Fault Diagnosis of a Reconfigurable Crawling–Rolling Robot Based on Support Vector Machines

Elangovan, Karthikeyan; Tamilselvam, Yokhesh Krishnasamy; Elara, Mohan Rajesh; Iwase, Masami; Nemoto, Takuma; Wood, Kristin L.

doi:10.3390/app7101025

Cited by 28 publications

(19 citation statements)

References 20 publications

(10 reference statements)

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“…The residual signals obtained for normal and abnormal conditions are utilized for the FDI of the robot manipulator. First, numerical attributes such as feature parameters are used for SVM-based FDI [20][21][22][23][24][25]. Various types of features can be used.…”

Section: Fault Diagnosis Using Support Vector Machinementioning

confidence: 99%

“…5 Increase the fault estimation reliability and accuracy in the NHVSO with the ANHVSO (18,20,21). 6 Run the residual signal characterization by energy (22,23).…”

Section: Fault Detection and Fault Identificationmentioning

confidence: 99%

“…To avoid these issues and to address the problem of fault diagnosis, the support vector machines (SVMs) [20][21][22][23] machine learning algorithm is utilized in this paper. This algorithm has a strong mathematical background, and better addresses feature dimensionality due to the availability of the different types of kernels that can be used for training.…”

Section: Introductionmentioning

confidence: 99%

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An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

et al. 2020

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A robot manipulator is a multi-degree-of-freedom and nonlinear system that is used in various applications, including the medical area and automotive industries. Uncertain conditions in which a robot manipulator operates, as well as its nonlinearities, represent challenges for fault diagnosis and fault-tolerant control (FDC) that are addressed through the proposed FDC technique. A machine-learning-based neural adaptive, high-order, variable structure observer for fault diagnosis (FD) and adaptive, modern, fuzzy, backstepping, variable structure control for use in a fault-tolerant control (FC) algorithm, are proposed in this paper. In the first stage, a variable structure observer is proposed as an FD technique for the robot manipulator. The chattering phenomenon associated with the variable structure observer(VSO) is solved using a high-order variable structure observer. Then, the dynamic behavior estimation performance in the high-order variable structure observer is improved by incorporating a neural network algorithm in the FD pipeline. This adaptive technique is also effective in improving the robustness of the fault signal estimation. Moreover, support vector machines (SVMs) that can derive adaptive threshold values are used to categorize faults. To design an effective fault-tolerant controller (FC), an adaptive modern fuzzy backstepping variable structure controller is used in this study. First, a new variable structure controller is designed. Next, to increase robustness and reduce high-frequency oscillations in uncertain conditions, a backstepping algorithm is used in parallel with the variable structure controller to design the backstepping variable structure controller. To design an effective hybrid controller, a fuzzy algorithm is integrated into the backstepping variable structure controller to create a fuzzy backstepping variable structure controller. Then, to improve the robustness and reliability of the FC, a neural adaptive. high-order. variable structure observer is applied to the fuzzy backstepping variable structure controller to design a modern fuzzy backstepping variable structure controller. An adaptive algorithm is used to fine-tune the variable structure coefficients and reduce the effect of faults on the robot manipulator. The effectiveness of the selected algorithm is validated using a PUMA robot manipulator. The neural adaptive. high-order variable structure observer improves the average performance for the identification of various faults by about 27% and 29.2%, compared with the neural high-order variable structure observer and variable structure observer, respectively.

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Section: Fault Diagnosis Using Support Vector Machinementioning

confidence: 99%

“…5 Increase the fault estimation reliability and accuracy in the NHVSO with the ANHVSO (18,20,21). 6 Run the residual signal characterization by energy (22,23).…”

Section: Fault Detection and Fault Identificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

et al. 2020

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“…Inertial measurement units (IMUs) have been widely used in mobile robot navigation [31][32][33], and can be used to make portable rehabilitation devices. IMU devices measure acceleration, angular rates, and magnetic field vectors in their own three-dimensional local coordinate system, and, with proper calibration, represent an orthonormal base that is aligned with the outer sensor casing [34].…”

Section: Inertial Measurement Unitsmentioning

confidence: 99%

Foot-Mounted Inertial Measurement Units-Based Device for Ankle Rehabilitation

2018

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Ankle sprains are frequent injuries that occur among people of all ages. Ankle sprains constitute approximately 15% of all sports injuries, and are the most common traumatic emergencies. Without proper treatment and rehabilitation, a more severe sprain can weaken the ankle, making it more likely for new injures, and leading to long-term problems. In this work, we present an inertial measurement units (IMU)-based physical interface for measuring the foot attitude, and a graphical user interface that acts as a visual guide for patient rehabilitation. A foot-mounted physical interface for ankle rehabilitation was developed. The physical interface is connected to the computer by a Bluetooth link, and provides feedback to the patient while performing dorsiflexion, plantarflexion, eversion, and inversion exercises. The system allows for in-home rehabilitation at an affordable price while engaging the patient through active therapy. According to the results, more consistent rehabilitation could be achieved by providing feedback on foot angular position during therapy procedures.

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“…Its application primarily solves problems of linear and non-linearly separable data classification [52][53][54], detects and identifies failures and errors in various systems [55,56], and assesses risk in various branches of the economy [57,58]. In this paper, the range of special zone development in the spa areas was determined by means of the SVM technique.…”

Section: Introductionmentioning

confidence: 99%

The Use of Artificial Intelligence as a Tool Supporting Sustainable Development Local Policy

et al. 2019

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This paper addresses the problem of noise in spa protection areas. Its aim is to determine the delimitation of the areas that exceed a permissible noise level around the sanatorium on the example of a health resort in Inowrocław. The determination of the exceedance of permissible noise levels allows us to develop directly effective local policy tools to be included in planning documents. In order to reduce noise infiltration, it is important to define environmental priorities. Taking into account their impact on the health of users in the protection area, environmental priorities enable us to introduce additional elements to street architecture. In order to properly manage space, in accordance with the idea of sustainable development, zones of environmental sensitivity-and their socio-environmental vulnerability-have been designated for assessing damage (exceeding permissible noise in health facilities) and defining methods of building resilience (proper management). This has provided the basis for a natural balance optimized for the people living in these areas. To achieve the goal above, non-linear support vector machine (SVM) networks were used. This technique allows us to classify the linearly inseparable data and to determine the optimal separation margin. The boundaries of the areas which exceeded permissible noise levels (separation margin) were estimated on the basis of noise pollution maps, created by means of the SVM technique. Thus, the study results in establishing buffer zones where it is possible to use varied land utilization in terms of form and function, as described in the planning documents. Such an activity would limit the spread of noise.Sustainability 2019, 11, 4199 2 of 17 it is important to properly manage and recognize social, environmental and health vulnerabilities. "Noise sensitivity" is defined as an individual and increased probability of perceiving sounds as unpleasant [8][9][10][11]. Moreover, getting used to excessive noise levels causes indifference, which is caused by exposure to a hazardous situation [12][13][14][15][16].Noise can be characterized by its source (e.g., anthropogenic or natural causes) or by specific physical values, such as power, intensity, frequency or duration. It should be noted that its relevant parameters refer not only to strictly objective values considered to be unpleasant or harmful but also, to the same extent, to the places where common sounds will cause unwanted or disturbing effects [17][18][19]. Organized urban spaces are treated like resources directly used by local residents. The conditions of these spaces decide also on the possibilities for creating a proper base for planners who, to a greater or lesser degree, introduce quantitative and qualitative changes in the area [20,21].It is important then, to analyze the acoustic situation. The determination of physical parameters such as density, open spaces, their shape, the greenery and the location of the buildings has a significant effect on the noise spread in the environment [18,22]. Maps are a...

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Fault Diagnosis of a Reconfigurable Crawling–Rolling Robot Based on Support Vector Machines

Cited by 28 publications

References 20 publications

An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator

Foot-Mounted Inertial Measurement Units-Based Device for Ankle Rehabilitation

The Use of Artificial Intelligence as a Tool Supporting Sustainable Development Local Policy

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