Identification of Optimal Process Parameters in Electro-Discharge Machining Using ANN and PSO

Electrical Discharge Machining (EDM) process is a widely used machining process in several fabrication, construction and repair work applications. Considering Pulse-On Time, Pulse OFF time, Peak-Current and Gap voltage as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness are considered as outputs. In order to reduce the number of experiments Design of Experiments (DOE) was undertaken using Orthogonal Array and later on the outputs were optimized using ANN and PSO. It was found that the results obtained from both the techniques were tallying with each other.

Pulse interference identification and suppression for OFDM signal

The new generation smart meter is the core node of information acquisition and flows in the power Internet of Things (IoT). Because it is powered by the low-voltage power line, various short-time pulse interference signals in the line can be easily coupled to the received signal of the communication module embedded in the meter, resulting in the degradation of communication performance. In view of this situation, an identification-suppression algorithm of the short-time pulse-interference signal is proposed. The core idea is to comprehensively judge the existence of the interference signal and its specific position in the time domain based on the energy ratio of adjacent OFDM symbols and the change of mean square error value between frequency domain amplitude signals. Based on this, an interference energy elimination scheme with an adaptive threshold is realized. Theoretical analysis and simulation results show that the scheme has low computational complexity, high accuracy of pulse interference identification and position judgment, and can effectively reduce the energy of pulse interference signal, and thus improving the decoding performance of OFDM while it receives signals.

Nonlinear Pulse-Time Conversion in Radioisotope Devices: Analysis and Application Possibilities

The paper considers the operation of radioisotope measuring devices under dynamic conditions, when the Poisson pulse flux at the output of the radiation detector becomes unsteady and the nonlinearity of the calibration curve of the device, the stochasticity of the radiation signal and the inertia of the meter significantly complicate the task of estimating the measured physical parameter. of the device and analysis of the possibility of its application for linearization of the characteristics of the device, increasing the speed of the devices and solving the measuring problem in real time.The process of nonlinear transformation of the radiation signal in the system is analyzed on the basis of the assumption about the exponential distribution of the intervals between the pulses of the information flow at the output of the radiation detector. A generalized algorithm for the synthesis of a given transformation function of a time-pulse computing device of a radioisotope device has been developed according to its mathematical description. To describe the transformation function given by a set of points, it is proposed to use its approximation by a power series.The proposed calculation formulas are verified by modeling in the Scilab program on a specific example of linearization of the curve of a radioisotope altimeter with a given tabular calibration characteristic. The results obtained confirm the expediency of using time-pulse computing devices for linearizing the conversion curve of radioisotope devices in real time.Carrying out calculations according to the proposed algorithms by means of modern microelectronics opens up new possibilities for expanding the field of application of radioisotope devices in dynamic problems of industrial flaw detection, measuring the parameters of object movement, thickness of rolled products and coatings, in devices for continuous monitoring of liquid media.

Predictive Analysis for Real Time Stress Detection

Stress can be characterized as a feeling of either emotional or physical tension. Due to the biology of the human body, it releases some hormones when under stress. These hormones might cause tensed muscles, increase pulse rate or the heart rate, increase brain activity to make the brain more alert to the surrounding. Stress can be predicted well before it happens by constantly measuring the Heart Rate Variability (HRV) parameters obtained using the pulse sensor. In this project a supervised machine learning model is created using the data acquired from Physionet, once the data is acquired it is cleaned and the missing data is filled. This data set is later used to create a random forest classifier and is saved using pickle library. Once the model is created it is used to detect stress in real time. Pulse sensor amped is used to get the required pulse data in the form of a CSV file and a numpy array is created using inter beat interval information got from pulse sensor. Once a numpy array is created neurokit2 library is used to extract the HRV information of the R-R interval. Later these parameters are compared with the created model and checked to see if the subject is stressed, if the model detects the subject as stressed an alerting message is sent to the subject’s smartphone using Twilio.

A Pulse-Multiplication Proposal for MIRACLES, the Neutron TOF-Backscattering Instrument at the European Spallation Source

The fixed-energy window scan approach, for both elastic and inelastic modes, is a valuable tool to discriminate between motions activated when dynamical phase transitions occur in a sample as a function of time, temperature, pressure, electrical field or illumination. Considering that, on one hand, such variations can generate a weak signal, and on the other, high data throughput makes it possible to screen many samples during a beam time, pulse multiplication is an ideal strategy to optimize the intensity of the analyzed signal. To ensure this capability, a proposal for a future upgrade of MIRACLES, the neutron time-of-flight backscattering spectrometer at the European Spallation Source (ESS) under construction in Lund, is reported in this article. The concept for a new chopper layout relies on the extraction of several elastic pulses, ensuring an increase in the neutron total elastic intensity hitting the sample. This proposal can be extended to the inelastic counterpart. The premise is to maintain the original beamline layout without modification, either of the guide sections or of the current chopper layout of MIRACLES, thereby guaranteeing that minimal changes and impact will occur during the proposed upgrade. However, this also presents a significant challenge, namely, to achieve an efficient pulse multiplication within the width and the length of the guide and within the rising/decay time of the pulses. With the concept presented here, an increase in elastic intensity by a factor of 2.8 was obtained. This is analogous to performing elastic fixed window (EFW) measurements with an ESS source operating at 14 MW, widening considerably the performance capabilities of MIRACLES. The knowledge generated here is also valuable for the design of scientific instruments for the next generation of low-energy, accelerator-driven neutron sources.

Experimental Evaluation on Corner Accuracy in WEDM for Aluminium 6061 Alloy

An important electro-thermal process known as wire electrical discharge machining (WEDM) is applied for machining of conductive materials to generate most precisely. All cutting inaccuracies of WEDM arise out of the major cause of wire bending. At the time of cutting a sharp corner or cut profile, bending of the wire leads to a geometrical error on the workpiece. Though this type of error may be of a few hundred microns, it is not suitable for micro applications. In this research study, an experimental investigation based on response surface methodology (RSM) has been done on wire EDM of Aluminium 6061 t6 alloy. This chapter studies the outcome of input process variables (i.e., wire feed rate, pulse on time, pulse off time, and gap voltage) on machining output responses (i.e., corner inaccuracy) extensively. Experimental validation of the proposed model shows that corner inaccuracy value may be reduced by modification of input parameters.

Time-pulse method of single-phase half-bridge inverter control in formation of the harmonic load current

The paper discusses the methods for harmonic current formation in DC to AC converters. The authors propose a timepulse method for control of switches in a half-bridge inverter for formation of the harmonic load current in a wide range of amplitude and output current frequency adjustment.