Research of High-precision Worm Gear Machine Tool Based on Error Transmission Theory and Error Correction Technique

2011 ◽  
Vol 47 (09) ◽  
pp. 157
Author(s):  
Donglin PENG
Keyword(s):  
Machine Tool ◽  
Error Correction ◽  
High Precision ◽  
Worm Gear ◽  
Correction Technique ◽  
Gear Machine

scholarly journals Deep PUF: A Highly Reliable DRAM PUF-Based Authentication for IoT Networks Using Deep Convolutional Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2009
Author(s):  
Fatemeh Najafi ◽  
Masoud Kaveh ◽  
Diego Martín ◽  
Mohammad Reza Mosavi
Keyword(s):  
Error Correction ◽  
Random Access ◽  
Error Correction Codes ◽  
Access Memory ◽  
Deep Convolutional Neural Networks ◽  
Device Identification ◽  
Physical Unclonable Functions ◽  
Server Side ◽  
Correction Technique ◽  
Reduction Methods

Traditional authentication techniques, such as cryptographic solutions, are vulnerable to various attacks occurring on session keys and data. Physical unclonable functions (PUFs) such as dynamic random access memory (DRAM)-based PUFs are introduced as promising security blocks to enable cryptography and authentication services. However, PUFs are often sensitive to internal and external noises, which cause reliability issues. The requirement of additional robustness and reliability leads to the involvement of error-reduction methods such as error correction codes (ECCs) and pre-selection schemes that cause considerable extra overheads. In this paper, we propose deep PUF: a deep convolutional neural network (CNN)-based scheme using the latency-based DRAM PUFs without the need for any additional error correction technique. The proposed framework provides a higher number of challenge-response pairs (CRPs) by eliminating the pre-selection and filtering mechanisms. The entire complexity of device identification is moved to the server side that enables the authentication of resource-constrained nodes. The experimental results from a 1Gb DDR3 show that the responses under varying conditions can be classified with at least a 94.9% accuracy rate by using CNN. After applying the proposed authentication steps to the classification results, we show that the probability of identification error can be drastically reduced, which leads to a highly reliable authentication.

Error correction technique for numerical control machine tools based on the simplex method

2021 ◽  
pp. 095440542110281
Author(s):  
Hongwei Liu ◽  
Rui Yang ◽  
Pingjiang Wang ◽  
Jihong Chen ◽  
Hua Xiang
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Simplex Method ◽  
Tool Path ◽  
Repeated Measurements ◽  
Numerical Control ◽  
Machining Accuracy ◽  
Correction Technique ◽  
Fluctuation Range ◽  
Nc Machine

The objective of this research is to develop a novel correction mechanism to reduce the fluctuation range of tools in numerical control (NC) machining. Error compensation is an effective method to improve the machining accuracy of a machine tool. If the difference between two adjacent compensation data is too large, the fluctuation range of the tool will increase, which will seriously affect the surface quality of the machined parts in mechanical machining. The methodology used in compensation data processing is a simplex method of linear programming. This method reduces the fluctuation range of the tool and optimizes the tool path. The important aspect of software error compensation is to modify the initial compensation data by using an iterative method, and then the corrected tool path data are converted into actual compensated NC codes by using a postprocessor, which is implemented on the compensation module to ensure a smooth running path of the tool. The generated, calibrated, and amended NC codes were immediately fed to the machine tool controller. This technique was verified by using repeated measurements. The results of the experiments demonstrate efficient compensation and significant improvement in the machining accuracy of the NC machine tool.

The Determination of the Three-Point Support Design of Machine Tool Based on iSIGHT

2014 ◽  
Vol 607 ◽  
pp. 342-345
Author(s):  
Sheng Hui Zhao ◽  
Xiao Chuang Zhu ◽  
Da Wei Zhang
Keyword(s):  
Machine Tool ◽  
High Precision ◽  
Multidisciplinary Optimization ◽  
Joint Surface ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Support Design ◽  
Optimal Position ◽  
Point Support

In order to meet the requirements of high-precision machine tool, it has been an important factor to select an appropriate way to support the bed. By building a multidisciplinary optimization (MDO) process based on iSIGHT, this article select the deformation difference of the guides and the deformation difference of the joint surface between column and bed of the machine tool as the objective functions, and then conduct a multi-objective optimization (MOO) of the positional parameters of the three-point support. Eventually the optimization result is given and the optimal position of the three-point support is determined.

Application of PLC in the DC Vertical Lathe Spindle Control

2014 ◽  
Vol 687-691 ◽  
pp. 480-483
Author(s):  
Jia Xing Ma
Keyword(s):  
Machine Tool ◽  
High Precision ◽  
Speed Control ◽  
Dc Motor ◽  
Foreign Demand ◽  
Programmable Controller ◽  
Machine Tool Spindle ◽  
Speed Regulator

CNC vertical lathe is the main on products. The domestic and foreign demand is also very big. The key part of the high precision is on the control of the spindle. This design is with the German SIEMENS company programmable controller (PLC), S7-200 as the main controller; Germany SIEMENS company 6 ra7075 dc speed regulator, Z4 dc speed regulating device of dc motor, dc speed control was adopted to realize efficient and accurate control of machine tool spindle, and the electrical principle diagram is given.

High-Precision Tracking Control of Machine Tool Feed Drives Based on ADRC

2016 ◽  
Author(s):  
Chengyong Zhang ◽  
Yaolong Chen
Keyword(s):  
Machine Tool ◽  
High Precision ◽  
Tracking Control ◽  
Position Control ◽  
Feedback System ◽  
Pi Controller ◽  
Ball Screw ◽  
Feed Drives ◽  
Precision Tracking ◽  
Precision Tracking Control

In this paper, the active-disturbance-rejection control (ADRC) is applied to realize the high-precision tracking control of CNC machine tool feed drives. First, according to the number of the feedback channel, the feed systems are divided into two types: signal-feedback system, e.g., linear motor and rotary table, and double-feedback system, e.g., ball screw feed drive with a load/table position feedback. Then, the appropriate controller is designed to ensure the closed-loop control performance of each type of system based on the idea of ADRC. In these control frameworks, the extended state observers (ESO) estimate and compensate for unmodeled dynamics, parameter perturbations, variable cutting load, and other uncertainties. For the signal-feedback system, the modified ADRC with an acceleration feedforward term is used directly to regulate the load/table position response. However, for the double-feedback system, the ADRC is applied only to the motor position control, and a simple PI controller is used to achieve the accurate position control of the load. In addition, based on ADRC feedback linearization, a novel equivalent-error-model based feedforward controller is designed to further improve the command following performance of the double-feedback system. The experimental results demonstrate that the proposed controllers of both systems have better tracking performance and robustness against the external disturbance compared with the conventional P-PI controller.

A new error correction technique for BD systems

2010 ◽  
Vol 56 (2) ◽  
pp. 663-668 ◽  
Author(s):  
Jun Lee ◽  
Seong-Hun Lee
Keyword(s):  
Error Correction ◽  
Correction Technique
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