Integrated Manufacturing of Bespoke Mechatronic Systems

2018 ◽  
pp. 219-234
Author(s):  
Jake Smith ◽  
Nicholas Fry ◽  
Robert Richardson ◽  
Jordan H. Boyle
Keyword(s):  
Mechatronic Systems ◽  
Integrated Manufacturing

CIM Computer Integrated Manufacturing

1987 ◽  
Author(s):  
August-Wilhelm Scheer
Keyword(s):  
Computer Integrated Manufacturing ◽  
Integrated Manufacturing

Computer integrated manufacturing—a joint effort

1984 ◽  
Vol 1 (7) ◽  
pp. 214 ◽  
Author(s):  
Craig Skevington
Keyword(s):  
Computer Integrated Manufacturing ◽  
Joint Effort ◽  
Integrated Manufacturing

scholarly journals Gradual Wear Diagnosis of Outer-Race Rolling Bearing Faults through Artificial Intelligence Methods and Stray Flux Signals

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1486
Author(s):  
Israel Zamudio-Ramirez ◽  
Roque A. Osornio-Rios ◽  
Jose A. Antonino-Daviu ◽  
Jonathan Cureño-Osornio ◽  
Juan-Jose Saucedo-Dorantes
Keyword(s):  
Kinematic Chain ◽  
Industrial Applications ◽  
Electric Motors ◽  
Feed Forward Neural Network ◽  
Mechatronic Systems ◽  
Linear Discriminant ◽  
Bearing Faults ◽  
Outer Race ◽  
Non Invasive ◽  
Operation Conditions

Electric motors have been widely used as fundamental elements for driving kinematic chains on mechatronic systems, which are very important components for the proper operation of several industrial applications. Although electric motors are very robust and efficient machines, they are prone to suffer from different faults. One of the most frequent causes of failure is due to a degradation on the bearings. This fault has commonly been diagnosed at advanced stages by means of vibration and current signals. Since low-amplitude fault-related signals are typically obtained, the diagnosis of faults at incipient stages turns out to be a challenging task. In this context, it is desired to develop non-invasive techniques able to diagnose bearing faults at early stages, enabling to achieve adequate maintenance actions. This paper presents a non-invasive gradual wear diagnosis method for bearing outer-race faults. The proposal relies on the application of a linear discriminant analysis (LDA) to statistical and Katz’s fractal dimension features obtained from stray flux signals, and then an automatic classification is performed by means of a feed-forward neural network (FFNN). The results obtained demonstrates the effectiveness of the proposed method, which is validated on a kinematic chain (composed by a 0.746 KW induction motor, a belt and pulleys transmission system and an alternator as a load) under several operation conditions: healthy condition, 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm hole diameter on the bearing outer race, and 60 Hz, 50 Hz, 15 Hz and 5 Hz power supply frequencies

scholarly journals Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 420
Author(s):  
Phong B. Dao
Keyword(s):  
Real Time ◽  
Feedforward Control ◽  
Design Method ◽  
Mechatronic Systems ◽  
Control Approach ◽  
Runtime Environment ◽  
Multiagent Control ◽  
On Line ◽  
Promising Solution ◽  
Function Approximator

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method.

scholarly journals Changes in the dynamics of the output characteristics of mechatronic systems with planetary hydraulic motors

2021 ◽  
Vol 1741 ◽  
pp. 012045
Author(s):  
A Voloshina ◽  
A Panchenko ◽  
O Titova ◽  
I Panchenko
Keyword(s):  
Mechatronic Systems ◽  
Hydraulic Motors ◽  
Output Characteristics
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