Ying-Chun Chang

Optimization of Allocation and Noise Reduction on Multi-Noises System by Using Genetic Algorithm

An optimization of a layout plan and noise reduction on multi-noises system is considered. In this paper, a novel approach, a genetic algorithm (GA) based on the principles of natural biological evolution, is used as an optimizer. [1] By GA optimization in adjusting the locations and the required noise reduction for each piece of noisy equipment, the deviation with respect to the targeted noise value along the systems boundary line specified by EPA (Environment Protection Authority) can thus be minimized. In addition, the techniques of binary genetic algorithms (BGA), reproduction, crossover mutation and elitism are applied in GA searching. The numerical cases of multi-noise systems are exemplified. Results show that the correctness of the GA method is acceptable. The optimal design of noise control by adjusting the location and choosing the proper noise reduction measures on equipment proposed in this study offers a quick and economic approach.

Numerical Assessment of Optimal One-Chamber Perforated Mufflers by Using GA Method

Research on new techniques of perforated silencers has been addressed; however, the research work in shape optimization for a volume-constrained silencer requested upon the demands of operation and maintenance inside a constrained machine room is rare. Therefore, the main purpose of this paper is not only to analyze the sound transmission loss of a one-chamber perforated muffler but also to optimize the best design shape under space-constrained conditions. In this paper, both the generalized decoupling technique and plane wave theory are used. The four-pole system matrix used to evaluate acoustic performance is also deduced in conjunction with a genetic algorithm (GA); moreover, numerical cases of sound elimination with respect to pure tones (150, 550, 950 Hz) are fully discussed. Before GA operation can be carried out, the accuracy of the mathematical model has to be checked using Crocker’s experimental data. The results reveal that the maximum value of sound transmission loss (STL) can be optimally and precisely achieved at the desired frequencies. Consequently, the approach used for the optimal design of the one-chamber perforated mufflers is indeed easy and quite effective.

Shape Optimization of One-Chamber Cross-Flow Mufflers by GA Optimization

In order to reduce the venting noise within a confined room, the development of a high performance muffler within certain space constraints is imperative. Therefore, the main purpose of this paper is to develop an optimally shaped one-chamber cross-flow perforated muffler that will dramatically increase the acoustical performance within a limited space. On the basis of plane wave theory, a four-pole system matrix for evaluating acoustical performance is derived by using a decoupled numerical method. Moreover, in order to search for a global optimum, a genetic algorithm (GA) with tournament selection in elitism and uniform crossover/mutation (analogous to a gene’s evolutionary process) has been used for the muffler’s optimization. To assure the GA’s correctness, the STL’s maximization of one-chamber cross-flow perforated mufflers with respect to three targeted frequencies (200, 400, and 800Hz) is exemplified. Furthermore, a numerical case for dealing with an octave band noise emitted from an air compressor using one-chamber cross-flow mufflers has been introduced and fully discussed. To achieve a better optimization with the GA, various GA parameter sets were used. Before the GA operation is carried out, the mathematical models of cross-flow perforated mufflers are verified by comparing the numerical result and experimental data with those obtained by Sullivan and Wu respectively. Consequently, the results reveal that the acoustical performance for a cross-flow perforated muffler is excellent. Moreover, they reveal that the optimization approach proposed in this study is easy, economical, and quite effective.

Application of Neural Network and Genetic Algorithm to the Optimum Design of Perforated Tube Mufflers

Research on new techniques of perforated silencers has been well addressed. However, the research work on shape optimization for a volume-constrained silencer within a constrained machine room is rare. Therefore, the optimum design of mufflers becomes an essential issue. In this paper, to simplify the optimum process, a simplified mathematical model of the muffler is constructed with a neural network using a series of input design data (muffle dimensions) and output data (theoretical sound transmission loss) obtained by a theoretical mathematical model (TMM). To assess the optimal mufflers, the neural network model (NNM) is used as an objective function in conjunction with a genetic algorithm (GA). Moreover, the numerical cases of sound elimination with respect to pure tones (500, 1000, 2000Hz) are exemplified and discussed. Before the GA operation can be carried out, the accuracy of the TMM is checked by Crockers experimental data. In addition, both the TMM and NNM are compared. It is found that the TMM and the experimental data are in agreement. Moreover, the TMM and NNM confirm. The results reveal that the maximum value of the sound transmission loss (STL) can be optimally obtained at the desired frequencies. Consequently, it is obvious that the optimum algorithm proposed in this study can provide an efficient way to develop optimal silencers.

An Experimental Study of Low-Frequency Vibration-Based Electromagnetic Energy Harvesters Used while Walking

The goal of this paper is to develop and experimentally test portable vibration-based electromagnetic energy harvesters which are fit for extracting low frequency kinetic energy. Based on a previous study on fixed vibration-based electromagnetic energy harvesters, three kinds of portable energy harvesters (prototype I, prototype II, and prototype III) are developed and tested. To obtain the related parameters of the energy harvesters, an experimental platform used to measure the vibrational systems electrical power at the resonant frequency and other fixed frequencies is also established. Based on the research work of vibration theory, a low frequency vibration-arm mechanism (prototype III) which is easily in resonance with a walking tempo is developed. Here, a strong magnet fixed to one side of the vibration-arm along with a set of wires placed along the vibrating path will generate electricity. The circular device has a radius of 180 mm, a width of 50 mm, and weighs 200 grams. Because of its light mass, it is easy to carry and put into a backpack. Experimental results reveal that the energy harvester (prototype III) can easily transform kinetic energy into electrical power via the vibration-based electromagnetic system when walking at a normal speed. Consequently, electrical energy reaching 0.25 W is generated from the energy harvester (prototype III) by extracting kinetic energy produced by walking.

SHAPE OPTIMIZATION OF MULTI-CHAMBER SIDE INLET/OUTLET MUFFLERS HYBRIDIZED WITH MULTIPLE PERFORATED INTRUDING TUBES USING A GENETIC ALGORITHM

The use of perforated-tube side mufflers for depressing venting noise within a constrained space has been prevalent in modern industries. Also, research on mufflers equipped with side inlets/outlets has been thoroughly documented. However, research on shape optimization of side inlet/outlet mufflers hybridized with multiple open-ended perforated intruding tubes which may enhance acoustic performance has gone unnoticed. Therefore, we wish to not only analyze the sound transmission loss (STL) of side inlet/outlet mufflers but also to optimize their best design shape within a limited space. In this paper, the generalized decoupling technique and the plane wave theory used in solving the coupled acoustical problem are employed. Also, a four-pole system matrix for evaluating acoustic performance is deduced in conjunction with a genetic algorithm (GA). We have also introduced a numerical study that deals with broadband noise within a constrained blower room using three kinds of mufflers. Additionally, before muffler shape optimization is performed, an accuracy check on the mathematical models has been performed. Moreover, to verify the reliability of the GA optimization, optimal noise abatements for various pure tones on various mufflers have been examined. Results reveal that mufflers equipped with perforated intruding tubes are superior to those equipped with non-perforated intruding tubes. Also, mufflers with multi-perforated tubes will increase the acoustic performance. Consequently, the approach used in seeking the optimal design of the STL proposed in this study is quite effective.

Shaped optimization of multi‐chamber mufflers with open‐ended perforated inlets using a simulated annealing method.

Recently, research on new techniques of single‐chamber mufflers equipped with a non‐perforated intruding tube has been addressed; however, the research work on multi‐chamber mufflers conjugated with open‐ended perforated intruding inlet tubes which may dramatically increase the acoustical performance has been neglected. Therefore, the main purpose of this paper is not only to analyze the sound transmission loss (STL) of a multi‐chamber open‐ended perforated inlet‐tube muffler but also to optimize the best design shape within a limited space. In this paper, the four‐pole system matrix for evaluating the acoustic performance is derived by using a decoupled numerical method. Moreover, a simulated annealing method has been used during the optimization process. To appreciate the acoustical ability of the open‐ended perforated intruding inlet‐tube and chambers inside a muffler, two kinds of traditional multi‐chamber mufflers hybridized with non‐perforated intruding inlet tubes (one‐chamber and two‐chamber muffl...

Numerical assessment of plenums intersected by four baffles using the boundary element method, genetic algorithm, and neural networks

There has been much research on partitioned plenums in the industrial field. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, five-chamber plenums intersected by four baffles within a fixed space are assessed. In order to select the appropriate design parameter sets used in the shape optimization of a five-chamber plenum, three kinds of design parameter sets (Case I: L1* and L2*; Case II: L1** and L2**; Case III: L1***, L2***, and L3***) are proposed. In order to simplify the shape optimization of plenums intersected by multiple baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fitted with a series of real data - input design data (baffle dimensions) and output data approximated by BEM data in advance. Before optimization is performed, accuracy of the boundary element method (BEM) for a one-chamber and three-chamber plenum is checked using analytical and experimental data and found to be accurate. To assess the optimal plenums, a genetic algorithm (GA) is adopted. Consequently, optimal results reveal that the depths of the two upper baffles and the two lower baffles play essential roles in minimizing the noise level of the lower frequencies (400∼800 Hz). Moreover, the horizontal span of the baffles will influence the acoustical performance of the higher frequencies (1200 Hz and above).

A study of the measurement system capability for a gauge block comparator

Abstract This is a study of the measurement system capability and analysis of a gauge block comparator aimed at improving the quality requirements of calibration instruments that ensure system stability. The total variance of measuring instruments includes the following: different measuring environments, precision of measuring equipment, the experience of the measuring staff, and the specifications of the workpiece. The source variations must be converted into data and charted to show the measuring capability of the system. The main items in a measurement system analysis are the following: stability, bias, linearity, repeatability, and reproducibility. Different experimental models are designed according to different characteristics. After running the data, we can evaluate the data using statistical methods which include the following: hypothesis test, one-sample t-test, two-sample t-test, linear regression analysis, and analysis of variance (F test). We then use statistical software (MINITAB) to do a reliability analysis and list the charts. Finally, we can determine if the measuring capability of an instrument is accurate enough to provide a reference for instrument calibration and quality assurance. This analysis helps us understand if the measuring instruments are abnormal. Using the analysis method to determine the measurement system can clearly show whether a system is reliable or not.

Optimal assessment of wool lining inside multi-tube mufflers with a rectangular section using the boundary element method and the genetic algorithm

Abstract Recently, research on new mufflers equipped with connected curved tubes using phase cancellation techniques has been addressed in the industrial field. On the basis of the transfer matrix method and the stiffness matrix method, researchers have explored noise reduction effects within a constrained space. However, the attenuation bands are too narrow and the overall acoustical performance in dealing with broadband noise is thus insufficient. Therefore, in order to broaden the spectrum of the acoustical performance curves at various targeted tones (250, 500, and 900 Hz), a wool optimally lined within the ducts of HQ mufflers is proposed. In this paper, five kinds of HQ mufflers with rectangular sections (muffler A: a double-connected curved tube muffler; muffler B: a double-connected abrupt tube muffler; muffler C: a one-sided triple-connected curved tube muffler; muffler D: a two-sided tripleconnected curved tube muffler; muffler E: a one-sided triple-connected abrupt tube muffler) within a fixed length are assessed. In order to facilitate the assessment of optimal mufflers, a boundary element model (BEM) is adopted as the mathematical objective function. To assess the optimal mufflers, a genetic algorithm (GA) is linked with the BEM. Before the GA operation can be carried out, the accuracy of the mathematical models must be checked using the experimental data. Optimal results reveal that the maximum value of the sound transmission loss (STL) can be optimally improved at the targeted frequencies. Consequently, the optimum algorithm proposed in this study provides an efficient way to find a better silencer for industry.