The cutting parameters dependent vibration monitoring method for machine tools

2020 ◽  
Vol 148 (4) ◽  
pp. 2793-2793
Author(s):  
Mingxin Hui ◽  
Jing Wang ◽  
Bin Liu ◽  
Xun Wang ◽  
Xiaobin Cheng ◽  
...  
Keyword(s):  
Machine Tools ◽  
Cutting Parameters ◽  
Vibration Monitoring ◽  
Monitoring Method

scholarly journals Design of Vibration Frequency Method with Fine-Tuned Factor for Fault Detection of Three Phase Induction Motor

2021 ◽  
Vol 3 (1) ◽  
pp. 52-65
Author(s):  
Thomas Amanuel ◽  
Amanuel Ghirmay ◽  
Huruy Ghebremeskel ◽  
Robel Ghebrehiwet ◽  
Weldekidan Bahlibi
Keyword(s):  
Induction Motor ◽  
Vibration Frequency ◽  
Vibration Monitoring ◽  
Slight Variation ◽  
Frequency Method ◽  
Monitoring Method ◽  
Stator Current ◽  
Research Article ◽  
Proposed Model ◽  
Fault Parameters

This research article focuses on industrial applications to demonstrate the characterization of current and vibration analysis to diagnose the induction motor drive problems. Generally, the induction motor faults are detected by monitoring the current and proposed fine-tuned vibration frequency method. The stator short circuit fault, broken rotor bar fault, air gap eccentricity, and bearing fault are the common faults that occur in an induction motor. The detection process of the proposed method is based on sidebands around the supply frequency in the stator current signal and vibration. Moreover, it is very challenging to diagnose the problem that occur due to the complex electromagnetic and mechanical characteristics of an induction motor with vibration measures. The design of an accurate model to measure vibration and stator current is analyzed in this research article. The proposed method is showing how efficiently the root cause of the problem can be diagnosed by using the combination of current and vibration monitoring method. The proposed model is developed for induction motor and its circuit environment in MATLAB is verified to perform an accurate detection and diagnosis of motor fault parameters. All stator faults are turned to turn fault; further, the rotor-broken bar and eccentricity are structured in each test. The output response (torque and stator current) is simulated by using a modified winding procedure (MWP) approach by tuning the winding geometrical parameter. The proposed model in MATLAB Simulink environment is highly symmetrical, which can easily detect the signal component in fault frequencies that occur due to a slight variation and improper motor installation. Finally, this research article compares the other existing methods with proposed method.

scholarly journals Multidimensional System Identification and Active Vibration Control of a Piezoelectric-Based Sting System Used in Wind Tunnel

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yi Yu ◽  
Xing Shen ◽  
Yun Huang
Keyword(s):  
Control System ◽  
System Identification ◽  
Wind Tunnel ◽  
Vibration Control ◽  
Active Vibration Control ◽  
Low Frequency ◽  
Vibration Monitoring ◽  
Multidimensional System ◽  
Monitoring Method ◽  
Active Vibration

In wind tunnel tests, the cantilever sting is usually used to support aircraft models because of its simple structure and low aerodynamic interference. However, in some special conditions, big-amplitude and low-frequency vibration would occur easily on the model not only in the pitch direction but also in the yaw direction, resulting in inaccurate data and even damage of the supporting structure. In this paper, aiming at suppressing the vibration in pitch and yaw plane, a multidimensional system identification and active vibration control system on the basis of piezoelectric actuators is established. A vibration monitoring method based on the strain-displacement transformation (SDT) matrix is proposed, which can transform strain signals into vibration displacements. The system identification based on chirp-Z transform (CZT) is applied to improve the adaptability and precision of the building process for the system model. After that, the hardware platform as well as the software control system based on the classical proportional-derivative (PD) algorithm is built. A series of experiments are carried out, and the results show the exactness of the vibration monitoring method. The system identification process is completed, and the controller is designed. Vibration control experiments verify the effectiveness of the controller, and the results indicate that vibrations in pitch and yaw directions are attenuated apparently. The spectrum power is reduced over 14.8 dB/Hz, which prove that the multidimensional identification and active vibration control system has the capability to decline vibration from different directions.

Prediction models for specific energy consumption of machine tools and surface roughness based on cutting parameters and tool wear

2020 ◽  
pp. 095440542097106
Author(s):  
Yu Su ◽  
Congbo Li ◽  
Guoyong Zhao ◽  
Chunxiao Li ◽  
Guangxi Zhao
Keyword(s):  
Surface Roughness ◽  
Energy Consumption ◽  
Tool Wear ◽  
Specific Energy ◽  
Machine Tools ◽  
Prediction Models ◽  
Specific Energy Consumption ◽  
Cutting Parameters ◽  
Experimental Results ◽  
Support Vector

The specific energy consumption of machine tools and surface roughness are important indicators for evaluating energy consumption and surface quality in processing. Accurate prediction of them is the basis for realizing processing optimization. Although tool wear is inevitable, the effect of tool wear was seldom considered in the previous prediction models for specific energy consumption of machine tools and surface roughness. In this paper, the prediction models for specific energy consumption of machine tools and surface roughness considering tool wear evolution were developed. The cutting depth, feed rate, spindle speed, and tool flank wear were featured as input variables, and the orthogonal experimental results were used as training points to establish the prediction models based on support vector regression (SVR) algorithm. The proposed models were verified with wet turning AISI 1045 steel experiments. The experimental results indicated that the improved models based on cutting parameters and tool wear have higher prediction accuracy than the prediction models only considering cutting parameters. As such, the proposed models can be significant supplements to the existing specific energy consumption of machine tools and surface roughness modeling, and may provide useful guides on the formulation of cutting parameters.

Special Issue on Multiaxis Control and Multitasking Machining

2017 ◽  
Vol 11 (2) ◽  
pp. 139-139
Author(s):  
Keiichi Nakamoto ◽  
Keyword(s):  
Machine Tools ◽  
Tool Path ◽  
High Accuracy ◽  
Numerical Control ◽  
Plant Production ◽  
Vibration Monitoring ◽  
Practical Case ◽  
Accuracy Evaluation ◽  
Generation Process ◽  
Special Issue

Machine tools using numerical control (NC) devices are typical mechatronics products, and introducing them is a powerful way to automate plant production. NC machine tools in workshops meet the requirements of high accuracy and efficiency in the machining of a variety of parts and mold dies. Turning centers and machining centers are typical examples of such machine tools. Various cutting processes have been integrated in them to cope with the increase in machine parts that not only have complicated geometries but also must be made with high accuracy, in small quantities, and in a short machining time. In addition, turning and machining centers have been given multitasking capabilities, and the number of control axes has been increased so that complex products may be manufactured efficiently. Given that the strong attention and interest in multiaxis control and multitasking machine tools are rapidly increasing, it is fitting that the current state of the art of these tools and their practical and applicable technologies be presented. This special issue features 16 research articles – one review and 15 papers – related to the latest research results and practical case studies in multiaxis control and multitasking machining. Their subjects cover various advances in machine control, motion accuracy evaluation, machining error analysis, chatter vibration monitoring or suppression, trouble-free tool path generation, process planning, and new applications of the machine tools. We thank the authors for their contributions to this special issue, and we are sure that both non-specialists and specialists alike will find the information the authors provide both interesting and informative. Moreover, we deeply appreciate the reviewers for their incisive efforts. Without these contributions, this special issue could not have been realized. We truly hope that this special issue will trigger further research on multiaxis control and multitasking machining.

Blade tip timing vibration monitoring method based on fiber Bragg

2013 ◽  
Author(s):  
Fei Wu ◽  
Lei Liang ◽  
Junya Xing ◽  
Lin Wang ◽  
Lang Jia
Keyword(s):  
Vibration Monitoring ◽  
Monitoring Method ◽  
Blade Tip

Tool-Wear Monitoring and Control

2005 ◽  
Author(s):  
J. Srinivas ◽  
Rao Dukkipati ◽  
V. Sreebalaji ◽  
K. Ramakotaih
Keyword(s):  
Tool Wear ◽  
Machine Tools ◽  
Flank Wear ◽  
Cutting Parameters ◽  
Monitoring And Control ◽  
Tool Wear Monitoring ◽  
Wear Monitoring ◽  
Trained Neural Network ◽  
And Control ◽  
Control Methodology

This paper presents, a control methodology based on experimental data of the tool wear as a function of cutting variables. In automatic machine tools there is strong need to control the tool wear by adjustment of the cutting parameters. In this connection, a control system, which can adjust the cutting parameters for a desired wear rate, is necessary. A regression relation is also established between the flank-wear and the cutting parameters. An inversely trained neural network model, which supplies the modified values of the cutting parameters, is used as a controller. The results are shown in the form of tables and graphs.

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