High Speed Self Research Articles

Experimental analysis of the influence of discharge gap on EDM performance

In order to reduce the machining time and improve the surface quality of holes, a high speed self adjusting electrical discharge machining (EDM) approach is needed with independent flushing system that were able to remove the debris in the machining process. With the change in the gap distance and depth of the hole drilled, the electrode automatically adjusts the gap with the help of a linear actuator. For that, the optimum gap distance for getting maximum result is crucial. Taguchi L27 orthogonal array technique is used for the preliminary experimental analysis. The study revealed that discharge gap which is proportional to the gap voltage is the most influential parameter that affects the surface finish and material removal rate. The formation mechanism of the hole in the copper plate had found out, in order to get the optimum gap distance for the maximum MRR, TWR, and ROC. The results from the comparison experiment shows that the best result will be get at 0.5 mm gap distance and this can be taken as the optimum gap distance for the automatic feeding mechanism. In addition, low voltage and current would benefit for the EDM process working in micro level and for the removal of the recast layer.

Effect of discharge gap on EDM using desirability function analysis

Electro Discharge Machining (EDM) has been developed as a precise machining process to produce accurate features in electrically conducting materials. A high-speed self- adjusting EDM approach is needed with feedback system to remove the debris in the machining process. In the current study, the micro feature machining in the copper plate is investigated in order to get the optimum gap distance in EDM process. With the change in the gap distance and depth of the hole drilled, the linear actuator automatically adjusts the gap for the electrode. So it is crucial to find out the optimum input parameters that contribute for maximum result. For the experimental analysis Taguchi L27 orthogonal array technique is used. With the help of Desirability Function Analysis (DFA) and Analysis of Variance (ANOVA), the optimum parameters values had found out for maximum Material Removal Rate (MRR) with minimum Tool Wear Rate (TWR) and Radial Over Cut (ROC). The parameters values for optimum result are found to be voltage (39.95 V), Frequency (4.67 KHz), Duty Factor (67.47%) and Gap distance (0.5 mm). The ANOVA revealed that, the parameters have almost equal contribution for getting the optimum values that affects the surface finish and material removal rate. The results from the experiment reveals that the desirable result will be get at 0.5 mm gap distance and this would be taken as the optimum gap distance for the automatic feeding mechanism. In addition, low voltage and current would benefit for the EDM process working in micro level and for the removal of the recast layer.

Fast Color Straight Line Pattern Recognition in an Object Using High Speed Self Learning Devices

Most of the man-made objects are having some straight lines with colors. A very high-speed object recognition method using color straight line patterns is carried out using a novel self-learning device (RKD - Rasiq Krishnakumar Device). Instead of that Artificial Neural Networks (ANN), RKD based networks are used for different steps in this pattern classification. The color and straight-line features are extracted by using high-speed color segmentation and fast efficient straight-line segment extraction methods using the RKD based systems. The training and the testing algorithms of the pattern classification are using RKD-based processing. The fast color features extraction method uses an array of RKD-based devices and the fast efficient straight-line segment extraction method employs an array of processing elements and a main control unit. Some fusion devices are used for a straight line with colors features. The area of interest and the area of line segments of a particular object are other features for improving the accuracy of object classification.

Lane detection algorithm based on Hough transform for high-speed self driving vehicles

This study proposes a lane detection method based on expressway driving videos through a computer vision-based image processing system without using sensors. Both straight and curved sections can occur on a road, and thus, lanes must be detected by quickly determining such sections. The proposed method detects straight and curved sections that are estimated to be lanes using the Hough transform. When lanes are detected from actual images, the scope of left and right lanes is limited to reduce computational load. In this paper, we propose a lane-detection algorithm using the colour space and a stepwise algorithm for accurate lane detection. To verify the proposed algorithms, we developed a small self-driving vehicle model using a TX-2 board. The experiment results when applying the proposed Hough transform algorithm and lane-detection algorithm using the colour space show that the lane detection rate of vehicles driving on curves at high speed is approximately 96%. Through the extensive simulation results, the proposed algorithm to vehicle black boxes or autonomous driving will help prevent lane departure and reduce accident rates.

Implementation of High Speed Self Switching Frequency Agile RADAR

<div class="WordSection1"><p><strong><a href="mailto:suryak1986@yahoo.com"></a></strong></p></div><strong> </strong>The radar has to resist diversified jamming; High Speed self-adaptive frequency agility is an important and effective function for radars to resist jamming. The procedure to achieve this function are described, and the function is realized with FPGA using Hardware description Language, the validity is proved by on- line sampling and simulation. The High speed self-adaptive frequency agility module can analyze the type of jamming to select transmitting frequency to avoid the frequencies which have interference, under frequency diversity and fixed frequency, respectively. The general application on a searching radar shows that the module has good real-time and anti- jamming capacity.

RECONFIGURABLE SELF-ADDRESSABLE MEMORY-BASED FSM A SCALABLE INTRUSION DETECTION ENGINE

One way to detect and thwart a network attack is to compare each incoming packet with predefined patterns, also Called an attack pattern database, and raise an alert upon detecting a match. This article presents a novel pattern-matching Engine that exploits a memory-based, programmable state machine to achieve deterministic processing rates that are Independent of packet and pattern characteristics. Our engine is a self addressable memory based finite state machine (samFsm), whose current state coding exhibits all its possible next states. Moreover, it is fully reconfigurable in that new attack Patterns can be updated easily. A methodology was developed to program the memory and logic. Specifically, we merge “non-equivalent” states by introducing “super characters” on their inputs to further enhance memory efficiency without Adding labels. This is the most high speed self addressable memory based fsm.sam-fsm is one of the most storage-Efficient machines and reduces the memory requirement by 60 times. Experimental results are presented to demonstrate the Validity of sam-fsm.

Characterization of a 0.13 μm CMOS Link Chip using Time Resolved Emission (TRE)

The Picosecond Imaging Circuit Analysis (PICA) technique using the Superconducting Single-Photon Detector (SSPD) allows the detailed characterization of pulse width variations along the delay chain of a high speed Self Timing Interface (STI). Pulses gradually shrink and finally disappear along the delay chain.

Improved background compensation in atomic absorption spectrometry using the high speed self reversal method

The latest generation of atomic absorption spectrometers allows the quantitation of low and ultralow element concentrations with flame and furnace atomization in a wide variety of different applications. Nowadays, analytical procedures require instruments obtaining reliable and reproducible results with a minimum effort in time-consuming sample pre-treatment. In order to fulfill these items, automatic sampling systems and background compensation techniques are widely used to solve interference problems generated by samples. Furthermore, digital control of heating rates and gas flows as well as intelligent system control allows the accurate and full automatic measurement of multielement sequences up to 20 elements including the changeover of the atomization unit itself. During evaluation of different background compensation methods in flame and furnace operation deuteriumlamp-, high speed self reversal-, and Zeeman- effect based methods have been used. Data have been collected for various samples with typically high background levels. Analytical results for Zn, Cd and As are different according to the selection of the background compensation method. Additionally, differences in sensitivities must be considered. Problems and limitations of the deuterium background compensation method will be discussed and compared with experimental data generated using the high speed self reversal method and literature data.