The Development of a Fault Detection and Identification System for Executive Units of Manipulators Using Technical Vision

Alexander, Priscilla

doi:10.1109/fareastcon50210.2020.9271544

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…First, video and visual input and recording might be implemented by putting a high-speed camera at the tip of the robot arm as an added sensor for tracking. The extracted data from raw images and videos will undergo image processing technique into a type of visual force to suppress the signal error and remove the unwanted noise [10]. Besides, the relevant data gained from the pictorial records will be utilised to increase the coordination of the system"s trajectory [11].…”

Section: Discussionmentioning

confidence: 99%

Adaptive Trajectory Control Design for Bilateral Robotic Arm with Enforced Sensorless and Acceleration based Force Control Technique

Mansor¹,

Jamaluddin²,

Shukor³

2021

IJACSA

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This study offers an approach for tackling the issue of instability on the computed force generated on a joint of a robotic arm by improving the model of a bilateral master-slave haptic system with an adaptive technique known as Reaction Force Observer (RFOB). The purpose of recommended modelling is to correct unsought signals coming from the employed standard controller and the surroundings produced within the moving joint of the articulated robotic arm. RFOB is employed to adjust the signal interference by modifying its position response to obtain the desired final location. The investigation and observation were carried out in two separate tests to evaluate the outcomes of the recommended integration technique with the former system that only enforced Disturbance Observer (DOB). Generated feedbacks produced from the organised experiments are measured inside a simulation platform. All numerical records and signal charts illustrate the durability of the proposed method since the system integrated with acceleration-based force control is more precise and quicker.

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Section: Discussionmentioning

confidence: 99%

Adaptive Trajectory Control Design for Bilateral Robotic Arm with Enforced Sensorless and Acceleration based Force Control Technique

Mansor¹,

Jamaluddin²,

Shukor³

2021

IJACSA

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“…Ref. [8] proposes the use of embedded machine vision and observers to aid diagnosis. The specific method is to identify the position of the end-effector by means of a stereo camera, which has the advantages of simple implementation, high accuracy of typical fault detection, and elimination of the need to use additional sensors.…”

Section: Introductionmentioning

confidence: 99%

Neural Network-Enhanced Fault Diagnosis of Robot Joints

Zhang,

Zhu

2023

Algorithms

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Industrial robots play an indispensable role in flexible production lines, and the faults caused by degradation of equipment, motors, mechanical system joints, and even task diversity affect the efficiency of production lines and product quality. Aiming to achieve high-precision multiple size of fault diagnosis of robotic arms, this study presents a back propagation (BP) multiclassification neural network-based method for robotic arm fault diagnosis by taking feature fusion of position, attitude and acceleration of UR10 robotic arm end-effector to establish the database for neural network training. The new algorithm achieves an accuracy above 95% for fault diagnosis of each joint, and a diagnostic accuracy of up to 0.1 degree. It should be noted that the fault diagnosis algorithm can detect faults effectively in time, while avoiding complex mathematical operations.

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