Automated inspection has proven to be the most effective approach to maintaining quality in indus... more Automated inspection has proven to be the most effective approach to maintaining quality in industrial-scale manufacturing. This study employed the eye-in-hand architecture in conjunction with deep learning and convolutional neural networks to automate the detection of defects in forged aluminum rims for electric vehicles. RobotStudio software was used to simulate the environment and path trajectory for a camera installed on an ABB robot arm to capture 3D images of the rims. Four types of surface defects were examined: (1) dirt spots, (2) paint stains, (3) scratches, and (4) dents. Generative adversarial network (GAN) and deep convolutional generative adversarial networks (DCGAN) were used to generate additional images to expand the depth of the training dataset. We also developed a graphical user interface and software system to mark patterns associated with defects in the images. The defect detection algorithm based on YOLO algorithms made it possible to obtain results more quickl...
2018 13th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT), 2018
paper presented the proximity capacitive sensor using recursive Chebyshev neural network (RCNN) t... more paper presented the proximity capacitive sensor using recursive Chebyshev neural network (RCNN) to detect user gesture. The human interactive gesture signal analyses have been a research topic smart home fields that algorithms build in local device to recognize real time. The neural network have been used in many fields that including identification, control and classification. The features of RCNN have Chebyshev polynomials to train and map different capacitance input value. Moreover, the recursive weight record previous signal to add learn procession. Therefore, the RCNN methods to identify user gesture has satisfactory response.
2018 7th International Symposium on Next Generation Electronics (ISNE), 2018
This paper presented a rotation memory neural network identify elders fall situation in wearable ... more This paper presented a rotation memory neural network identify elders fall situation in wearable device. The older human signal analysis have been a research topic health care fields that algorithms build in wearable device real time detect fall situation. However, the wearable device system code size is limited. Therefore, we utilize rotation memory methods to adjust weight that simplify tradition self-organizing neural network. In the experimental results, the rotation memory neural network identify human fall signal. In addition, we used wearable device combined BLE (Bluetooth low energy) feedback output response real time.
Motion control is an essential part of industrial machinery and manufacturing systems. In this pa... more Motion control is an essential part of industrial machinery and manufacturing systems. In this paper, the adaptive fuzzy controller is designed to the position control of X-Y linear stage for precision motion and trajectory tracking control. The direct fuzzy controller controller is developed to demonstrate the feasibility to track a reference trajectory. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system and the free parameters of the adaptive fuzzy controller can be tuned on-line by an output feedback control law. The simulation results are presented to verify the tracking performances of the proposed controllers.
2018 7th International Symposium on Next Generation Electronics (ISNE), 2018
This paper presented a Laypunov base fuzzy expert knowledge model identify human fall signal in w... more This paper presented a Laypunov base fuzzy expert knowledge model identify human fall signal in wearable device. The older human signal analysis have been a research topic health care fields that algorithms build in wearable device real time detect fall situation. The fuzzy expert knowledge model used knowledge base to identify human fall situation, and we also combined Lyapunov convergent theories to adjust knowledge base. In the experimental results, the fuzzy expert knowledge model analysis human fall signal. In addition, we used wearable device combined BLE (Bluetooth low energy) feedback output response real time.
Synchronized motion control with high accuracy becomes very essential part in industry. Due to so... more Synchronized motion control with high accuracy becomes very essential part in industry. Due to some possible effect such as unknown disturbance or unmatched system model, it is difficult to obtain the precision of synchronous control using the conventional proportional–integral control method with parallel architecture. The adaptive compensator must be employed to eliminate tracking errors. The objective of this research is to propose the modified cross-coupling architecture using single-neuron proportional–integral controller and a synchronous compensator for dual-axis linear actuator. The single-neuron proportional–integral control strategy with delta learning algorithm can adjust the weighting coefficients of controllers to provide the robustness for each single-axis DC linear actuator system. A back-propagation neural network compensator is designed to adaptively reduce position and velocity errors between the two-axis servo systems. Both simulation and experimental results are ...
Motion control is an essential part of industrial machinery and manufacturing systems. In this ar... more Motion control is an essential part of industrial machinery and manufacturing systems. In this article, the adaptive fuzzy controller is proposed for precision trajectory tracking control in biaxial X-Y motion stage system. The theoretical analyses of direct fuzzy control which is insensitive to parameter uncertainties and external load disturbances are derived to demonstrate the feasibility to track the reference trajectories. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system, and all the signals are bounded in the closed-loop system. The intelligent position controller combines the merits of the adaptive fuzzy control with robust characteristics and learning ability for periodic command tracking of a servo drive mechanism. The simulation and experimental results on square, triangle, star, and circle reference contours are presented to show that the proposed controller indeed accomplishes the better tracking performances with regar...
High-precision trajectory control is considered as an important factor in the performance of indu... more High-precision trajectory control is considered as an important factor in the performance of industrial two-axis contour motion systems. This research presents an adaptive direct fuzzy cerebellar model articulation controller (CMAC) sliding mode control (DFCMACSMC) for the precise control of the industrial XY-axis motion system. The FCMAC was utilized to approximate an ideal controller, and the weights of FCMAC were on-line tuned by the derived adaptive law based on the Lyapunov criterion. With this derivation in mind, the asymptotic stability of the developed motion system could be guaranteed. The two-axis stage system was experimentally investigated using four contours, namely, circle, bowknot, heart, and star reference contours. The experimental results indicate that the proposed DFCMACSMC method achieved the improved tracking capability, and so reveal that the DFCMACSMC scheme outperformed other schemes of the model uncertainties and cross-coupling interference.
2021 IEEE 3rd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS), 2021
As society gradually relies on technologies to prevent dangers and detect the environment, the pr... more As society gradually relies on technologies to prevent dangers and detect the environment, the processing of data transmission and analysis becomes important. In recent years, firefighters are sacrificed during rescue missions. Even with the high-tech equipment in the current era, the lives of firefighters are not prevented in the fire scene. Thus, this research designs and develops an alarm system for hospitals and schools. The Message Queuing Telemetry Transport (MQTT) technology and fire sensors are utilized and integrated to extract the conditions of the environment. In the system, the subscriber server collects the data on a personal computer. Also, the website and database server monitor the wards in a hospital. Integrating and designing the systems help to understand the emergent situation.
In this paper, a multipath mitigation tracking system is presented for static GPS applications. I... more In this paper, a multipath mitigation tracking system is presented for static GPS applications. It is comprised of four function blocks, those being (1) adaptive path estimator (APE), (2) multipath interference reproducer (MPIR), (3) Rake-based delay locked loop (RB-DLL), and (4) Rake-based phase locked loop (RB-PLL). Only the short delay condition with delay less than 1.5 PN chip is considered here, because GPS pseudorange error envelope decreases to zero for delay time greater than 1.5 PN chip. In order to estimate reflection profile in the correlation domain, the FFT-based circular correlation and block average method (BAM) are utilized to offer significant savings in computational complexity. The APE estimates the delayed profiles and coefficients of the reflection signals. With the path parameters from APE, the corresponding multipath arms are activated to accomplish the multipath reproduction. These replica profiles are used for subtracting the reflection components from carri...
Gantry systems in which two linear motors are used to drive a single axis provide flexible and ef... more Gantry systems in which two linear motors are used to drive a single axis provide flexible and efficient solutions for a wide range of material handling applications. It is an important issue to find a way to drive the parallel stage to achieve a synchronous motion effectively and precisely. In this research, the proportional–integral–derivative–type fuzzy controller structure is presented for precision trajectory tracking control in synchronized XY motion gantry stage system. Three proportional–integral–derivative–type fuzzy controllers are designed for each axis, and the complete membership functions and rule table are developed to fulfill the better tracking capability. The controller parameters, which include the scaling factor of fuzzy rules and proportional–integral structures, are searched using the cross-mixing global artificial bee colony algorithm. The algorithm can optimize these parameters based on the integral of the time-weighted absolute error criterion. MATLAB system...
Automated inspection has proven to be the most effective approach to maintaining quality in indus... more Automated inspection has proven to be the most effective approach to maintaining quality in industrial-scale manufacturing. This study employed the eye-in-hand architecture in conjunction with deep learning and convolutional neural networks to automate the detection of defects in forged aluminum rims for electric vehicles. RobotStudio software was used to simulate the environment and path trajectory for a camera installed on an ABB robot arm to capture 3D images of the rims. Four types of surface defects were examined: (1) dirt spots, (2) paint stains, (3) scratches, and (4) dents. Generative adversarial network (GAN) and deep convolutional generative adversarial networks (DCGAN) were used to generate additional images to expand the depth of the training dataset. We also developed a graphical user interface and software system to mark patterns associated with defects in the images. The defect detection algorithm based on YOLO algorithms made it possible to obtain results more quickl...
2018 13th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT), 2018
paper presented the proximity capacitive sensor using recursive Chebyshev neural network (RCNN) t... more paper presented the proximity capacitive sensor using recursive Chebyshev neural network (RCNN) to detect user gesture. The human interactive gesture signal analyses have been a research topic smart home fields that algorithms build in local device to recognize real time. The neural network have been used in many fields that including identification, control and classification. The features of RCNN have Chebyshev polynomials to train and map different capacitance input value. Moreover, the recursive weight record previous signal to add learn procession. Therefore, the RCNN methods to identify user gesture has satisfactory response.
2018 7th International Symposium on Next Generation Electronics (ISNE), 2018
This paper presented a rotation memory neural network identify elders fall situation in wearable ... more This paper presented a rotation memory neural network identify elders fall situation in wearable device. The older human signal analysis have been a research topic health care fields that algorithms build in wearable device real time detect fall situation. However, the wearable device system code size is limited. Therefore, we utilize rotation memory methods to adjust weight that simplify tradition self-organizing neural network. In the experimental results, the rotation memory neural network identify human fall signal. In addition, we used wearable device combined BLE (Bluetooth low energy) feedback output response real time.
Motion control is an essential part of industrial machinery and manufacturing systems. In this pa... more Motion control is an essential part of industrial machinery and manufacturing systems. In this paper, the adaptive fuzzy controller is designed to the position control of X-Y linear stage for precision motion and trajectory tracking control. The direct fuzzy controller controller is developed to demonstrate the feasibility to track a reference trajectory. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system and the free parameters of the adaptive fuzzy controller can be tuned on-line by an output feedback control law. The simulation results are presented to verify the tracking performances of the proposed controllers.
2018 7th International Symposium on Next Generation Electronics (ISNE), 2018
This paper presented a Laypunov base fuzzy expert knowledge model identify human fall signal in w... more This paper presented a Laypunov base fuzzy expert knowledge model identify human fall signal in wearable device. The older human signal analysis have been a research topic health care fields that algorithms build in wearable device real time detect fall situation. The fuzzy expert knowledge model used knowledge base to identify human fall situation, and we also combined Lyapunov convergent theories to adjust knowledge base. In the experimental results, the fuzzy expert knowledge model analysis human fall signal. In addition, we used wearable device combined BLE (Bluetooth low energy) feedback output response real time.
Synchronized motion control with high accuracy becomes very essential part in industry. Due to so... more Synchronized motion control with high accuracy becomes very essential part in industry. Due to some possible effect such as unknown disturbance or unmatched system model, it is difficult to obtain the precision of synchronous control using the conventional proportional–integral control method with parallel architecture. The adaptive compensator must be employed to eliminate tracking errors. The objective of this research is to propose the modified cross-coupling architecture using single-neuron proportional–integral controller and a synchronous compensator for dual-axis linear actuator. The single-neuron proportional–integral control strategy with delta learning algorithm can adjust the weighting coefficients of controllers to provide the robustness for each single-axis DC linear actuator system. A back-propagation neural network compensator is designed to adaptively reduce position and velocity errors between the two-axis servo systems. Both simulation and experimental results are ...
Motion control is an essential part of industrial machinery and manufacturing systems. In this ar... more Motion control is an essential part of industrial machinery and manufacturing systems. In this article, the adaptive fuzzy controller is proposed for precision trajectory tracking control in biaxial X-Y motion stage system. The theoretical analyses of direct fuzzy control which is insensitive to parameter uncertainties and external load disturbances are derived to demonstrate the feasibility to track the reference trajectories. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system, and all the signals are bounded in the closed-loop system. The intelligent position controller combines the merits of the adaptive fuzzy control with robust characteristics and learning ability for periodic command tracking of a servo drive mechanism. The simulation and experimental results on square, triangle, star, and circle reference contours are presented to show that the proposed controller indeed accomplishes the better tracking performances with regar...
High-precision trajectory control is considered as an important factor in the performance of indu... more High-precision trajectory control is considered as an important factor in the performance of industrial two-axis contour motion systems. This research presents an adaptive direct fuzzy cerebellar model articulation controller (CMAC) sliding mode control (DFCMACSMC) for the precise control of the industrial XY-axis motion system. The FCMAC was utilized to approximate an ideal controller, and the weights of FCMAC were on-line tuned by the derived adaptive law based on the Lyapunov criterion. With this derivation in mind, the asymptotic stability of the developed motion system could be guaranteed. The two-axis stage system was experimentally investigated using four contours, namely, circle, bowknot, heart, and star reference contours. The experimental results indicate that the proposed DFCMACSMC method achieved the improved tracking capability, and so reveal that the DFCMACSMC scheme outperformed other schemes of the model uncertainties and cross-coupling interference.
2021 IEEE 3rd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS), 2021
As society gradually relies on technologies to prevent dangers and detect the environment, the pr... more As society gradually relies on technologies to prevent dangers and detect the environment, the processing of data transmission and analysis becomes important. In recent years, firefighters are sacrificed during rescue missions. Even with the high-tech equipment in the current era, the lives of firefighters are not prevented in the fire scene. Thus, this research designs and develops an alarm system for hospitals and schools. The Message Queuing Telemetry Transport (MQTT) technology and fire sensors are utilized and integrated to extract the conditions of the environment. In the system, the subscriber server collects the data on a personal computer. Also, the website and database server monitor the wards in a hospital. Integrating and designing the systems help to understand the emergent situation.
In this paper, a multipath mitigation tracking system is presented for static GPS applications. I... more In this paper, a multipath mitigation tracking system is presented for static GPS applications. It is comprised of four function blocks, those being (1) adaptive path estimator (APE), (2) multipath interference reproducer (MPIR), (3) Rake-based delay locked loop (RB-DLL), and (4) Rake-based phase locked loop (RB-PLL). Only the short delay condition with delay less than 1.5 PN chip is considered here, because GPS pseudorange error envelope decreases to zero for delay time greater than 1.5 PN chip. In order to estimate reflection profile in the correlation domain, the FFT-based circular correlation and block average method (BAM) are utilized to offer significant savings in computational complexity. The APE estimates the delayed profiles and coefficients of the reflection signals. With the path parameters from APE, the corresponding multipath arms are activated to accomplish the multipath reproduction. These replica profiles are used for subtracting the reflection components from carri...
Gantry systems in which two linear motors are used to drive a single axis provide flexible and ef... more Gantry systems in which two linear motors are used to drive a single axis provide flexible and efficient solutions for a wide range of material handling applications. It is an important issue to find a way to drive the parallel stage to achieve a synchronous motion effectively and precisely. In this research, the proportional–integral–derivative–type fuzzy controller structure is presented for precision trajectory tracking control in synchronized XY motion gantry stage system. Three proportional–integral–derivative–type fuzzy controllers are designed for each axis, and the complete membership functions and rule table are developed to fulfill the better tracking capability. The controller parameters, which include the scaling factor of fuzzy rules and proportional–integral structures, are searched using the cross-mixing global artificial bee colony algorithm. The algorithm can optimize these parameters based on the integral of the time-weighted absolute error criterion. MATLAB system...
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Papers by Wei-lung Mao