrator in ultrasonic EDM processing is designed and fabricated. The structure parameters of the vibrator have a very significant impact on the dynamic characteristics. The effect of different structural parameters on dynamic characteristics of the vibrator is analyzed by using Finite Element Method(FEM), and the modal frequency and vibration amplitude sensitivities of the vibrator to the structural parameters are investigated by modal and harmonic analysis.. According the results of the sensitivities analysis, the structural parameters which have an important impact on the working modal frequency and the vibration amplitude are achieved. The vibrator is designed and made based on the above theoretical analysis. The dynamic characteristics of the piezoelectric vibrator are tested. In the case of exciting voltage of 100V (peak-peak value), the first-order longitudinal vibration frequency (working frequency) of the vibrator is 27.36 kHz, vibration amplitude is about9.8μm, which is in compliance with the theoretically analytical results.

Abstract: The Define, Measure, Analyze, Improve, Control (DMAIC) Six Sigma strategy was designed to improve product quality and to reduce product defects. Because of its classification and feature selection capabilities, the Mahalanobis-Taguchi System is integrated in the improvement stage of DMAIC to reduce redundant testing items in the testing procedure and to optimize the economic benefit of the test flow. The important variables screened by the Reduced Model in MTS are C2, C5 and the classification accuracy rate is 99.13%. Implementation results show that atomic force microscope (AFM) inspection process reduces inspection attributes and maintains high inspection accuracy. The average AFM thickness is decreased from to . The standard deviation is reduced from 45.76 to 8.73, PCI is raised from 0.73 to 3.81, process accuracy is improved from 0.07 to 0.012, and process performance is improved from 0.67 to 3.76. Finally, this study confirmed that the new process parameters can reduce variance in the alignment membrane thickness and enhance the overall LCD chromaticity yield.

Abstract: Fault diagnosis is an important problem in the process of chemical industry and the artificial neural network is widely applied in fault diagnosis of chemical process. A hybrid algorithm combining ant colony optimization (ACO) algorithm with back-propagation (BP) algorithm, also referred to as ACO-BP algorithm, is proposed to train the neural network weights and thresholds. The basic theory and steps of ACO-BP algorithm are given, and applied in fault diagnosis of the continuous stirred-tank reactor (CSTR). Experimental results prove that ACO-BP algorithm has good fault diagnosis precision, and it can detect the fault in CSTR promptly and effectively.