scholarly journals Weak Signal Enhancement For Small Drill Condition Monitoring In PCB Drilling Process By Using Adaptive Multistable Stochastic Resonance

2021 ◽  
Author(s):  
Qifeng Tan ◽  
Guodong Liu ◽  
Yong Li ◽  
Hao Tong
Keyword(s):  
Tool Wear ◽  
Stochastic Resonance ◽  
Condition Monitoring ◽  
Printed Circuit Boards ◽  
Hole Drilling ◽  
Drilling Process ◽  
Weak Signal ◽  
Weak Signals ◽  
The Impact ◽  
Sr Method

Abstract The on-line tool condition monitoring is demanded to detect the tool wear and to ensure the hole drilling process of printed circuit boards (PCB) goes on smoothly. However, due to the impact of ambient noise caused by the limited size of small drill and the laminated material of PCB, the tool wear signal features are too weak to extract. The stochastic resonance (SR) method has been proven to be effective in enhancing weak signals among various weak signal extraction. In this paper, an adaptive multistable stochastic resonance is presented to improve performance of the SR method and process the tool wear signals for PCB drilling. The differential evolution (DE) algorithm is applied to adaptively optimize potential parameters and compensation factor, which makes the SR method suitable for high frequency signal. Moreover, tool wear experiments with different drill wear are carried out to verify the effectiveness of the proposed method. The results indicate that the proposed method improves the signal-to-noise ratio and has great potential in enhancing weak signals for small drill condition monitoring in PCB drilling process.

scholarly journals A New Second-Order Tristable Stochastic Resonance Method for Fault Diagnosis

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 965 ◽  
Author(s):  
Lu Lu ◽  
Yu Yuan ◽  
Heng Wang ◽  
Xing Zhao ◽  
Jianjie Zheng
Keyword(s):  
Fault Diagnosis ◽  
Stochastic Resonance ◽  
Fitness Function ◽  
Resonance Method ◽  
Poor Performance ◽  
Rolling Bearing ◽  
Second Order ◽  
Weak Signals ◽  
Rolling Bearings ◽  
Sr Method

Vibration signals are used to diagnosis faults of the rolling bearing which is symmetric structure. Stochastic resonance (SR) has been widely applied in weak signal feature extraction in recent years. It can utilize noise and enhance weak signals. However, the traditional SR method has poor performance, and it is difficult to determine parameters of SR. Therefore, a new second-order tristable SR method (STSR) based on a new potential combining the classical bistable potential with Woods-Saxon potential is proposed in this paper. Firstly, the envelope signal of rolling bearings is the input signal of STSR. Then, the output of signal-to-noise ratio (SNR) is used as the fitness function of the Seeker Optimization Algorithm (SOA) in order to optimize the parameters of SR. Finally, the optimal parameters are used to set the STSR system in order to enhance and extract weak signals of rolling bearings. Simulated and experimental signals are used to demonstrate the effectiveness of STSR. The diagnosis results show that the proposed STSR method can obtain higher output SNR and better filtering performance than the traditional SR methods. It provides a new idea for fault diagnosis of rotating machinery.

An improved adaptive stochastic resonance with general scale transformation to extract high-frequency characteristics in strong noise

2018 ◽  
Vol 32 (15) ◽  
pp. 1850185 ◽  
Author(s):  
Dawen Huang ◽  
Jianhua Yang ◽  
Jingling Zhang ◽  
Houguang Liu
Keyword(s):  
Stochastic Resonance ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Scale Transformation ◽  
Weak Signal ◽  
Signal Features ◽  
Signal Characteristics ◽  
Periodic Signals ◽  
Sr Method ◽  
General Scale

The idea of general scale transformation is introduced in detail. Based on this idea, an improved adaptive stochastic resonance (SR) method is proposed to extract weak signal features. Different periodic signals are considered to verify the proposed method. Compared with the normalized scale transformation, the output signal-to-noise ratio (SNR) of the proposed method is increased to a greater extent. Further, the influences of some key parameters on the responses of the two methods are discussed minutely. Results show that the improved adaptive SR method with general scale transformation is obviously superior to the traditional normalized scale transformation that is used in the former literatures. For different noise intensities and time scales, the proposed approach can always obtain the optimal response of SR to enhance the weak signal characteristics.

WEAR TESTING OF BUTTONS IN BITS FOR BLASTHOLE DRILLING

Tribologia ◽  
2018 ◽  
Vol 278 (2) ◽  
pp. 13-19 ◽  
Author(s):  
Rafał DUDEK ◽  
Krzysztof WŁADZIELCZYK
Keyword(s):  
Abrasive Wear ◽  
Blast Hole ◽  
Operating Time ◽  
Operating Conditions ◽  
Wear Testing ◽  
Hole Drilling ◽  
Drilling Process ◽  
Rock Mining ◽  
Drilling Rigs ◽  
The Impact

The article presents the results of the wear testing of buttons in selected types of bits with the diameter of 95 mm used for blast hole drilling in a rock mining. The purpose of the testing was to determine the type of the wear of peripheral and frontal buttons in the actual operating conditions of bits and the impact of selected parameters of the drilling process and of sharpening the buttons on their durability. Tests of button wear were carried out by the blasthole drilling in deposits of the Devonian and Triassic dolomites. For the blast hole drilling with tested bits, drilling rigs HSB 500 and HBM 60, equipped with down-the-hole impact mechanisms VKP 95-2 from the company Permon were used. Tests on the wear of buttons were carried out according to the adopted methodology, taking into account both their abrasive wear and wear through crushing or falling out. During the drilling of holes, every effort was made to use fixed values of parameters of the drilling process, except for the value of drill stem rotation speed, because one of objectives of the research was to determine its impact on the abrasive wear of tested bits buttons. The obtained results of tests proved that the predominant type of wear of button bits for blast hole drilling is an abrasive wear of frontal buttons, and regular sharpening of the buttons allows increasing the operating time of rock bits by up to 35%.

scholarly journals Chaotic Resonance in Izhikevich Neural Network Motifs Under Electromagnetic Induction

2021 ◽  
Author(s):  
Guowei Wang ◽  
Lijian Yang ◽  
Xuan Zhan ◽  
Anbang Li ◽  
Ya Jia
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Electromagnetic Induction ◽  
Current Intensity ◽  
Signal Frequency ◽  
Network Motifs ◽  
Neuronal System ◽  
Weak Signal ◽  
Weak Signals ◽  
The Impact

Abstract Chaotic resonance (CR) is the response of a nonlinear system to weak signals enhanced by internal or external chaotic activity (such as the signal derived from Lorenz system). In this paper, the triple-neuron feed-forward loop (FFL) Izhikevich neural network motifs with eight types are constructed as the nonlinear systems, and the effects of EMI on CR phenomenon in FFL neuronal network motifs are studied. It is found that both the single Izhikevich neural model under electromagnetic induction (EMI) and its network motifs exhibit CR phenomenon depending on the chaotic current intensity. There exists an optimal chaotic current intensity ensuring the best detection of weak signal in single Izhikevich neuron or its network motifs via CR. The EMI can enhance the ability of neuron to detect weak signals. For T1-FFL and T2-FFL motifs, the adjustment of EMI parameters makes T2-FFL show a more obvious CR phenomenon than that for T1-FFL motifs, which is different from the impact of system parameters (e.g., the weak signal frequency, the coupling strength, and the time delay) on CR. Another interesting phenomenon is that the variation of CR with time delay exhibits quasi periodic characteristics. Our results showed that CR effect is a robust phenomenon which is observed in both single Izhikevich neuron and network motifs, which might help one understand how to improve the ability of weak signal detection and propagation in neuronal system.

Approach to Weak Signal Extraction Based on Empirical Mode Decomposition and Stochastic Resonance

2013 ◽  
Vol 819 ◽  
pp. 216-221
Author(s):  
Pan Zhang ◽  
Tai Yong Wang ◽  
Lu Liu ◽  
Lu Yang Jin ◽  
Jin Xiang Fang
Keyword(s):  
Stochastic Resonance ◽  
Empirical Mode Decomposition ◽  
Signal Extraction ◽  
Weak Signal ◽  
Weak Signals ◽  
Mode Decomposition ◽  
Pre Treatment

The empirical mode decomposition (EMD) of weak signals submerged in a heavy noise was conducted and a method of stochastic resonance (SR) used for noisy EMD was presented. This method used SR as pre-treatment of EMD to remove noise and detect weak signals. The experiment result prove that this method, compared with that using EMD directly, not only improve SNR, enhance weak signals, but also improve the decomposition performance and reduce the decomposition layers.

scholarly journals Analysis of the Machinability of Carbon Fiber Composite Materials in Function of Tool Wear and Cutting Parameters Using the Artificial Neural Network Approach

Materials ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 2747 ◽  
Author(s):  
Norberto Feito ◽  
Ana Muñoz-Sánchez ◽  
Antonio Díaz-Álvarez ◽  
José Antonio Loya
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Composite Materials ◽  
Carbon Fiber ◽  
Tool Wear ◽  
Thrust Force ◽  
Cutting Parameters ◽  
Drilling Process ◽  
Artificial Neural ◽  
The Impact

Local delamination is the most undesirable damage associated with drilling carbon fiber reinforced composite materials (CFRPs). This defect reduces the structural integrity of the material, which affects the residual strength of the assembled components. A positive correlation between delamination extension and thrust force during the drilling process is reported in literature. The abrasive effect of the carbon fibers modifies the geometry of the fresh tool, which increases the thrust force and, in consequence, the induced damage in the workpiece. Using a control system based on an artificial neural network (ANN), an analysis of the influence of the tool wear in the thrust force during the drilling of CFRP laminate to reduce the damage is developed. The spindle speed, feed rate, and drill point angle are also included as input parameters of the study. The training and testing of the ANN model are carried out with experimental drilling tests using uncoated carbide helicoidal tools. The data were trained using error-back propagation-training algorithm (EBPTA). The use of the neural network rapidly provides results of the thrust force evolution in function of the tool wear and cutting parameters. The obtained results can be used by the industry as a guide to control the impact of the wear of the tool in the quality of the finished workpiece.

STUDY OF THE DRILLING PROCESS USED IN THE HOLE-DRILLING METHOD THROUGH THRUST FORCE MEASUREMENT AND TOOL WEAR ANALYSIS

2015 ◽  
Author(s):  
Rodrigo Blödorn ◽  
Mariana Tiemi Tamura ◽  
Rodrigo Alberto Henke ◽  
Matias Roberto Viotti ◽  
Armando Albertazzi Gonçalves Jr. ◽  
...  
Keyword(s):  
Tool Wear ◽  
Thrust Force ◽  
Force Measurement ◽  
Hole Drilling ◽  
Drilling Process ◽  
Hole Drilling Method ◽  
Wear Analysis ◽  
Drilling Method

scholarly journals Partly Duffing Oscillator Stochastic Resonance Method and Its Application on Mechanical Fault Diagnosis

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jian Dang ◽  
Rong Jia ◽  
Xingqi Luo ◽  
Hua Wu ◽  
Diyi Chen
Keyword(s):  
Fault Diagnosis ◽  
Mechanical System ◽  
Stochastic Resonance ◽  
Noise Intensity ◽  
Duffing Oscillator ◽  
Working Environment ◽  
Permutation Entropy ◽  
Weak Signals ◽  
Weak Fault ◽  
The Impact

Due to the fact that the slight fault signals in early failure of mechanical system are usually submerged in heavy background noise, it is unfeasible to extract the weak fault feature via the traditional vibration analysis. Stochastic resonance (SR), as a method of utilizing noise to amplify weak signals in nonlinear dynamical systems, can detect weak signals overwhelmed in the noise. However, based on the analysis of the impact of noise intensity on SR effect, it is concluded that the detection results are dramatically limited by the noise intensity of measured signals, especially for incipient fault feature of mechanical system with poor working environment. Therefore, this paper proposes a partly Duffing oscillator SR method to extract the fault feature of mechanical system. In this method, to locate the appearance of weak fault feature and decrease noise intensity, the permutation entropy index is constructed to select the measured signals for the input of Duffing oscillator system. Then, according to the regulation of system parameters, a reasonable match between the selected signals and Duffing oscillator model is achieved to produce a SR phenomenon and realize the fault diagnosis of mechanical system. Experiment results demonstrate that the proposed method achieves a better effect on the fault diagnosis of mechanical system.

scholarly journals Thermomechanical Impact of the Single-Lip Deep Hole Drilling on the Surface Integrity on the Example of Steel Components

2021 ◽  
Vol 5 (4) ◽  
pp. 120
Author(s):  
Jan Nickel ◽  
Nikolas Baak ◽  
Pascal Volke ◽  
Frank Walther ◽  
Dirk Biermann
Keyword(s):  
Surface Integrity ◽  
Mechanical Load ◽  
Fatigue Behavior ◽  
Dynamic Strength ◽  
Cutting Parameters ◽  
Temperature Measurements ◽  
Hole Drilling ◽  
Drilling Process ◽  
Subsurface Zone ◽  
The Impact

The fatigue behavior of components made of quenched and tempered steel alloys is of elementary importance, especially in the automotive industry. To a great extent, the components’ fatigue strength is influenced by the surface integrity properties. For machined components, the generated surface is often exposed to the highest thermomechanical loads, potentially resulting in transformations of the subsurface microstructure and hardness as well as the residual stress state. While the measurement of the mechanical load using dynamometers is well established, in-process temperature measurements are challenging, especially for drilling processes due to the process kinematics and the difficult to access cutting zone. To access the impact of the thermomechanical load during the single-lip drilling process on the produced surface integrity, an in-process measurement was developed and applied for different cutting parameters. By using a two-color pyrometer for temperature measurements at the tool’s cutting edge in combination with a dynamometer for measuring the occurring force and torque, the influence of different cutting parameter variations on the thermomechanical impact on the bore surface are evaluated. By correlating force and temperature values with the resultant surface integrity, a range of process parameters can be determined in which the highest dynamic strength of the samples is expected. Thermally induced defects, such as the formation of white etching layers (WEL), can be avoided by the exact identification of critical parameter combinations whereas a mechanically induced microstructure refinement and the induction of residual compressive stresses in the subsurface zone is targeted. Further, eddy-current analysis as a non-destructive method for surface integrity evaluation is used for the characterization of the surface integrity properties.

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