Storing Test Data Research Articles

A material constants estimation method for efficient elastic–plastic–creep simulation of aluminum alloys by effective utilization of stored test data

A material constants estimation method for efficient elastic–plastic–creep simulation of aluminum alloys by effective utilization of stored test data

Design and Development of an Innovative Test Device Capable of Automatically Performing Carpet Static Loading Tests

The resistance of carpets to texture deformation is considered one of the most important properties that affects the quality of carpet. Static load is an essential factor that has a profound impact on carpets causing compression of carpet pile yarns. Mainly, two tests are available to determine the compressibility and resilience performance of carpets, namely thickness loss after brief moderate static loading and thickness loss after prolonged heavy static loading. Currently, the commercially available test devices have drawbacks, including a requirement for an additional apparatus to test performance, conducting tests manually which leads to personal faults, and inability of storing test data. In this study, a newly developed test device for measuring compressibility and resilience performance of carpet was designed and manufactured. The newly designed test device is statistically verified and capable of performing carpet thickness measurement, brief moderate static loading and prolonged heavy static loading tests automatically.

Storage-Based Built-In Self-Test for Gate-Exhaustive Faults

Built-in self-test (BIST) approaches are suitable for in-field testing since they do not require a tester for storage and application of test data. They also reduce the security vulnerabilities associated with loading and unloading of external test data into scan chains. As technologies evolve, in-field testing needs to address more complex defect and aging mechanisms that require specific deterministic tests. This can be addressed by BIST approaches that store test data on-chip and use the data for on-chip generation of both random and deterministic tests. In this case, there is a tradeoff between the amount of stored test data and the comprehensiveness of the test set that can be applied. This article explores this tradeoff in a specific context that has the following main features: 1) the initial stored test data is based on a stuck-at test set; 2) the target faults are single-cycle gate-exhaustive faults; and 3) the stored test data is enhanced gradually by test data based on a gate-exhaustive test set to increase the coverage of gate-exhaustive faults.

Investigasi Kondisi Permukaan Isulator Tegangan Tinggi berbasis Machine Learning TensorFlow

The insulator plays an essential role in preventing the flow of current from the phase conductor to the earth through supporting towers so that the insulation is a significant part of the electrical energy transmission system. Generally, high-voltage insulators are widely used as external plug insulators, for that the performance of insulators is influenced by environmental conditions that indirectly affect the surface condition of the insulators. In this study, a diagnostic tool used in the testing surface of the insulator, which can classify mechanically whether the insulator is good or damaged. The classification method uses TensorFlow Machine learning. Machine Learning is used as a brain in the isolation classification process while TensorFlow functions to store training data and test data in the classification process. The results obtained from this study show the accuracy of classification data is 98%.

Direct Computation of LFSR-Based Stored Tests for Broadside and Skewed-Load Tests

Using both broadside and skewed-load tests for delay faults provides a higher fault coverage and more compacted test sets. An earlier work showed that it is possible to share input test data between broadside and skewed-load tests, and thus reduce the input test data volume. This article develops an algorithm for computing stored tests that can be used for applying both broadside and skewed-load tests in the context of a specific test data compression method. Under this method, a programmable linear-feedback shift register is used for on-chip decompression. In the stored test data, a stored test consists of a seed and two primary input vectors. The seed determines the scan-in state of the applied broadside or skewed-load test as well as the additional scan-in vector required for a skewed-load test. In the algorithm developed in this article, stored tests are computed directly without first computing broadside or skewed-load tests. This avoids situations where the tests cannot be compressed or do not have common input test data.

Real Time Temperature Monitoring

The purpose of this project is to measure the temperature through a thermistor inserted into a properly sized circuit.This implementation was designed to be possible, given the characteristics of the used sensor, a measurement in the range of -5 to 270 oC, although the temperatures of interest of this application are between 18 and 35 oC.For the analysis of this measure, as well as for the control, an application was developed in MatLab. This software allows, not only programming and processing the acquired signal, but also serves as a graphical interface where it is possible to monitor the entire process in real time. For the acquisition of the analog signal, was uses an Arduino UNO board.Inside of the MatLab environment, a screen has been developed that allows visualizing the temperature evolution in real time, as well as verifying if it is inside the stipulated limit. The developed application also allows the system to stop and store test data in a file for later calculations.For a better framing, this circuit can be considered as a system developed for temperature control of a typical classroom.That being said, the is then to control the temperature, stipulating limit values, to visualize its evolution in real time through an indicator and a graph and to collect data for later calculations.

IPRM: IP core resource multiplexing of core wrapper design for reducing test application time in DVFS-based multicore SoCs

A modify wrapper/test access mechanism(TAM) structure is described to explore the maximal potential capacity of TAM, named “IP cores resource multiplexing(IPRM)”, reducing test application time for DVFS-based multicore System-on-Chips(MSoCs). The IPRM core wrappers, different from standard wrappers, enable to isolated core wrapper resource again to store test data for embedded cores under test. An integer linear programming (ILP) formulation with IPRM wrapper is proposed to improve multi-site test. Experimental results of the ITC’02 SoC Benchmark show that IPRM core wrapper reduces the burdens on ATE effectively, and can reduce the test application time by 10–50%.

Effects of Trace Elements on Corrosion in Total Immersion and under Wet/Dry Conditions

Abstract The effects of 13 trace elements in a base line solution that is considered to represent flue gas desulfurization environments have been studied by electrochemical measurements for five alloys that were totally immersed or immersed for 1 h/day. Polarization resistance and corrosion potential measurements were performed continuously for 10 electrodes per test solution over a 6-day period, resulting in approximately 600 measurements per test. A computerized system was used to store test data and analyze results. Very large differences in corrosion behavior were observed for the five alloys in a solution containing a given combination of trace elements and for a given alloy in solutions containing different combinations of trace elements. A statistical analysis has been performed to determine the trace elements that have significant effects on corrosion behavior.