scholarly journals Power efficiency estimation based health monitoring and fault detection of modular and reconfigurable robot

2021 ◽  
Author(s):  
Jing Yaun
Keyword(s):  
Fault Detection ◽  
Health Monitoring ◽  
Power Efficiency ◽  
Joint Torque ◽  
Robot System ◽  
Operation Conditions ◽  
Efficiency Estimation ◽  
Joint Torque Sensor ◽  
Reconfigurable Robot ◽  
Critical Components

Power efficiency degradation of machines often provides intrinsic indication of problems associated with their operation conditions. Inspired by this observation, in this thesis work, a simple yet effective power efficiency estimation base health monitoring and fault detection technique is proposed for modular and reconfigurable robot with joint torque sensor. The design of the Ryerson modular and reconfigurable robot system is first introduced, which aims to achieve modularity and compactness of the robot modules. Critical components, such as the joint motor, motor driver, harmonic drive, sensors, and joint brake, have been selected according to the requirement. Power efficiency coefficients of each joint module are obtained using sensor measurements and used directly for health monitoring and fault detection. The proposed method has been experimentally tested on the developed modular and reconfigurable robot with joint torque sensing and a distributed control system. Experimental results have demonstrated the effectiveness of the proposed method.

scholarly journals Power efficiency estimation based health monitoring and fault detection of modular and reconfigurable robot

2021 ◽  
Author(s):  
Jing Yaun
Keyword(s):  
Fault Detection ◽  
Health Monitoring ◽  
Power Efficiency ◽  
Joint Torque ◽  
Robot System ◽  
Operation Conditions ◽  
Efficiency Estimation ◽  
Joint Torque Sensor ◽  
Reconfigurable Robot ◽  
Critical Components

Power efficiency degradation of machines often provides intrinsic indication of problems associated with their operation conditions. Inspired by this observation, in this thesis work, a simple yet effective power efficiency estimation base health monitoring and fault detection technique is proposed for modular and reconfigurable robot with joint torque sensor. The design of the Ryerson modular and reconfigurable robot system is first introduced, which aims to achieve modularity and compactness of the robot modules. Critical components, such as the joint motor, motor driver, harmonic drive, sensors, and joint brake, have been selected according to the requirement. Power efficiency coefficients of each joint module are obtained using sensor measurements and used directly for health monitoring and fault detection. The proposed method has been experimentally tested on the developed modular and reconfigurable robot with joint torque sensing and a distributed control system. Experimental results have demonstrated the effectiveness of the proposed method.

scholarly journals Multiple Working Mode Based Door Opening Control and Fault Detection of Mobile Modular and Reconfigurable Robot

2021 ◽  
Author(s):  
Saleh Ahmad Ali
Keyword(s):  
Fault Detection ◽  
Control Design ◽  
Torque Control ◽  
Experimental Results ◽  
Joint Torque ◽  
Detection Scheme ◽  
Door Opening ◽  
Position Errors ◽  
Internal Forces ◽  
Reconfigurable Robot

The study in this thesis addresses the problem of opening a door with a modular and reconfigurable robot (MRR) mounted on a wheeled mobile robot platform. The foremost issue with door opening problems is the prevention of occurrence of large internal forces that arise due to position errors or imprecise modeling of the robot or its environment, i.e. the door parameters, specifically. Unlike previous methods that relied on compliance control, making the control design rather complicated, this thesis presents a new concept that utilizes the multiple working modes of the MRR modules. The control design is significantly simplified by switching selected joints of the MRR to work in passive mode during door opening operation. As a result, the occurrence of large internal forces is prevented. Different control schemes are used for control of the joint modules in different working modes. For passive joint modules, a feedforward torque control approach is used to compensate the joint friction to ensure passive motion. For the active joint modules, a distributed control method, based on torque sensing, is used to facilitate the control of joint modules working under this mode. To enable autonomous door opening, an online door parameter estimation algorithm is proposed on the basis of the least squares method; and a path planning algorithm is developed on the basis of Hermite cubic spline functions, with consideration of motion constraints of the mobile MRR. The theory is validated using simulations and experimental results, as presented herein. A distributed fault detection scheme for MRR robots with joint torque sensing is also proposed in this thesis. The proposed scheme relies on filtering the joint torque command and comparing it with a filtered torque estimate that is derived from the nonlinear dynamic model of MRR with joint torque sensing. Common joint actuator faults are considered with fault detection being performed independently for each joint module. The proposed fault detection scheme for each module does not require motion states of any other module, making it an ideal modular approach for fault detection of modular robots. Experimental results have attested the effectiveness of the proposed fault detection scheme.

Distributed control of modular and reconfigurable robot with torque sensing

Robotica ◽  
2008 ◽  
Vol 26 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Guangjun Liu ◽  
Sajan Abdul ◽  
Andrew A. Goldenberg
Keyword(s):  
Distributed Control ◽  
Control Method ◽  
Joint Torque ◽  
Control Technique ◽  
Model Uncertainties ◽  
Robust Controller ◽  
Joint Friction ◽  
Reconfigurable Robots ◽  
Joint Torque Sensor ◽  
Reconfigurable Robot

SUMMARYA major technical challenge in controlling modular and reconfigurable robots is associated with the kinematics and dynamic model uncertainties caused by reconfiguration. In parallel, conventional model uncertainties such as uncompensated joint friction still persist. This paper presents a modular distributed control technique for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under the proposed control method that is based on joint torque sensing, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need to adjust control parameters of the other modules of the robot. Model uncertainties associated with link and payload masses are compensated using joint torque sensor measurement. The remaining model uncertainties, including uncompensated dynamic coupling and joint friction, are compensated by a decomposition-based robust controller. Simulation results have confirmed the effectiveness of the proposed method.

scholarly journals Multiple Working Mode Based Door Opening Control and Fault Detection of Mobile Modular and Reconfigurable Robot

2021 ◽  
Author(s):  
Saleh Ahmad Ali
Keyword(s):  
Fault Detection ◽  
Control Design ◽  
Torque Control ◽  
Experimental Results ◽  
Joint Torque ◽  
Detection Scheme ◽  
Door Opening ◽  
Position Errors ◽  
Internal Forces ◽  
Reconfigurable Robot

The study in this thesis addresses the problem of opening a door with a modular and reconfigurable robot (MRR) mounted on a wheeled mobile robot platform. The foremost issue with door opening problems is the prevention of occurrence of large internal forces that arise due to position errors or imprecise modeling of the robot or its environment, i.e. the door parameters, specifically. Unlike previous methods that relied on compliance control, making the control design rather complicated, this thesis presents a new concept that utilizes the multiple working modes of the MRR modules. The control design is significantly simplified by switching selected joints of the MRR to work in passive mode during door opening operation. As a result, the occurrence of large internal forces is prevented. Different control schemes are used for control of the joint modules in different working modes. For passive joint modules, a feedforward torque control approach is used to compensate the joint friction to ensure passive motion. For the active joint modules, a distributed control method, based on torque sensing, is used to facilitate the control of joint modules working under this mode. To enable autonomous door opening, an online door parameter estimation algorithm is proposed on the basis of the least squares method; and a path planning algorithm is developed on the basis of Hermite cubic spline functions, with consideration of motion constraints of the mobile MRR. The theory is validated using simulations and experimental results, as presented herein. A distributed fault detection scheme for MRR robots with joint torque sensing is also proposed in this thesis. The proposed scheme relies on filtering the joint torque command and comparing it with a filtered torque estimate that is derived from the nonlinear dynamic model of MRR with joint torque sensing. Common joint actuator faults are considered with fault detection being performed independently for each joint module. The proposed fault detection scheme for each module does not require motion states of any other module, making it an ideal modular approach for fault detection of modular robots. Experimental results have attested the effectiveness of the proposed fault detection scheme.

scholarly journals Early Fault Detection of Wind Turbines Based on Operational Condition Clustering and Optimized Deep Belief Network Modeling

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 984 ◽  
Author(s):  
Hong Wang ◽  
Hongbin Wang ◽  
Guoqian Jiang ◽  
Jimeng li ◽  
Yueling Wang
Keyword(s):  
Fault Detection ◽  
Wind Turbines ◽  
Health Monitoring ◽  
Deep Belief Network ◽  
Operating Conditions ◽  
Behavior Modeling ◽  
Operation Condition ◽  
Belief Network ◽  
Operation Conditions ◽  
Early Fault Detection

Health monitoring and early fault detection of wind turbines have attracted considerable attention due to the benefits of improving reliability and reducing the operation and maintenance costs of the turbine. However, dynamic and constantly changing operating conditions of wind turbines still pose great challenges to effective and reliable fault detection. Most existing health monitoring approaches mainly focus on one single operating condition, so these methods cannot assess the health status of turbines accurately, leading to unsatisfactory detection performance. To this end, this paper proposes a novel general health monitoring framework for wind turbines based on supervisory control and data acquisition (SCADA) data. A key feature of the proposed framework is that it first partitions the turbine operation into multiple sub-operation conditions by the clustering approach and then builds a normal turbine behavior model for each sub-operation condition. For normal behavior modeling, an optimized deep belief network is proposed. This optimized modeling method can capture the sophisticated nonlinear correlations among different monitoring variables, which is helpful to enhance the prediction performance. A case study of main bearing fault detection using real SCADA data is used to validate the proposed approach, which demonstrates its effectiveness and advantages.

scholarly journals Robust Control Based on Joint Torque Sensor Information for Robot Manipulators

1991 ◽  
Vol 27 (6) ◽  
pp. 693-699
Author(s):  
Junichi IMURA ◽  
Toshiharu SUGIE ◽  
Yasuyoshi YOKOKOHJI ◽  
Tsuneo YOSHIKAWA
Keyword(s):  
Robust Control ◽  
Robot Manipulators ◽  
Joint Torque ◽  
Torque Sensor ◽  
Joint Torque Sensor ◽  
Sensor Information

Research on WSNs Topology and Application of Lightning Monitoring in Distribution Lines

2012 ◽  
Vol 433-440 ◽  
pp. 5573-5578
Author(s):  
Tie Liu Wang ◽  
Si Lei Shen ◽  
Jun Jie Wang
Keyword(s):  
Wireless Sensor Network ◽  
Fault Diagnosis ◽  
Sensor Network ◽  
Health Monitoring ◽  
Routing Protocol ◽  
Power Efficiency ◽  
Wireless Sensor ◽  
Environmental Sampling ◽  
Distribution Lines ◽  
Distribution Line

Wireless Sensor Network (WSN) is used for such tasks as surveillance, widespread environmental sampling, security, and health monitoring widely. In this paper, a WSNs topology is proposed for lightning monitoring of distribution lines, which decides the number of nodes, routing protocol and power efficiency. The WSNs is deployed along the distribution line with nodes mounted on tall towers, which is used to monitor the lightning activities and accomplish fault diagnosis. At last, a monitoring system based on WSN is fabricated.

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