Advanced Materials Research Vols. 383-390

Abstract: When designer designing a new engineering drawing, they will refer to the previous valid design document that same or nearly match with their new design specification. Previous design have been reviewed, analyzed and proven to be successful. By using the previous design, it likely saves significant resources and manpower. In real situations, engineering drawing is usually in large quantities and not in order. This paper describes a research and development of an extraction technique in the field of engineering drawing. Non-geometry information that will be emphasis in this research is information that available in the title block.

Abstract: The objective of this paper is to identify, detect and isolate faults to an industrial gas turbine. The detection scheme is based on the generation of so-called "residuals" that are errors between estimated and measured variables of the process. A State-Space model is used for identification and some observer-based methods are used for residual generation, while for residual evaluation a neural network classifier for MLP is used. The proposed fault detection and isolation tool has been tested on a single-shaft industrial gas turbine simulator.

Abstract: Polychromatic sets theory is used for boxes parts CAPP expert system so as to store knowledge rules of selecting machining method in form of contour matrix. Through the logic operation of coloring in the knowledge based, the machining schemes relating to the features can be obtained. Genetic algorithm is used to sequence machining step in the machining center to make the process of sequencing machining step more flexible and convenient, and the result of sequencing machining step more reasonable.

Abstract: Industrial robots are a cost-efficient possibility to face the increasing demands of future production processes. This paper presents an adaptronic approach to improve the structural properties of stateoftheart robots. For this purpose, highly-flexible piezo-based actuator foils and sensors are directly integrated into CFRP components without structural weakening. This paper shows the potential of these implemented measures for the active damping of structural vibration due to chattering while machining and for aprecision positioning even in the sub-micrometer range.

Abstract: The forming behavior of Tailor Welded Blanks (TWB) are greatly influenced by blank conditions like thickness ratio, strength ratio, weld conditions like weld orientation, weld location, and weld properties. Designers will be greatly benefited if an ‘Expert system’ is available that can deliver forming behavior of TWB for varied weld and blank conditions. This work primarily aims at developing an expert system based on Artificial Neural Network (ANN) to predict the tensile behavior of TWBs made of DP 590 Steel grade base material. ANN models are developed based on full factorial and L27 orthogonal array design of experiments method and the results are compared. Through out the work, PAM STAMP 2G® finite element (FE) code is used to simulate the tensile behavior. The strain hardening exponent ‘n’ and strength co-efficient ‘K’ are predicted and used to train the ANNs. The results obtained from expert system/ANN models are validated by comparing them with the results obtained from FE simulations for chosen intermediate levels. The results are encouraging with acceptable prediction errors.

Abstract: This paper describes the 0.35 um SiGe BiCMOS Voltage Controlled Oscillators (VCOs). One is Cross-coupled VCO, and the other one is Colpitts VCO. Both of them are designed with the same method. For achieving lower noise, the differential structure was used at this design. The center frequency for Cross-coupled VCO and Colpitts VCO is 5GHz. The tuning range of Cross-coupled VCO and Colpitts VCO is 1750 MHz and 230 MHz, respectively. The phase noise and the figure of merit (the FOM) for Cross-coupled VCO, are -155.5 dBc/Hz and -224.7dBc/Hz @1MHz offset frequency at an oscillation frequency of 5GHz, respectively. The phase noise and the figure of merit value of Colpitts VCO is -134.1 dBc/Hz and -200.3 dBc/Hz at the 1MHz offset from the center frequency of 5GHz. For The DC current of Cross-coupled and Colpitts VCO is 2 mA and 4 mA , respectively. Considering a 3.0 V supply Cross-coupled voltage (VCC) for both VCOs. The output power of Cross-coupled VCO is -3.94 dBm and the Colpitts VCO achieves an output power of 5.428 dBm. Agilent ADS software is used throughout this work

Abstract: The author wants to use a case study to investigate the injection moulding machine parameters which will affect the horizontal length dimension of a plastic component used in digital camera. Currently the injection moulding machine process setting caused variations in the diameter exceeding the specification limit. Therefore the experiment is needed to identify the process factors that could be set to maintain the horizontal length dimension closest to the target value and smallest possible variation. The experimental model is used to investigate four factors to identify the factors having large effect by using the Full Factorial Design of Experiment (DOE). The experiment has emphasized the use of these designs in identifying the subset of factors that are active and provide some information about the interaction.

Abstract: This paper introduces an application of Multi-Objective Evolution Algorithm (MOEA) to design Q and R weighting matrices in Linear Quadratic regulators (LQR). Considering the difficulty of designing weighting matrices for a linear quadratic regulator, a multi-objective evolutionary algorithm based approach is proposed. The LQR weighting matrices, state feedback control rate and consequently the optimal controller are obtained by means of establishing the multi-objective optimization model of LQR weighting matrices and applying MOEA to it, which makes control system meet multiple performance indexes simultaneously. Controller of double inverted pendulum system is designed using the proposed approach. Simulation results show that it has shorter adjusting time and smaller amplitude value deviating from steady-state than a Non-dominated Sorting Genetic Algorithm LQR ( NSGA- LQR )weighting matrices design approach.

Abstract: Using VB 6.0 and CATIA software, this paper illustrates a method to generate the parameters and three dimensional shapes of the hydraulic torque converter blade automatically, in order to cut the development cycle. Finally, as an example of this methodology, a particular parametric design of a hydraulic torque converter blade is presented to verify the validity of the method by establishing a VB 6.0 program, which can generate the blade parameters and the three dimensional shape of the specific hydraulic torque converter blade.

Abstract: The selection of machining parameters needs to be automated, according to its important role in machining process. This paper proposes a method for cutting parameters selection by fuzzy inference system generated using fuzzy subtractive clustering method (FSCM) and trained using an adaptive network based fuzzy inference system (ANFIS). The desired surface roughness (Ra) was entered into the first step as a reference value for three fuzzy inference system (FIS). Each system determine the corresponding cutting parameters such as (cutting speed, feed rate, and depth of cut). The interaction between these cutting parameters were examined using new sets of FIS models generated and trained for verification purpose. A new surface roughness value was determined using the cutting parameters resulted from the first steps and fed back to the comparison unit and was compared with the desired surface roughness and the optimal cutting parameters ( which give the minimum difference between the actual and predicted surface roughness were find out). In this way, single input multi output ANFIS architecture presented which can identify the cutting parameters accurately once the desired surface roughness is entered to the system. The test results showed that the proposed model can be used successfully for machinability data selection and surface roughness prediction as well.