scholarly journals Logical–Linguistic Model of Diagnostics of Electric Drives with Sensors Support

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4429
Author(s):  
Yury Nikitin ◽  
Pavol Božek ◽  
Jozef Peterka
Keyword(s):  
Fuzzy Inference ◽  
Technical Condition ◽  
Numerical Control ◽  
Cnc Machine ◽  
Diagnostic Systems ◽  
Mechatronic Systems ◽  
Inference System ◽  
Electric Drives ◽  
Electrical Drives ◽  
Linguistic Model

The presented paper scientifically discusses the progressive diagnostics of electrical drives in robots with sensor support. The AI (artificial intelligence) model proposed by the authors contains the technical conditions of fuzzy inference rule descriptions for the identification of a robot drive’s technical condition and a source for the description of linguistic variables. The parameter of drive diagnostics for a robotized workplace that is proposed here is original and composed of the sum of vibration acceleration amplitudes ranging from a frequency of 6.3 Hz to 1250 Hz of a one-third-octave filter. Models of systems for the diagnostics of mechatronic objects in the robotized workplace are developed based on examples of CNC (Computer Numerical Control) machine diagnostics and mechatronic modules based on the fuzzy inference system, concluding with a solved example of the multi-criteria optimization of diagnostic systems. Algorithms for CNC machine diagnostics are implemented and intended only for research into precisely determined procedures for monitoring the lifetime of the mentioned mechatronic systems. Sensors for measuring the diagnostic parameters of CNC machines according to precisely determined measuring chains, together with schemes of hardware diagnostics for mechatronic systems are proposed.

Equipment State Assessment System Based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

2015 ◽  
Vol 792 ◽  
pp. 243-247 ◽  
Author(s):  
Alexandra Khalyasmaa ◽  
Artem Aminev ◽  
Dmitry Bliznyuk
Keyword(s):  
Expert Systems ◽  
Fuzzy Inference ◽  
Technical Condition ◽  
Gas Analysis ◽  
Assessment System ◽  
Technical Diagnostics ◽  
Inference System ◽  
Power Stations ◽  
Neuro Fuzzy ◽  
Equipment State

The paper is dedicated to analyze the modern expert systems to assess the technical condition of power stations and substations high-voltage equipment. The main problems of modern expert systems and their possible solutions are determined. As the structure and their basic construction principles are considered. Also this paper proposes an algorithm for the expert system model using fuzzy inference on the basis of technical diagnostics and tests. As a case study of assessment of power transformers state based on dissolved gas analysis in the oil is presented.

Integrity Assessment and Control of Offshore Topside Piping: An Expert System Based Approach

2018 ◽  
Author(s):  
R. M. Chandima Ratnayake
Keyword(s):  
Expert System ◽  
Fuzzy Inference ◽  
Control Program ◽  
Technical Condition ◽  
Practical Significance ◽  
Illustrative Case ◽  
Inference System ◽  
Suggested Approach ◽  
Integrity Assessment ◽  
And Control

Downtime has a significant influence on the productive capability of offshore topside operating systems. Integrity assessment and control (IA&C) disciplines face major challenges in implementing a plant integrity control strategy, due to the lack of a methodology for incorporating fuzziness present in the data. To date, the employed IA&C practices face challenges in maintaining uniform quality from one integrity control program to another, due to the variability present in the technical IA&C process, especially among the different integrity assessment experts. Hence, it is vital to use expert systems-based approaches to sustain IA&C activities at an anticipated level and maintain the performance of operating assets at a target level. This manuscript provides a methodology and an illustrative case for how to perform IA&C activities for offshore topside piping. The illustrative case is demonstrated using a fuzzy inference system (FIS). Technical condition (TC) and relative degradation (RD) are selected as the inputs to the FIS for assessing the likelihood of failure (LoF). Expert system-based calculations, and how to use such results for IA&C, are demonstrated. The practical significance of the suggested approach is also discussed.

scholarly journals Assessment improvement of road accidents on highways of the Far North as the basis for sustainable regional development

2021 ◽  
Vol 112 ◽  
pp. 00007
Author(s):  
Dmitry A. Skorobogatchenko ◽  
Vitaly S. Borovik ◽  
Vitaly V. Borovik ◽  
Anton Y. Zhabunin ◽  
Roman R. Chugumbaev
Keyword(s):  
Road Safety ◽  
Safety Assessment ◽  
Traffic Accidents ◽  
Fuzzy Inference ◽  
Road Traffic ◽  
Technical Condition ◽  
Road Accidents ◽  
Inference System ◽  
Far North ◽  
Wide Range

The paper substantiates the need to assess the road safety in the specific conditions of the Far North by means of the analysis of the factors in the “driver-car-road-environment” system. The authors suggest a methodology for assessment of road traffic accidents, which makes it possible to take into account a wide range of factors affecting road accidents. In particular, the simulation takes into account the characteristics of the driver, technical condition of the vehicle, road conditions, weather and climate. Adaptive neural networks based on fuzzy inference systems are used as a tool for road safety assessment. The authors mention the results of statistical studies on a number of variables of the “driver-car-road-environment” system, which make it possible to form membership functions in the fuzzy inference system. The final part of the paper presents the practical results of road safety assessment for various categories of drivers in different road conditions in one of the largest cities in the Far North.

Intelligent Machine Tool: New Manual Programming Techniques

2015 ◽  
Vol 220-221 ◽  
pp. 485-490
Author(s):  
Mirosław Pajor ◽  
Kamil Stateczny
Keyword(s):  
Machine Tool ◽  
Control Systems ◽  
Machine Tools ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Diagnostic Systems ◽  
Mechatronic Systems ◽  
Cad Cam ◽  
Programming Techniques ◽  
Machine Communication

Modern CNC machine tools constitute advanced mechatronic systems. Numerous works are undertaken on the development of new intelligent control systems for CNC machine tools [1–5] equipped with unique diagnostic systems. One of the development directions of CNC control systems is exploring new forms and techniques of operator-machine communication as well as new, simpler machine tool programming procedures. Nowadays, there are many techniques for programming CNC machine tools [6], [7]. These techniques have taken a variety of forms both due to historical limits of technology and various environmental requirements. Despite the existence of complex control systems for operation and programming CNC machine tools or CAD/CAM systems facilitating the generation of a machining strategy for complicated elements, there is a demand for machine tools that are easier to operate, and therefore do not require advanced programming skills for operation.

Influence of Nonlinear Friction and Disturbance in the Control of a Mechatronic System: CNC Machine Tool Application

2011 ◽  
Author(s):  
Liz K. Rincon ◽  
Joa˜o M. Rosario
Keyword(s):  
Machine Tool ◽  
Cutting Force ◽  
Viscous Friction ◽  
Numerical Control ◽  
Machining Process ◽  
Contour Error ◽  
Nonlinear Friction ◽  
Cnc Machine ◽  
Mechatronic Systems ◽  
High Speeds

The CNC (Computer Numerical Control) machine tools are complex mechatronic systems applied to the manufacture with high precision and high speeds. To achieve high accuracy and operational efficiency, the disturbance and friction, which occur during machining process, should be reduced as low as possible. This paper develops an analysis of influence by cutting force and friction effect in the control of machine tool based on the CNC dynamic model and parameters identification. For this purpose, the study focuses on Coulomb and Viscous nonlinear friction and the external disturbances. The analysis uses control position error, contour error, and stability to determine the influence of friction and disturbance. The results show that Viscous friction has more critical influence on system than the Cutting force and Coulomb. The work contributes in recognizing which parameters have greater influence on the machine behavior through dynamic analysis with the identification strategy, in order to design and improve the control structure for a real CNC system.

scholarly journals Adaptation of fuzzy inference system to solve assessment problems of technical condition of construction objects

2020 ◽  
Vol 3 (2(53)) ◽  
pp. 52-55
Author(s):  
Serhii Kartavykh ◽  
Oleksii Komandyrov ◽  
Petro Kulikov ◽  
Vitalii Ploskyi ◽  
Natalia Poltorachenko ◽  
...  
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Technical Condition ◽  
Inference System ◽  
Assessment Problems

scholarly journals Analysis of Diagnostic Methods and Energy of Production Systems Drives

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 843
Author(s):  
Ivan Kuric ◽  
Ivana Klačková ◽  
Yury Rafailovich Nikitin ◽  
Ivan Zajačko ◽  
Miroslav Císar ◽  
...  
Keyword(s):  
Fuzzy Inference ◽  
Diagnostic System ◽  
Sensory Systems ◽  
Technical Condition ◽  
Repair Time ◽  
Diagnostic Methods ◽  
Technical Diagnostics ◽  
Inference System ◽  
Diagnostic Parameters ◽  
Industrial Enterprises

This article deals with solving the urgent scientific problem of the diagnostics of drives of technological robotized workplaces with support of sensors. The dependence of diagnostic parameters on the technical state of drives of automated technological systems, which is of great economic importance for industrial enterprises, is being investigated. Diagnostic models have been developed based on sensory systems to diagnose drive models of technological robotized workplaces. The use of these models may also include monitoring systems in which it is possible to build a system for identifying detected changes. These systems identify many contradictory changes and thereby reduce the false alarm frequency of monitoring sensory systems. Numerous methods for solving technical diagnostics problems are often based on methods based on mathematical models describing work processes, as well as on spectral analysis of measured parameters, such as vibrations, noise, and electric current. A fuzzy inference system for assessing the technical condition, a system for estimating the residual resource of drives, and asystem for calculating diagnostic intervals based on fuzzy knowledge have been developed. Based on the historical trend of the diagnostic parameters, the intelligent diagnostic system determines the current technical condition of the actuator and predicts future technical condition changes, determines the remaining service life and the time intervals for diagnostics. The analysis of the time spent on planned preventive maintenance of technological equipment makes it possible to conclude that, after the modernization of equipment in 2018, the repair time was reduced from 350 h to 260 h per year (26%). Since 2019, there is a tendency to increase repair time by 30 h each year.

scholarly journals The distributed system of multipoint daily monitoring of the technical condition of the working equipment of mobile lifts with mast-type work platforms

2021 ◽  
Vol 2021 (2) ◽  
pp. 294-302
Author(s):  
Maria S. KOROVINA ◽  
◽  
Sergey K. KOROVIN ◽  
Keyword(s):  
Distributed System ◽  
Fuzzy Inference ◽  
Technical Condition ◽  
Dynamic Processes ◽  
Inference System ◽  
Daily Monitoring ◽  
Neuro Fuzzy ◽  
Work Cycle ◽  
Matlab Package ◽  
Safety Systems

Objective: To consider the requirements for safety devices of mobile lifts with working platforms and ana- lyze the specifics of daily monitoring of their technical condition. To consider the need to expand the func- tionality of the built-in safety systems of these lifts. To demonstrate the need for in-depth control and anal- ysis of the work cycle dynamic processes of mobile lifts with mast-type work platforms and provide tech- nical solutions for their implementation. Methods: The relationship of mechanical and electromechanical characteristics of electric drives of mobile lifts with mast-type work platforms with the output parameters of a distributed system of multipoint daily monitoring in various modes has been revealed using the Adap- tive Neuro-Fuzzy Inference System (ANFIS) of the MATLAB package. Results: On the laboratory bench, the values of the minimum root-mean-square errors in determining the speed, torque on the shaft, and the stator current of an asynchronous electric motor with a squirrel-cage rotor were obtained according to the data of the three-axis accelerometer LIS331DLH, gyroscope I3G4250D, and magnetometer LIS3MDL, as well as an electret microphone on training and test samples, various training methods and membership func- tions of the generated structures of ANFIS, the Adaptive Neuro-Fuzzy Inference System. Practical impor- tance: The possibility of expanding the functionality of built-in safety systems of mobile lifts with mast- type work platforms is shown based on the control of the work cycle dynamic processes by a distributed system of multipoint daily monitoring trained using the ANFIS of the MATLAB package, which can be recommended for practical use.

Developing a Knowledge Base about the Technological Forces within the Asymmetric Incremental Forming Process

2015 ◽  
Vol 651-653 ◽  
pp. 1115-1121 ◽  
Author(s):  
Melania Tera ◽  
Radu Eugen Breaz ◽  
Octavian Bologa ◽  
Sever Gabriel Racz
Keyword(s):  
Knowledge Base ◽  
Fuzzy Inference ◽  
Incremental Forming ◽  
Single Point ◽  
Feed Speed ◽  
Cnc Machine ◽  
Technological Parameters ◽  
Forming Process ◽  
Inference System ◽  
Sheet Metal Parts

Asymmetric single point incremental forming (ASPIF) has been recognized as a solution with potential in manufacturing small batches or single sheet metal parts. The approach presented in this paper presents the development of a knowledge base regarding the values of the technological force within the ASPIF process and the influence of some technological parameters such as feed, speed of the punch, thickness of the part and step, upon them. The method is based on the use of the information provided by the CNC machine sensors. Relationships between the torques developed by the drive motors on each axes and the technological forces will be set in order to refine the raw information displayed on the machine to a usable form. Finally, using an adaptive neuro-fuzzy inference system the dependence between the value of the technological force and the other parameters has been extracted.

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