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This design activity is an innovative method of rapid assembly system for folding chairs. The research methods used in this study included literature analysis, TRIZ the method, human factors engineering (HFE), universal design, and IPA. First, the design of the folding chair and the layout of the literature related to the chair are analyzed. The contradiction matrix was used in the TRIZ method to find the principle of invention and analyze it, to provide a reference for the innovative design of folding chairs, and then use the relevant literature on materials to help design and select materials quickly. Next, the chair is assembled and unfolded and universal design is applied to design it into an acceptable product, causing it to be more popular. The human–machine interaction with HFE makes the design of rapid assembly and the design of folding chairs faster and safer. Finally, the IPA method is used to understand the subjective feelings of customers on the products of this research and the satisfaction and importance are used as the basis for evaluation; a two-dimensional matrix graph is drawn. After drawing a simulation using drawing software, it is compared with the traditional folding chair and the research results are as follows: (1) Quick unfolding function: use the pull ring upwards and it naturally unfolds downwards by gravity. (2) Quick folding and storage function: use the foot pedal, single-foot operation, and the folding chair can be quickly stored. (3) Rapid transportation and unfolding function: The chair back can be connected with other chair backs and has the functions of quick unfolding and quick storage, so as to realize the quick placement of the folding chair. This design activity realizes the preliminary design concept and design simulation of the product design through a systematic and innovative method. Through this design activity, we can understand the problems existing in product improvement before product development, so as to conduct market research and production cost assessment in the actual mass production later, and further reduce the cost of product design improvement.

This paper proposes an adaptive Kalman filter (AKF) control algorithm for capacitive touch panels under the radiation effect of a commercial fluorescent lamp. The predicted covariance matrix of the proposed algorithm is timely updated by two-dimensional gesture compensation. It adaptively adjusts the filter correction manner between fast tracking and smoothing modes. The trajectory area and velocity concept builds up the compensation method and proves in real-time practice by a microprocessor unit. The electromagnetic radiation effect is investigated to obtain the lamp emission noise level. A comprehensive system structure provides the flexibility and efficiency in competing with different algorithms for comparison. A microprocessor unit completed the AKF method calculation in 8.23 ms under fluorescent lamp lightening condition in real time. All Python environments are implemented in the merit of hardware peripheral support, rich programming environments, and open source modules.

The following topics are dealt with: learning (artificial intelligence); neural nets; feature extraction; pattern classification; object detection; time series; sport; stock markets; optimisation; medical computing.

In the face of an ever-changing global market, companies able to launch new products meeting consumer needs faster than their competitors may not only gain a larger market share, but also shorten the development cycle to reduce costs. However, there are currently no universal design strategies and tools for evaluating the design of consumer products. Therefore, the purpose of this study is mainly to formulate a systematic and innovative product design strategy and evaluation tool, so that designers can use them to select the key factors when designing consumer products and design products that meet customer needs in the shortest development cycle. First of all, this study was designed to sort out general design methods and influencing factors in consumer product design based on theoretical analysis and expert interviews. Next, a questionnaire survey of 15 design-related experts and scholars was conducted, and the most important design methods and design factors were selected using the Fuzzy Delphi Method (FDM). After that, the analytical network process (ANP) method was used to obtain the priority weight of each design factor, and select the optimal product design strategy, QTPCP, and the deciding elements that affect consumer demand for products, including 2 dimensions, 11 design elements, and 38 design factors, making theoretical contributions to product design management. The design strategies and evaluation tools developed according to the conclusions are helpful in comprehensive planning and design selection for products of different natures, and make practical contributions, enabling product developers or designers to efficiently select the optimal product design when faced with different new product designs.

The classification of sound signals can be applied to the fault diagnosis of mechanical systems, such as vehicles. The traditional sound classification technology mainly uses the time-frequency domain characteristics of signals as the basis for identification. This study proposes a technique for visualizing sound signals, and uses artificial neural networks as the basis for signal classification. This feature extraction method mainly uses a principle to convert a time domain signal into a coordinate symmetrized dot pattern, and presents it in the form of snowflakes through signal conversion. To verify the feasibility of this method to classify different noise characteristic signals, the experimental work is divided into two parts, which are the identification of traditional engine vehicle noise and electric motor noise. In sound measurement, we first use the microphone and data acquisition system to measure the noise of different vehicles under the same operating conditions or the operating noise of different electric motors. We then convert the signal in the time domain into a symmetrized dot pattern and establish an acoustic symmetrized dot pattern database, and use a convolutional neural network to identify vehicle types. To achieve a better identification effect, in the process of data analysis, the effect of the time delay coefficient and weighting coefficient on the image identification effect is discussed. The experimental results show that the method can be effectively applied to the identification of traditional engine and electric vehicle classification, and can effectively achieve the purpose of sound signal classification.

This aim of this work was to develop an integrated fault location and restoration approach for microgrids (MGs). The work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of a fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations was utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve fault location and restoration problems in MGs.

This work aims to develop an integrated fault location and restoration approach for microgrids (MGs). This work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations is utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve the fault location and restoration problem in MGs.

It is to use the Simulation Program with Integrated Circuit Emphasis(SPICE) Model in railway traction system simulations. There are no complex mathematical equations nor software programing activity for derive the multiphase transformer performance waveforms. There are three railway operation cases in the linear loading, non-linear loading and operational accident short circuit fault for validate its application. The contribution is to propose the new multiphase power system analysis technique in the low entry effort.

With the development of artificial intelligence in recent years, deep learning has been widely used in mechanical system signal classification but the impact of different feature extractions on the efficiency and effectiveness of deep learning neural networks is more important. In this study, a vehicle classification based on engine acoustic emission signal in the time domain, the frequency domain and the wavelet transform domain for deep learning network techniques is presented and compared. In signal classification, different feature extractions will show in different decomposition levels and can be used to recognize the various acoustic conditions. In the experimental work, as engines from 10 different ground vehicles operate, the measured sound signal is converted into a digital signal, and the established data set is classified and identified by the deep learning method. The number of samples, identification rate and identification time in the various signal domains are compared and discussed in this study. Finally, the experimental results and data analysis show that by using the wavelet signal and the deep learning method, excellent identification time and identification rate can be achieved, compared with traditional time and frequency domain signals.

The calculation of the magnitudes and phase angles of the bus voltage is a challenging task in real-time applications for power systems. Voltage profile, which denotes the present conditions of a power system, is determined by executing the traditional AC power flow program or by searching the supervisory control and data acquisition system. The AC power flow program is not suitable for several real-time applications, such as contingency analysis and security control calculations, because of its complexity and convergence problems. Fast computation is the major concern in such applications. In this paper, a new method based on sensitivity factors, referred to as Jacobian-based distribution factors (JBDFs), is proposed for calculating the magnitudes and phase angles of bus voltages. This method requires setting up JBDFs and deriving optimal solution paths of bus voltage for non-swing buses through dynamic programming under base-case loading conditions. Under real-time conditions, the proposed method initially calculates real and reactive power line flows via JBDFs, and then computes the voltage magnitudes and phase angles of non-swing buses through the derived optimal solution paths. The excellence of the proposed hybrid calculation method is verified by IEEE test systems. Simulation results demonstrate that the proposed method exhibits fast computation and high accuracy. Thus, the method is suitable for real-time applications. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

In this study, we examined the development of industry-oriented safety degree curricula at a college level. Based on a review of literature on the practices and study of the development of safety curricula, we classified occupational safety and health curricula into the following three domains: safety engineering, health engineering, and safety and health management. We invited 44 safety professionals to complete a four-round survey that was designed using a modified Delphi technique. We used Chi-square statistics to test the panel experts' consensus on the significance of the items in the three domains and employed descriptive statistics to rank the participants' rating of each item. The results showed that the top three items for each of the three domains were Risk Assessment, Dangerous Machinery and Equipment, and Fire and Explosion Prevention for safety engineering; Ergonomics, Industrial Toxicology, and Health Risk Assessment for health engineering; and Industrial Safety and Health Regulations, Accident Investigation and Analysis, and Emergency Response for safety and health management. Only graduates from safety programmes who possess practical industry-oriented abilities can satisfy industry demands and provide value to the existence of college safety programmes.

A spiral-ADDIEE&R model is introduced and utilized to develop, implement and evaluate an industry oriented technology course, automatic measurement technology. A process is built to develop teaching material and training device. The practical competence indicators for automatic measurement technology will be found using the Delphi questionnaire answered by industrial supervisors, engineers and university scholars. The teaching material contains 6 chapters and 27 sections for developing and a multi-functional automatic measurement platform that includes over 20 kinds of sensors and measurement devices, designed and constructed for student training use. An experimental class is given with assessment performed for examining the flaws in this course development process.

This paper aims to evaluate the maximum interconnected capacity of the distributed generation(DG), which been interconnected into the distribution feeders. The ±2.5% voltage derivation limit of the Taipower interconnected guides are adopted for evaluating the maximum interconnected capacity of DG, and the unbalanced power flow program is used to solve for the bus voltage profiles before and after the DG interconnected into a primary feeder. The IEEE 13-Bus feeder is modified as a sample system. The simulation scenariosinclude the individual phase and three-phase connections between the DG and the primary feeder. The outcomes demonstrate that the maximum interconnected capacity of DG is dependent on the short-circuit capacity, connection location, load demand, and voltage variation limit. Keywords-distributed generation; maximum interconnected capacity; power flow; voltage variation

A fast and high-efficient sensitivity-based approach for real-time three-phase line flow calculation is proposed in this paper, this approach combines the three-phase power-flow (TPPF) solution techniques with the new sensitivity factor, named three-phase ZBUS distribution factor (TPZBD). The TPZBD is associated with both the changes of real and reactive power injections of individual phase at each bus into the three-phase line flow. Hence, the proposed TPZBD directly reflects load demand changes to the line flow. Accordingly, any feasible TPPF solution technique must be used to solve for the base case line flow solution at first time, based on the solution and TPZBD formulas, the real-time three-phase line flow is determined rapidly by the presented approach without any iteration after load demand changes. Finally, a 7-node sample system that is modified from Taipower distribution feeders is used to test the proposed approach. The results of this paper demonstrate that the proposed approach is capable of calculating real-time three-phase line flow for distribution automation.

This paper aims to analyze the dynamic operations of a low-voltage micro grid with various distributed energy resources. The sample system is composed of a low-voltage micro grid with a 30 kVA micro-hydro generator, a 30 kVA diesel engine generator, a 30 kVA gas engine generator, and a 15 kVA micro-wind turbine generator as well as loads. The dynamic models of individual components are established and tested to ensure accuracy, and then the aforementioned components are integrated to form a micro grid dynamic simulation system in the Matlab/Simulink environment. The system dynamic operations of the proposed micro grid are discussed. The results are expected to provide distribution engineers with the necessary information on the dynamic characteristics of the AC low-voltage micro grids. Further, the results are helpful for the development of micro grids in Taiwan.

Under technological advancement, technology allows human life to be more convenient and safer. This study used LabView as the system development software and the computer on the server side, to develop an intelligent distributed monitoring system for monitoring household electronic appliances. Besides controlling the server-end, network and GSM system were used to construct remote control and monitoring capabilities. The communication between the server end and each control end was through ZigBee, thus achieving a wireless network.

This paper proposes an effective approach for planning a load transfer substation pair(LTSP) between two normally closed-loop feeders considering minimization of system power losses. Firstly, the annual equivalent load of each load point is calculated. Then, a genetic algorithm-based (GA-Based) approach has been proposed to solve this optimization problem. The objective is minimization of the annual system power losses. Finally, the optimal LTSP was chosen considering minimizing annual system power losses and the maximum voltage drops at each bus as well as ampere capacities of each feeder segment. The method presents in this paper are valuable to distribution engineers for planning the LTSPs between normally closed-loop feeders.

In this research, a multi-function electro-cardiogram measurement system is designed and constructed. The system applies the structure of virtual instrument built by software part, Labview hardware part, DAQ card and some external circuits is applied in the development process. This research integrates different fields that include physiological signals, circuits, virtual instrument, and physiology. The functions of system include waveform display, auto signal processing, data saving, histogram display, heartbeat display, irregular heart rhythms warning and remote measurement. Practical measurements have been carried out to demonstrate the capabilities of this measurement technique.

In this research, a new electro-oculogram measurement technique is designed and constructed. The structure of virtual instrument built by software part, Labview hardware part, DAQ card and some external circuits is applied in the development process. This research integrates industry needing oriented technology – physiological measurement of medical industry, advanced technology – virtual instrument, and medical knowledge – physiology. Practical measurements have been carried out to demonstrate the capabilities of this new measurement technique.

This research proposes poleplacement approach to achieve adaptive control design of band-pass digital filters. Digital control concept is deployed in the design scheme for practical computer control use. Frequency transformation is current well known skill to transfer low-pass prototype filter into another desired filter. It is a mathematical methodology to have the passband change. Here, poleplacement approach is used to shift poles of the original low-pass prototype filter to the desired poles location so that a new filter which has the desired passband and the desired cut-off frequency can be obtained. This control process provides the filters potentially possessing adaptive performances. The filter responses of frequency transformation and the responses of poleplacement control approach are also compared to show the feasibility of this design. Key words: adaptive, digital, band-pass filter, control design, poleplacement.

A new sensitivity factor which is called ZBUS distribution factor (ZBDF) to calculate active and reactive three-phase line flows for distribution automation is proposed in this paper. This method is associated with both the changes of individual phase-active and reactive power injection at each bus into the three-phase real and reactive power line flows. Hence, the proposed ZBDF reflects load changes to the line flows, while the loading conditions change from the base case loads. Accordingly, the existing implicit ZBUS Gauss method is applied to solve for the base case three-phase power flow (TPPF). Based on the power flow solutions, the ZBUS matrix, the primitive line impedance, and the changes of the individual phase-active and reactive power at each bus, the three-phase line flows for distribution automation are determined accurately and rapidly from the presented method without any iteration. Finally, a sample system is used to verify the developed approach. The numerical simulation results demonstrate that the proposed method not only provides high-speed computation, but also can be applied to distribution automation.

This paper develops an optimal robust control algorithm for finding digital computer control of decentralized stochastic singularly-perturbed large-scale actuator type systems with multiple time varying delays. Due to the derived algorithm concerns at each moment, the found controller is also suitable in the time varying condition. Moreover, this system possesses the fast response characteristics of the subsystems. The system order can be reduced and the analysis process can be simplified. . This noise-disturbed, time varying and multiple delay system can be often seen in practical computer controlled large-scale systems such as electric power systems, communication networks, cyber networks, and aerospace systems. Finally, the optimal cost is also obtained.

This is an extension research of [1]. In [1], frequency scaling of adaptive digital filter design algorithm is proposed. The pole placement technique is used to achieve the frequency scaling of adaptive digital filter design. In this paper, the same concept is applied for a fast way to design adaptive high-pass filters. Frequency transformation is used to transfer low-pass prototype filter into high-pass filter. State feedback is used to shift poles of the original low-pass prototype filter to the desired poles location so that a high-pass filter which has the desired passband and the desired cut-off frequency can be obtained. The responses of the frequency transformed high-pass filters and the responses of the state feedback digital controlled high-pass filters are also compared to show the feasibility of this approach in this paper.

In this research, the structure and design of virtual impedance analyzers are studied. The construction process is also described and introduced. This programmable virtual impedance analyzer is achieved by software part, Labview, hardware part, DAQ card and some external circuits. The measurement functions include: (1) impedance [Z] display that has magnitude, phase, impedance and reactance, (2) display settings that has visible section and scale, (3) measurement frequency control, (4) run button, and (5) display window. In the illustrations, demonstrate the design of front panels and also proceed the measurement test of designed virtual impedance analyzer to show the capabilities.

This article is aimed at a case study of a vocational high school in central Taiwan, proposing various energy conservation strategies, as well as promoting 16 optimal plans for energy conservation over a 3-year period of monitoring and recording. This study is based on the statistics regarding energy conservation, and the subject has been designated by the Ministry of Education as a demonstration school of implementing energy conservation education. It was also awarded the "2006 Energy Conservation Excellent Company Award" by the Ministry of Economic Affairs. The practicality and effectiveness of the optimal planning in energy conservation is discussed and proven in this study.

In this research, a single input virtual digital multi-meter are designed and constructed. It consists of three major works: (1) software design of front panel, (2) measurement circuit design and (3) system integration. The related measurement theories are also described and introduced. This digital multi-meter is made by software part, Labview, hardware part, DAQ card and external measurement circuits. The measurement functions include (1) DC voltage (2) AC voltage (3) DC current (4) AC current (5) resistance (6) capacitance (7) inductance (8) diode test (9) audio continuity. In the illustrations, demonstrate the design of front panels and also proceed the measurement test of the designed single input virtual digital multi-meter to show the capabilities.

An iteration method is proposed for sub-optimal output feedback computer control of decentralized singularly-perturbed systems. Computer control, decentralized output feedback control, and order- reduced control are three primary goals for this control scheme. The analog to digital transformation technique is used to convert continuous-time state models to discrete-time domain for the controllers which can be implemented by computer and be able to deal with today's complicated large scale system. Singular perturbation methods are applied to reduce the order of the system. After order reduction, it will help us to analysis the system; reduce the manufacturing process and cost. The contribution of this research provides a sub-optimal computer control algorithm for large-scale and high-dimension systems with strong potential for practical applications, such as power distribution and communication networks.

The paper proposes a direct torque control (DTC) scheme for a matrix-converter-fed induction motor drive system. DTC is a high performance motor control scheme with fast torque and flux responses. However, the main disadvantage of conventional DTC is electromagnetic torque ripple. Besides, the matrix converter is a single-stage ac-ac power conversion device without dc-link energy storage elements. Due to the properties of the matrix converter, the pseudo dc-link will provide with three different types of voltage: the high, middle, and low voltages. Therefore, based on space vector modulation generated by a matrix converter, there are three states on each space vector location. By suitably selecting switching pattern, the electromagnetic torque ripple of the motor is effectively reduced. Using this switching strategy, the advantages of the DTC schemes and the benefits of the matrix converters can be combined. As a result, a satisfactory servo drive can be achieved.

This paper develops a simple algorithm for having robust optimal computer control in decentralized stochastic singularly-perturbed systems by poles assignment. This type of noise-disturbed system can be often seen in computer controlled large-scale systems such as electric power systems, communication networks, and aerospace systems. Due to that this computer controlled system possesses the fast response characteristics of the subsystems, the system analysis can be simplified by singularly perturbation methodology and the aggregation matrix is also applied to obtain faster calculation. Finally, the aggregation matrix is found out that will be an important intermediary to easily achieve the robust sub-optimal poles assignment. In the end, three steps are proposed to complete the robust sub-optimal pole assignment.

This research proposes using poleplacement technique to achieve adaptive filter design. Digital control concept is also deployed in the design scheme for practical computer control use. Frequency scaling is current well known skill to scale low-pass prototype filter into another low-pass filter. It is a mathematical methodology to have the passband change. Here, poleplacement approach is used to shift poles of the original low-pass prototype filter to the desired poles location so that a new filter which has the desired passband and the desired cut-off frequency can be obtained. This approach potentially makes filters possess adaptive performances, and the filter system can be controlled by digital computer. The responses of the frequency transformed filters and the responses of the state feedback digital controlled filters are also compared to show the feasibility of this approach in this paper.

This paper studies a method that is used to have control in decentralized actuator type large-scale systems by sub-optimal poles assignment. This type of system can be often seen in computer controlled systems such as electric power systems, communication networks, and aerospace systems. Due to that the fast responses of the subsystems die out a lot faster than the main plain in this type of system, the states of the subsystems can be ignored to simplify the system by singularly perturbation methodology. The optimal poles found are based on a reduced-order model, therefore; the poles are called robust sub-optimal poles assignment. Finally, three easy steps are proposed to complete the robust sub-optimal pole assignment. How robust is this control method can be compared by the dominant pole of the original system and the poles of the reduced-order systems after implementing close-loop feedback.

The goal of this research is to develop a new control scheme for digital computer control of decentralized large-scale systems. Such a control system can be taken as a decentralized singularly-perturbed systems, because of the faster responses of the subsystems. Digital control of robust reduced-order controllers and reduced-order observer-based controllers are expected to be found for stabilization and reliable control of linear large-scale systems via decentralized control. The developed control techniques will be suitable for large-scale and high-dimension systems with strong potential for practical applications, such as power distribution and communication networks.

This study proposes a novel network sensitivity-based approach to solving complex power flow calculation problems in real time. A new sensitivity factor, named Jacobian-based distribution factor (JBDF), is used for the calculation of active and reactive power flow in transmission systems. It is derived from the Jacobian matrix of the base case Newton-Raphson power flow solution, and kept constant during real-time line flow calculation. Unlike well-known distribution factors, such as generation shift distribution factor (GSDF), generalised generation shift distribution factor (GGDF) and Z-bus distribution factor (ZBD), this approach reflects changes in complex injection power. Changes in load conditions from base case loads, with either conforming or non-conforming changes in complex power in each bus, can be used to rapidly compute active and reactive power flow without iterations. The proposed approach was tested on IEEE 14-Bus and 30-Bus systems. Numerical results demonstrate that the proposed approach is not only superior to previous distribution factors, but also compares favourably with the Newton-Raphson power flow method. It is well suited to real-time applications in steady-state security control and optimal dispatch.