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E-commerce has become a crucial business model through the Internet around the world. Therefore, its transaction trend forecast can provide important information for the market planning and development in advance. For this purpose, the integrated model of enhanced whale optimization algorithm (EWOA) with support vector machine (SVM) is proposed for forecast of E-commerce transaction trend in this study. First, the global optimization ability of the whale optimization algorithm (WOA) is enhanced by the search updating strategy. Second, multiple factors that may affect the E-commerce transaction trend are analyzed and determined using the gray correlation mechanism. Third, the EWOA algorithm is employed to optimize the SVM random parameters. Finally, the EWOA-SVM model is established for forecasting E-commerce transaction trend. Two representative cases tests confirm that the EWOA-SVM model is superior to other existing methods in terms of fast convergence speed and high prediction accuracy.
Suqi Zhang; Hsiung-Cheng Lin; Xinxin Wang. Forecast of E-Commerce Transactions Trend Using Integration of Enhanced Whale Optimization Algorithm and Support Vector Machine. Computational Intelligence and Neuroscience 2021, 2021, 1 -12.
AMA StyleSuqi Zhang, Hsiung-Cheng Lin, Xinxin Wang. Forecast of E-Commerce Transactions Trend Using Integration of Enhanced Whale Optimization Algorithm and Support Vector Machine. Computational Intelligence and Neuroscience. 2021; 2021 ():1-12.
Chicago/Turabian StyleSuqi Zhang; Hsiung-Cheng Lin; Xinxin Wang. 2021. "Forecast of E-Commerce Transactions Trend Using Integration of Enhanced Whale Optimization Algorithm and Support Vector Machine." Computational Intelligence and Neuroscience 2021, no. : 1-12.
The high-level penetration of intermittent renewable power generation may limit power system inertia, resulting in system frequency instability in increasing power converter-based energy sources. To resolve this problem, virtual inertia control using distributed gray wolf optimization (DGWO) method in a synchronous generator is simulated under a distinct output fluctuation condition. First, the DGWO algorithm was established to achieve a local and global balance solution, and standard test functions were employed to verify the model convergence. Second, the key parameters that determine the effect of the virtual inertia controller in the power grid were analyzed. A DGWO-based optimization strategy to stabilize inertia was also developed. Finally, simulation results using step and random loads under a high permeability level are provided to verify the effectiveness of the proposed model. In the step load disturbance, the system can recover from the disturbance point to the stable point after 3 s under the regulation of the proposed control strategy, which is reduced by 18 s compared with the traditional control method. In the random load test, it takes only 12 s, 63 s less than the traditional one. Accordingly, the power system frequency can be stabilized more quickly from a disturbance state to a stable stage.
Shuanbao Niu; Linan Qu; Hsiung-Cheng Lin; Wanliang Fang. Effective virtual inertia control using inverter optimization method in renewable energy generation. Energy Exploration & Exploitation 2021, 1 .
AMA StyleShuanbao Niu, Linan Qu, Hsiung-Cheng Lin, Wanliang Fang. Effective virtual inertia control using inverter optimization method in renewable energy generation. Energy Exploration & Exploitation. 2021; ():1.
Chicago/Turabian StyleShuanbao Niu; Linan Qu; Hsiung-Cheng Lin; Wanliang Fang. 2021. "Effective virtual inertia control using inverter optimization method in renewable energy generation." Energy Exploration & Exploitation , no. : 1.
It is crucial to carry out the fault diagnosis of rotating machinery by extracting the features that contain fault information. Many previous works using a deep convolutional neural network (CNN) have achieved excellent performance in finding fault information from feature extraction of detected signals. They, however, may suffer from time-consuming and low versatility. In this paper, a CNN integrated with the adaptive batch normalization (ABN) algorithm (ABN-CNN) is developed to avoid high computing resource requirements of such complex networks. It uses a large-scale convolution kernel at the grassroots level and a multidimensional 3 × 1 small convolution nuclear. Therefore, a fast convergence and high recognition accuracy under noise and load variation environment can be achieved for bearing fault diagnosis. The performance results verify that the proposed model is superior to Support Vector Machine with Fast Fourier Transform (FFT-SVM) and Multilayer Perceptron with Fast Fourier Transform (FFT-MLP) models and Deep Neural Network with Fast Fourier Transform (FFT-DNN).
Chao Fu; Qing Lv; Hsiung-Cheng Lin. Development of Deep Convolutional Neural Network with Adaptive Batch Normalization Algorithm for Bearing Fault Diagnosis. Shock and Vibration 2020, 2020, 1 -10.
AMA StyleChao Fu, Qing Lv, Hsiung-Cheng Lin. Development of Deep Convolutional Neural Network with Adaptive Batch Normalization Algorithm for Bearing Fault Diagnosis. Shock and Vibration. 2020; 2020 ():1-10.
Chicago/Turabian StyleChao Fu; Qing Lv; Hsiung-Cheng Lin. 2020. "Development of Deep Convolutional Neural Network with Adaptive Batch Normalization Algorithm for Bearing Fault Diagnosis." Shock and Vibration 2020, no. : 1-10.
The large-scale renewable energy power plants connected to a weak grid may cause bus voltage fluctuations in the renewable energy power plant and even power grid. Therefore, reactive power compensation is demanded to stabilize the bus voltage and reduce network loss. For this purpose, time-series characteristics of renewable energy power plants are firstly reflected using K-means++ clustering method. The time group behaviors of renewable energy power plants, spatial behaviors of renewable energy generation units, and a time-and-space grouping model of renewable energy power plants are thus established. Then, a mixed-integer optimization method for reactive power compensation in renewable energy power plants is developed based on the second-order cone programming (SOCP). Accordingly, power flow constraints can be simplified to achieve reactive power optimization more efficiently and quickly. Finally, the feasibility and economy for the proposed method are verified by actual renewable energy power plants.
Linan Qu; Shujie Zhang; Hsiung-Cheng Lin; Ning Chen; Lingling Li. Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method. Energies 2020, 13, 3556 .
AMA StyleLinan Qu, Shujie Zhang, Hsiung-Cheng Lin, Ning Chen, Lingling Li. Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method. Energies. 2020; 13 (14):3556.
Chicago/Turabian StyleLinan Qu; Shujie Zhang; Hsiung-Cheng Lin; Ning Chen; Lingling Li. 2020. "Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method." Energies 13, no. 14: 3556.
This study presents a measurement method for a bike frame to solve a problem that usually relies on the digimatic callipers or mechanical molds handled by a human, therefore avoiding a long time process and measurement errors. In such a mechanism, the measured data is based on the handwritten record, and thus a difficulty may occur in further data analysis using the computer. For this reason, this study aims to develop a mathematical model of three-dimensional geometry especially applied for robotic arm-based bike frame measurement. The proposed mathematical geometric model effectively integrates the sphere formula with the inner product of normal vector to find four parameters in the sphere formula using only three measured points. Accordingly, the centre coordinate of the check point and its diameter can be calculated accurately and simply. The practical model performance also prooves that all crucial quality checking items such as centre plane offset, inside diameter, axis point and parallelism in different rotating shafts of bike frame can be achieved in term of rapid, robustness and precision. Moreover, the measurement accuracy in the estimated standard deviation and measurement uncertainty using two different bike frames is presented to verify the effectiveness of the proposed model.
Hsiung‐Cheng Lin; Bo‐Ren Yu; Jen‐Yu Wang; Jun‐Ze Lai; Jia‐Yang Wu; Cheng‐Yu Peng; Chi‐Chun Chen. Realisation of three‐dimensional geometric model in case of bike frame measurement. IET Circuits, Devices & Systems 2020, 14, 713 -719.
AMA StyleHsiung‐Cheng Lin, Bo‐Ren Yu, Jen‐Yu Wang, Jun‐Ze Lai, Jia‐Yang Wu, Cheng‐Yu Peng, Chi‐Chun Chen. Realisation of three‐dimensional geometric model in case of bike frame measurement. IET Circuits, Devices & Systems. 2020; 14 (5):713-719.
Chicago/Turabian StyleHsiung‐Cheng Lin; Bo‐Ren Yu; Jen‐Yu Wang; Jun‐Ze Lai; Jia‐Yang Wu; Cheng‐Yu Peng; Chi‐Chun Chen. 2020. "Realisation of three‐dimensional geometric model in case of bike frame measurement." IET Circuits, Devices & Systems 14, no. 5: 713-719.
The impacts on the environment of many commercial products have not been fully considered in past years. For the sustainable development of Earth’s resources, future product design should move towards not only innovation, but also fundamentally in the green direction. Currently, the BioTRIZ method may provide a satisfactory solution for a single contradiction of green product design. However, if there are multiple contradictions existing due to multiple operational fields, difficulty in implementing design aspects may be posed. For this reason, this paper develops a BioTRIZ multi-contradiction resolution method targeting a green product design, which can find the crucial contradictions and thus achieve the necessary invention principles (IP). By summarizing the green factors and further dividing operational fields, the deduced matrix table becomes highly effective in the design. Accordingly, designers can be assisted to quickly find the operational fields under multiple contradictions. The effectiveness of the proposed method is verified using a product example of a window-cleaning robot design.
Zhonghang Bai; Lei Mu; Hsiung-Cheng Lin. Green Product Design Based on the BioTRIZ Multi-Contradiction Resolution Method. Sustainability 2020, 12, 4276 .
AMA StyleZhonghang Bai, Lei Mu, Hsiung-Cheng Lin. Green Product Design Based on the BioTRIZ Multi-Contradiction Resolution Method. Sustainability. 2020; 12 (10):4276.
Chicago/Turabian StyleZhonghang Bai; Lei Mu; Hsiung-Cheng Lin. 2020. "Green Product Design Based on the BioTRIZ Multi-Contradiction Resolution Method." Sustainability 12, no. 10: 4276.
Although the combined cooling, heating and power (CCHP) microgrid is feasible for achieving a high energy utilization efficiency, the fluctuation of energy sources, such as a photovoltaic system and multiple loads, may affect the safety, economics and stability in CCHP microgrid operation. For this reason, this paper establishes a mathematical model using a multi-objective optimization mechanism for resolving the influence of economy and energy allocation in the mixed photovoltaic type CCHP microgrid. It is based on analytic hierarchy process (AHP) to determine the individual weight of objective function optimization for the multi-objective power capacity allocation. The improved artificial bee colony (IABC) based on the whale search and dynamic selection probability can achieve an optimization solution, reaching a stable operation state and reasonable capacity configuration in the microgrid system. The performance results confirm that the proposed algorithm is superior to others in both convergence speed and accuracyfor the capacity allocation of the CCHP microgrid.
Huijuan Zhang; Zi Xie; Hsiung-Cheng Lin; Shaoyong Li. Power Capacity Optimization in a Photovoltaics-Based Microgrid Using the Improved Artificial Bee Colony Algorithm. Applied Sciences 2020, 10, 2990 .
AMA StyleHuijuan Zhang, Zi Xie, Hsiung-Cheng Lin, Shaoyong Li. Power Capacity Optimization in a Photovoltaics-Based Microgrid Using the Improved Artificial Bee Colony Algorithm. Applied Sciences. 2020; 10 (9):2990.
Chicago/Turabian StyleHuijuan Zhang; Zi Xie; Hsiung-Cheng Lin; Shaoyong Li. 2020. "Power Capacity Optimization in a Photovoltaics-Based Microgrid Using the Improved Artificial Bee Colony Algorithm." Applied Sciences 10, no. 9: 2990.
Currently, 3.6 V 700 mAh NiCd/NiMH battery is the most popular one used in emergency lights or other devices. It is well known that the state of health is related to the battery internal resistance and charging/discharging characteristics. However, the information needed may not be unveiled sufficiently from the manufactory although some certain specifications are provided. To provide users more accurate information, this system proposes an online battery quality measurement system based on two-pulse approach for internal resistance estimation along with long-term charging/discharging life cycle test. The measurement tasks are carried out using the microprocessor that connects with the computer via universal serial bus. Through the data acquisition system, every measured data from the microprocessor can be immediately transmitted to the data server via transmission control protocol/internet protocol. Accordingly, all testing results can be viewed online from the website, and their history record can be also tracked in the database. The experimental results verify that the proposed scheme can perform the quality measurement effectively and accurately.
Hsiung-Cheng Lin; Chao-Wei Wei; Hong-Ming Chen. Cell quality measurement using cloud computing in case of NiCd/NiMH battery study. Advanced Composites Letters 2020, 29, 1 .
AMA StyleHsiung-Cheng Lin, Chao-Wei Wei, Hong-Ming Chen. Cell quality measurement using cloud computing in case of NiCd/NiMH battery study. Advanced Composites Letters. 2020; 29 ():1.
Chicago/Turabian StyleHsiung-Cheng Lin; Chao-Wei Wei; Hong-Ming Chen. 2020. "Cell quality measurement using cloud computing in case of NiCd/NiMH battery study." Advanced Composites Letters 29, no. : 1.
Currently, the bike frame quality check (QC) mostly relies on human operation in industry. However, some drawbacks such as it being time-consuming, having low accuracy and involving non-computerized processes are still unavoidable. Apart from these problems,measured data are difficult to systematically analyze for tracking sources of product defects in the production process. For this reason, this paper aims to develop a 3D geometry mathematical model suitable for bicycle frames QC using robotic arm-based measurement. Unlike the traditional way to find coefficients of a space sphere, the proposed model requires only three check point coordinates to achieve the sphere axis coordinate and its radius. In the practical work, the contact sensor combined with the robotic arm is used to realize the compliance items measurement in shaft length, internal diameter, verticality, parallelism, etc. The proposed model is validated based on both mathematic verification and actual bike frame check.
Hsiung-Cheng Lin; Bo-Ren Yu; Jen-Yu Wang; Jun-Ze Lai; Jia-Yang Wu. Achievement of Accurate Robotic Arm-based Bike Frame Quality Check Using 3D Geometry Mathematical Model. Applied Sciences 2019, 9, 5355 .
AMA StyleHsiung-Cheng Lin, Bo-Ren Yu, Jen-Yu Wang, Jun-Ze Lai, Jia-Yang Wu. Achievement of Accurate Robotic Arm-based Bike Frame Quality Check Using 3D Geometry Mathematical Model. Applied Sciences. 2019; 9 (24):5355.
Chicago/Turabian StyleHsiung-Cheng Lin; Bo-Ren Yu; Jen-Yu Wang; Jun-Ze Lai; Jia-Yang Wu. 2019. "Achievement of Accurate Robotic Arm-based Bike Frame Quality Check Using 3D Geometry Mathematical Model." Applied Sciences 9, no. 24: 5355.
It is well known that the inherent instability of wind speed may jeopardize the safety and operation of wind power generation, consequently affecting the power dispatch efficiency in power systems. Therefore, accurate short-term wind speed prediction can provide valuable information to solve the wind power grid connection problem. For this reason, the optimization of feedforward (FF) neural networks using an improved flower pollination algorithm is proposed. First of all, the empirical mode decomposition method is devoted to decompose the wind speed sequence into components of different frequencies for decreasing the volatility of the wind speed sequence. Secondly, a back propagation neural network is integrated with the improved flower pollination algorithm to predict the changing trend of each decomposed component. Finally, the predicted values of each component can get into an overlay combination process and achieve the purpose of accurate prediction of wind speed. Compared with major existing neural network models, the performance tests confirm that the average absolute error using the proposed algorithm can be reduced up to 3.67%.
Yidi Ren; Hua Li; Hsiung-Cheng Lin. Optimization of Feedforward Neural Networks Using an Improved Flower Pollination Algorithm for Short-Term Wind Speed Prediction. Energies 2019, 12, 4126 .
AMA StyleYidi Ren, Hua Li, Hsiung-Cheng Lin. Optimization of Feedforward Neural Networks Using an Improved Flower Pollination Algorithm for Short-Term Wind Speed Prediction. Energies. 2019; 12 (21):4126.
Chicago/Turabian StyleYidi Ren; Hua Li; Hsiung-Cheng Lin. 2019. "Optimization of Feedforward Neural Networks Using an Improved Flower Pollination Algorithm for Short-Term Wind Speed Prediction." Energies 12, no. 21: 4126.
Hsiung-Cheng Lin; Ling-Ling Li; Vincent C. S. Lee. Multiple Autonomous Robots Coordination and Navigation. Journal of Robotics 2019, 2019, 1 -2.
AMA StyleHsiung-Cheng Lin, Ling-Ling Li, Vincent C. S. Lee. Multiple Autonomous Robots Coordination and Navigation. Journal of Robotics. 2019; 2019 ():1-2.
Chicago/Turabian StyleHsiung-Cheng Lin; Ling-Ling Li; Vincent C. S. Lee. 2019. "Multiple Autonomous Robots Coordination and Navigation." Journal of Robotics 2019, no. : 1-2.
Copper wire is a major conduction material that carries a variety of signals in industry. Presently, automatic wire elongating machines to produce very thin wiresare available for manufacturing. However, the original wires for the elongating process to thin sizes need heating, drawing and then threadingthrough the die molds by the manpower before the machine starts to work. This procedure repeatsuntil the wire threads through all various die molds. To replace the manpower, this paper aims to develop an automatic wire die molds threading system for the wire elongation process. Three pneumatic grippers are designed in the proposed system. The first gripper is used to clamp the wire. The second gripper fixed in the rotating mechanism is to draw the heated wire. The third gripper is used to move the wire for threading through the dies mold. The force designed for drawing the wire can be adjusted via the gear ratio. The experimental results confirm that the proposed system can accomplish the wiredies mold threading processin term of robustness, rapidness and accuracy.
Hsiung-Cheng Lin; Chung-Hao Cheng. Achievement of Automatic Copper Wire Elongation System. Algorithms 2019, 12, 105 .
AMA StyleHsiung-Cheng Lin, Chung-Hao Cheng. Achievement of Automatic Copper Wire Elongation System. Algorithms. 2019; 12 (5):105.
Chicago/Turabian StyleHsiung-Cheng Lin; Chung-Hao Cheng. 2019. "Achievement of Automatic Copper Wire Elongation System." Algorithms 12, no. 5: 105.
It is known that most of the renewable energy resources are the DC type. However, DC microgrids do not have zero crossing in current and voltage. This results in serious concerns about the circuit breaking and fault current limiting in the power system. Conventional thyristor-based DC fault current limiters (FCLs) may provide possible solutions for this problem. Unfortunately, a permanent interruption would arise on the system in case of a temporary fault. For this reason, this proposal aims to develop an integration system of the circuit breaker and FCL using a feedback-controlled zero-voltage switching method. In this proposed model, a load current is detected and an appropriate switch signal is thus generated by the controller based on the feedback-control strategy. Once the load current is beyond the predefined value, the switch will be opened to reduce the current immediately for a period of time set by the timer in advance. Then, the switch will be closed again to raise the current continuously until the overload threshold is reached. The switching transition duration is located at the resonant zero voltage, so that no switching power is required. Both simulation and practical performance results confirm that an expected constant load current can be well controlled over an expected range.
Hsiung‐Cheng Lin; Kai‐Chun Hsiao. Integration of DC circuit breaker and fault current limiter based on zero‐voltage resonant switching approach. IET Circuits, Devices & Systems 2019, 13, 344 -351.
AMA StyleHsiung‐Cheng Lin, Kai‐Chun Hsiao. Integration of DC circuit breaker and fault current limiter based on zero‐voltage resonant switching approach. IET Circuits, Devices & Systems. 2019; 13 (3):344-351.
Chicago/Turabian StyleHsiung‐Cheng Lin; Kai‐Chun Hsiao. 2019. "Integration of DC circuit breaker and fault current limiter based on zero‐voltage resonant switching approach." IET Circuits, Devices & Systems 13, no. 3: 344-351.
The rolling element bearing is one of the most critical components in a machine. Vibration signals resulting from these bearings imply important bearing defect information related to the machinery faults. Any defect in a bearing may cause a certain vibration with specific frequencies and amplitudes depending on the nature of the defect. Therefore, the vibration analysis plays a key role for fault detection, diagnosis, and prognosis to reach the reliability of the machines. Although fast Fourier transform for time–frequency analysis is still widely used in industry, it cannot extract enough frequencies without enough samples. If the real frequency does not match fast Fourier transform frequency grid exactly, the spectrum is spreading mostly among neighboring frequency bins. To resolve this drawback, the recent proposed enhanced fast Fourier transform algorithm was reported to improve this situation. This article reviews and compares both fast Fourier transform and enhanced fast Fourier transform for vibration signal analysis in both simulation and practical work. The comparative results verify that the enhanced fast Fourier transform can provide a better solution than traditional fast Fourier transform.
Hsiung-Cheng Lin; Yu-Chen Ye. Reviews of bearing vibration measurement using fast Fourier transform and enhanced fast Fourier transform algorithms. Advances in Mechanical Engineering 2019, 11, 1 .
AMA StyleHsiung-Cheng Lin, Yu-Chen Ye. Reviews of bearing vibration measurement using fast Fourier transform and enhanced fast Fourier transform algorithms. Advances in Mechanical Engineering. 2019; 11 (1):1.
Chicago/Turabian StyleHsiung-Cheng Lin; Yu-Chen Ye. 2019. "Reviews of bearing vibration measurement using fast Fourier transform and enhanced fast Fourier transform algorithms." Advances in Mechanical Engineering 11, no. 1: 1.
Electronic breakers or fuses are most widely used tools to protect the electric-driven facilities from overload or short circuit. However, they may suffer from two major drawbacks: (1) it normally takes more than 0.1 s to react, resulting in facilities not sufficiently protected, and (2) a higher rating size of breakers or fuses is demanded than expected due to lack of a surge current suppression mechanism. To overcome these problems, this paper proposes a fast large current electronic breaker based on the integration of current divider sensing and surge suppressing methods. The load surge current can be effectively suppressed by series negative temperature coefficient (NTC) thermistors. The load current is then divided into a small portion and converted to a voltage signal for amplification and comparison with the predefined threshold value, i.e., the maximum load tolerance current. AC power will be disconnected immediately by the switching circuit once the load current exceeds the tolerance value. The disconnection of power supply will continue for a period of time set by the timer. The experimental results verify that the proposed electronic breaker can provide a large load current protection up to 20 A under effective surge suppression within 10 ms.
Hsiung-Cheng Lin; Heng-Chuan Zo; Bo-Rong He. Advanced Fast Large Current Electronic Breaker Using Integration of Surge Current Suppression and Current Divider Sensing Methods. Journal of Sensors 2019, 2019, 1 -8.
AMA StyleHsiung-Cheng Lin, Heng-Chuan Zo, Bo-Rong He. Advanced Fast Large Current Electronic Breaker Using Integration of Surge Current Suppression and Current Divider Sensing Methods. Journal of Sensors. 2019; 2019 ():1-8.
Chicago/Turabian StyleHsiung-Cheng Lin; Heng-Chuan Zo; Bo-Rong He. 2019. "Advanced Fast Large Current Electronic Breaker Using Integration of Surge Current Suppression and Current Divider Sensing Methods." Journal of Sensors 2019, no. : 1-8.
Copper wire can be elongated to a very thin size like 0.01 mm from an original 0.6 mm via wire drawing dies. Although automatic machines are available for wire elongating process, the wire threading through dies still requires a human operation before entering an automation process. This procedure may repeat up to tens of times to complete, taking a long time. To resolve this problem, this paper develops an adjustable automatic wire copper wire drawing system for elongation using contactless heater. Three pneumatic claws are designed in the proposed system. The first claw is used to clamp the wire. The second claw fixed in the rotating mechanism is to draw the heated wire. The third claw is used to move the wire going through the drawing die after the drawn wire is cut off in one side. Then, the wire will be drawn again through the die mold. The force amount for drawing the wire can be adjusted via the gear connection controlled by the serer motor. Therefore, the system can be suited for variety of copper wire sizes. The experimental results prove that the proposed system has achieved the automatic copper wire elongation process successfully. Also, the human loading can be reduced considerably, and more importantly the operation time can be decreased significantly.
Hsiung-Cheng Lin; Jhih-Yao Hu; Chung-Hao Cheng. Enhancement of Copper Wire Lengthening Automatic System using Contactless Heater. International Journal of Networked and Distributed Computing 2019, 8, 9 -15.
AMA StyleHsiung-Cheng Lin, Jhih-Yao Hu, Chung-Hao Cheng. Enhancement of Copper Wire Lengthening Automatic System using Contactless Heater. International Journal of Networked and Distributed Computing. 2019; 8 (1):9-15.
Chicago/Turabian StyleHsiung-Cheng Lin; Jhih-Yao Hu; Chung-Hao Cheng. 2019. "Enhancement of Copper Wire Lengthening Automatic System using Contactless Heater." International Journal of Networked and Distributed Computing 8, no. 1: 9-15.
Automate guide vehicle (AGV) has been widely applied in industry. Therefore, it is important to design a highly efficient AGV. The path planning is known as one of the key factor for AGV operation. Although typical A-star algorithm with a heuristic mechanism can be used in the shortest path searching, it may suffer from broken lines and redundant nodes. In this paper, an improved A-star algorithm is presented. Based on the initial path planned by A-star algorithm, traversing all the nodes on an initial path and deleting unnecessary nodes and connections, the proposed model can remove the superfluous inflection points and redundant nodes effectively so that no obstacles exist during AGV moving. The performance results reveal that the proposed method can provide more efficient path planning with a shorter route and less turn times.
Yan Zhang; Ling-Ling Li; Hsiung-Cheng Lin; Zewen Ma; Jiang Zhao. Development of Path Planning Approach Based on Improved A-star Algorithm in AGV System. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018, 276 -279.
AMA StyleYan Zhang, Ling-Ling Li, Hsiung-Cheng Lin, Zewen Ma, Jiang Zhao. Development of Path Planning Approach Based on Improved A-star Algorithm in AGV System. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2018; ():276-279.
Chicago/Turabian StyleYan Zhang; Ling-Ling Li; Hsiung-Cheng Lin; Zewen Ma; Jiang Zhao. 2018. "Development of Path Planning Approach Based on Improved A-star Algorithm in AGV System." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 276-279.
The performance behavior of the lithium-ion battery can be simulated by the battery model and thus applied to a variety of practical situations. Although the particle swarm optimization (PSO) algorithm has been used for the battery model development, it is usually unable to find an optimal solution during the iteration process. To resolve this problem, an adaptive random disturbance PSO algorithm is proposed. The optimal solution can be updated continuously by obtaining a new random location around the particle’s historical optimal location. There are two conditions considered to perform the model process. Initially, the test operating condition is used to validate the model effectiveness. Secondly, the verification operating condition is used to validate the model generality. The performance results show that the proposed model can achieve higher precision in the lithium-ion battery behavior, and it is feasible for wide applications in industry.
Huang Kai; Guo Yong-Fang; Li Zhi-Gang; Lin Hsiung-Cheng; Hsiung-Cheng Lin. Development of Accurate Lithium-Ion Battery Model Based on Adaptive Random Disturbance PSO Algorithm. Mathematical Problems in Engineering 2018, 2018, 1 -13.
AMA StyleHuang Kai, Guo Yong-Fang, Li Zhi-Gang, Lin Hsiung-Cheng, Hsiung-Cheng Lin. Development of Accurate Lithium-Ion Battery Model Based on Adaptive Random Disturbance PSO Algorithm. Mathematical Problems in Engineering. 2018; 2018 ():1-13.
Chicago/Turabian StyleHuang Kai; Guo Yong-Fang; Li Zhi-Gang; Lin Hsiung-Cheng; Hsiung-Cheng Lin. 2018. "Development of Accurate Lithium-Ion Battery Model Based on Adaptive Random Disturbance PSO Algorithm." Mathematical Problems in Engineering 2018, no. : 1-13.
Traditional methods to protect the electric-driven facilities from overload or short circuit usually use electronic breaker or fuse. However, the reaction time for these devices normally require more than 0.1 s that may be not sufficiently fast to disconnect the power supply for protection. For this reason, this article develops a fast and simple electronic over-current protection circuit based on the current-adjustable sensing method. First, the load current is sensed and converted to a voltage signal using Hall sensor. Then, the signal is amplified and compared with the predefined threshold value, that is, the maximum tolerance current, using amplifier and comparator, respectively. The timer will generate a pulse signal input to the trigger circuit for rapidly switching off alternating current power once the load current exceeds the tolerance value. The alternating current power disconnection can continue for a period of time set by the timer in advance. The experimental results prove that the proposed circuit takes less than 10 ms and it is significantly fast to react for facility protection in time.
Hsiung-Cheng Lin; Bo-Rong He; Heng-Chuan Zo; Kai-Chun Hsiao. Development of fast electronic over-current protection circuit using current-adjustable sensing method. Advances in Mechanical Engineering 2018, 10, 1 .
AMA StyleHsiung-Cheng Lin, Bo-Rong He, Heng-Chuan Zo, Kai-Chun Hsiao. Development of fast electronic over-current protection circuit using current-adjustable sensing method. Advances in Mechanical Engineering. 2018; 10 (4):1.
Chicago/Turabian StyleHsiung-Cheng Lin; Bo-Rong He; Heng-Chuan Zo; Kai-Chun Hsiao. 2018. "Development of fast electronic over-current protection circuit using current-adjustable sensing method." Advances in Mechanical Engineering 10, no. 4: 1.
Traditional overload protection methods usually use either breakers or converters, focused on the side of power supply. However, these schemes may suffer from a slow response time or load dependence. Particularly, the facility may not be able to remain as a regular working condition when an overload occurs. To resolve this problem, the proposed feedback-controlling resonant switching algorithm aims to provide an expected load constant current to protect the load from overload without sacrifice for a normal load operation. On the basis of a negative feedback-control mechanism, the proposed model can detect the load current and thus generate an appropriate switch signal fast and accurately. The switch open period is decided by the model parameters and load current, and it can be set in advance by the timer. On the other hand, the switch closed period is determined by the expected load current that is independent on the load size. The switching acts at the resonant zero-voltage point, so that no power is consumed during the switching action. The performance simulation with DC 28 V supply confirms that the proposed model can maintain a predefined load constant current for an overload protection effectively.
Hsiung‐Cheng Lin; Kai‐Chun Hsiao. Development of load constant current model using feedback‐controlling resonant switching algorithm for overload protection. IET Circuits, Devices & Systems 2017, 11, 656 -665.
AMA StyleHsiung‐Cheng Lin, Kai‐Chun Hsiao. Development of load constant current model using feedback‐controlling resonant switching algorithm for overload protection. IET Circuits, Devices & Systems. 2017; 11 (6):656-665.
Chicago/Turabian StyleHsiung‐Cheng Lin; Kai‐Chun Hsiao. 2017. "Development of load constant current model using feedback‐controlling resonant switching algorithm for overload protection." IET Circuits, Devices & Systems 11, no. 6: 656-665.