scholarly journals Pulsing Test for Defect of Resistive Word Line in DRAM Main Cell using WGFMU (Waveform Generator Fast Measurement Unit)

2021 ◽  
Author(s):  
JaeYun Lee ◽  
EuiSeok Kim ◽  
JunYeal Lim ◽  
SeokHoon Oh ◽  
YoungHa Park
Keyword(s):  
High Resistance ◽  
Pulse Generator ◽  
Measurement Unit ◽  
Saturation Current ◽  
Waveform Generator ◽  
Fast Measurement ◽  
Main Cell ◽  
Cell Sample ◽  
The Difference

Abstract In this paper, we compare and describe the difference between the oscilloscope pulsing test and the WGFMU (Waveform Generator Fast Measurement Unit) in analyzing the defect of high resistance in DRAM main cell sample. The nanoprobe system has many constraints in the pulsing analysis utilizing the oscilloscope and pulse generator. There are certain cases where the system cannot support analysis when the saturation current is extremely minimal, such as the DRAM cell. In this paper, we address this constraint and propose a new way to conduct pulsing tests using the WGFMU's arbitrary linear waveform generator in the nanoprobe system.

Design and Test of a MEMS Accelerometer Array for Submarine Landslide Displacement Monitoring

2021 ◽  
Vol 55 (1) ◽  
pp. 5-16
Author(s):  
Yongqiang Ge ◽  
Jiawang Chen ◽  
Chen Cao ◽  
Jiamin He ◽  
Yan Sheng ◽  
...  
Keyword(s):  
Gas Hydrate ◽  
Integrated Circuit ◽  
Slope Failure ◽  
Circuit Board ◽  
Measurement Unit ◽  
Physical Model Test ◽  
Submarine Landslides ◽  
Micro Electro Mechanical Systems ◽  
Mems Accelerometer ◽  
The Difference

AbstractSubmarine landslides in gas hydrate areas are a significant geo-hazard that can cause considerable damage. The processes and mechanism of submarine landslides caused by gas hydrate dissociation are not clearly understood. Therefore, we designed a micro-electro-mechanical systems (MEMS) accelerometer array to study and monitor the deep displacement of submarine landslides. The MEMS accelerometer array consists of several gravity acceleration-sensing units that are protected and positioned using a flexible circuit board and elastic steel tape, such that all the units are connected to an Inter-Integrated Circuit (IIC) communication bus. By sensing the three-axis tilt angles, the direction and magnitude of the displacement for a measurement unit can be calculated; then, the overall displacement of the array is calculated as the difference in the displacements from the initial values. To ensure the accuracy of the tilt angle and displacement calculation, the calibration and verification test of the single MEMS sensor and sensor array is conducted. The MEMS accelerometer array is verified with respect to its principle and arrangement by a laboratory physical model test, and the initial experimentation demonstrated the capacities of the monitoring system for collecting real-time and in-situ information about the dynamic process and propagation of slope failure.

scholarly journals PMU and DVR based Power System Monitoring, Controlling and Voltage sag Compensation

2020 ◽  
Vol 32 ◽  
pp. 01006
Author(s):  
Abhishek Chalwadi ◽  
Kiruthika M ◽  
Bindu S
Keyword(s):  
Power System ◽  
Power Quality ◽  
Measurement Unit ◽  
Voltage Sag ◽  
Dynamic Voltage Restorer ◽  
Power System Monitoring ◽  
Voltage Restorer ◽  
Dynamic Voltage ◽  
The Difference ◽  
Compensation Device

The power system network is becoming dense and much more complex. Dynamic and continuous monitoring of the power system network is required to avoid power outages. Phasor Measurement Unit (PMU) is one such device that provides state estimation parameters of dynamic power system networks that are used for designing relays and controlling the system network. Power Quality problems such as voltage sags and swells can damage the sensitive load and cause abnormal voltage, current, and frequency conditions in a power system network. Fast and major developments in power electronics technology have made it possible to mitigate the power quality problems. Dynamic Voltage Restorer (DVR) is a voltage sag compensation device that compensates the difference in voltage avoiding interruptions and restores the voltage to the pre-fault value. This paper discusses a technique used for monitoring, protecting, and controlling the system under fault condition using PMU and compensate voltage sag for a sensitive load using DVR based on the data collected by placing PMU in an optimal location. The outcome of the above analysis is recorded which shows that effective monitoring, controlling, and voltage sag compensation can be done with less number of PMU’s placed optimally in conjunction with DVR.

scholarly journals On the conductivity of a gas, between parallel plate electrodes, when the current approaches the maximum value

1911 ◽  
Vol 86 (583) ◽  
pp. 72-77 ◽  
Keyword(s):  
Atmospheric Pressure ◽  
Parallel Plate ◽  
Complete Solution ◽  
Negative Electrode ◽  
Negative Ions ◽  
Saturation Current ◽  
Maximum Value ◽  
The Difference ◽  
Minimum Force ◽  
Made In

The relation connecting the current with the potential difference between parallel plate electrodes when the gas between the plates has been uniformly ionised by Röntgen rays or Becquerel rays has been investigated theoretically by many physicists. In all cases various assumptions are made in order to simplify the calculations, as the problem becomes very complicated when the disturbance of the field due to the separation of the ions is taken into consideration. Perhaps the most complete solution is that given by Mie, in which the only effect that is neglected is that of diffusion. The difference between the velocities of the positive and negative ions is taken into consideration, and the disturbance of the field due to the charge in the gas produced by the excess of ions of one sign in the neighbourhood of the electrodes. The method of analysis, consisting of a series of approximations, is difficult, but the results have been presented in a convenient form, for currents in air at atmospheric pressure that are certain fractions of the saturation current. A curve is given for each current which shows the distribution of force between the plates. The currents investigated ranged between those that were one-fifth and nine-tenths of the saturation current. In the former case the ratio of the electric force at the negative electrode to the minimum force in the filed was found to be 2.7. The ratio diminishes as the force increases, and for the current that is nine-tenths of the saturation current the ratio becomes 1.39.

scholarly journals STUDY ON IMPROVEMENT OF ACCURACY IN INERTIAL PHOTOGRAMMETRY BY COMBINING IMAGES WITH INERTIAL MEASUREMENT UNIT

2016 ◽  
Vol XLI-B5 ◽  
pp. 501-505
Author(s):  
Hideaki Kawasaki ◽  
Shojiro Anzai ◽  
Toshio Koizumi
Keyword(s):  
Calculation Method ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Feature Points ◽  
Error Growth ◽  
Actual Length ◽  
Inertial Measurement ◽  
Point Groups ◽  
The Difference ◽  
Time Accumulation

Inertial photogrammetry is defined as photogrammetry that involves using a camera on which an inertial measurement unit (IMU) is mounted. In inertial photogrammetry, the position and inclination of a shooting camera are calculated using the IMU. An IMU is characterized by error growth caused by time accumulation because acceleration is integrated with respect to time. <br><br> This study examines the procedure to estimate the position of the camera accurately while shooting using the IMU and the structure from motion (SfM) technology, which is applied in many fields, such as computer vision. <br><br> When neither the coordinates of the position of the camera nor those of feature points are known, SfM provides a similar positional relationship between the position of the camera and feature points. Therefore, the actual length of positional coordinates is not determined. If the actual length of the position of the camera is unknown, the camera acceleration is obtained by calculating the second order differential of the position of the camera, with respect to the shooting time. The authors had determined the actual length by assigning the position of IMU to the SfM-calculated position. Hence, accuracy decreased because of the error growth, which was the characteristic feature of IMU. In order to solve this problem, a new calculation method was proposed. Using this method, the difference between the IMU-calculated acceleration and the camera-calculated acceleration can be obtained using the method of least squares, and the magnification required for calculating the actual dimension from the position of the camera can be obtained. The actual length can be calculated by multiplying all the SfM point groups by the obtained magnification factor. This calculation method suppresses the error growth, which is due to the time accumulation in IMU, and improves the accuracy of inertial photogrammetry.

scholarly journals STUDY ON IMPROVEMENT OF ACCURACY IN INERTIAL PHOTOGRAMMETRY BY COMBINING IMAGES WITH INERTIAL MEASUREMENT UNIT

2016 ◽  
Vol XLI-B5 ◽  
pp. 501-505 ◽  
Author(s):  
Hideaki Kawasaki ◽  
Shojiro Anzai ◽  
Toshio Koizumi
Keyword(s):  
Calculation Method ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Feature Points ◽  
Error Growth ◽  
Actual Length ◽  
Inertial Measurement ◽  
Point Groups ◽  
The Difference ◽  
Time Accumulation

Inertial photogrammetry is defined as photogrammetry that involves using a camera on which an inertial measurement unit (IMU) is mounted. In inertial photogrammetry, the position and inclination of a shooting camera are calculated using the IMU. An IMU is characterized by error growth caused by time accumulation because acceleration is integrated with respect to time. &lt;br&gt;&lt;br&gt; This study examines the procedure to estimate the position of the camera accurately while shooting using the IMU and the structure from motion (SfM) technology, which is applied in many fields, such as computer vision. &lt;br&gt;&lt;br&gt; When neither the coordinates of the position of the camera nor those of feature points are known, SfM provides a similar positional relationship between the position of the camera and feature points. Therefore, the actual length of positional coordinates is not determined. If the actual length of the position of the camera is unknown, the camera acceleration is obtained by calculating the second order differential of the position of the camera, with respect to the shooting time. The authors had determined the actual length by assigning the position of IMU to the SfM-calculated position. Hence, accuracy decreased because of the error growth, which was the characteristic feature of IMU. In order to solve this problem, a new calculation method was proposed. Using this method, the difference between the IMU-calculated acceleration and the camera-calculated acceleration can be obtained using the method of least squares, and the magnification required for calculating the actual dimension from the position of the camera can be obtained. The actual length can be calculated by multiplying all the SfM point groups by the obtained magnification factor. This calculation method suppresses the error growth, which is due to the time accumulation in IMU, and improves the accuracy of inertial photogrammetry.

Highway Cross-Slope Measurement using Mobile LiDAR

2018 ◽  
Vol 2672 (39) ◽  
pp. 88-97 ◽  
Author(s):  
Alireza Shams ◽  
Wayne A. Sarasua ◽  
Afshin Famili ◽  
William J. Davis ◽  
Jennifer H. Ogle ◽  
...  
Keyword(s):  
South Carolina ◽  
Laser Scanning ◽  
Effective Means ◽  
Cost Effective ◽  
Measurement Unit ◽  
Ground Control ◽  
Lidar Data ◽  
Ground Control Points ◽  
South Carolina Department ◽  
The Difference

Ensuring adequate pavement cross-slope on highways can improve driver safety by reducing the potential for ponding to occur or vehicles to hydroplane. Mobile laser scanning (MLS) systems provide a rapid, continuous, and cost-effective means of collecting accurate 3D coordinate data along a corridor in the form of a point cloud. This study provides an evaluation of MLS systems in terms of the accuracy and precision of collected cross-slope data and documentation of procedures needed to calibrate, collect, and process this data. Mobile light detection and ranging (LiDAR) data were collected by five different vendors on three roadway sections. The results indicate the difference between ground control adjusted and unadjusted LiDAR derived cross-slopes, and field surveying measurements less than 0.19% at a 95% confidence level. The unadjusted LiDAR data incorporated corrections from an integrated inertial measurement unit and high-accuracy real-time kinematic GPS, however it was not post-processed adjusted with ground control points. This level of accuracy meets suggested cross-slope accuracies for mobile measurements (±0.2%) and demonstrates that mobile LiDAR is a reliable method for cross-slope verification. Performing cross-slope verification can ensure existing pavement meets minimum cross-slope requirements, and conversely is useful in identifying roadway sections that do not meet minimum standards, which is more desirable than through crash reconnaissance where hydroplaning was evident. Adoption of MLS would enable the South Carolina Department of Transportation (SCDOT) to address cross-slope issues through efficient and accurate data collection methods.

scholarly journals Multi-set Pre-processing of Multicolor Flow Cytometry Data

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rita Folcarelli ◽  
Gerjen H. Tinnevelt ◽  
Bart Hilvering ◽  
Kristiaan Wouters ◽  
Selma van Staveren ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cells ◽  
Classification Performance ◽  
Multivariate Methods ◽  
Measurement Variability ◽  
Flow Cytometry Data ◽  
Cell Sample ◽  
The Difference ◽  
Analytical Technology ◽  
Number Of Cells

Abstract Flow Cytometry is an analytical technology to simultaneously measure multiple markers per single cell. Ten thousands to millions of single cells can be measured per sample and each sample may contain a different number of cells. All samples may be bundled together, leading to a ‘multi-set’ structure. Many multivariate methods have been developed for Flow Cytometry data but none of them considers this structure in their quantitative handling of the data. The standard pre-processing used by existing multivariate methods provides models mainly influenced by the samples with more cells, while such a model should provide a balanced view of the biomedical information within all measurements. We propose an alternative ‘multi-set’ preprocessing that corrects for the difference in number of cells measured, balancing the relative importance of each multi-cell sample in the data while using all data collected from these expensive analyses. Moreover, one case example shows how multi-set pre-processing may benefit removal of undesired measurement-to-measurement variability and another where class-based multi-set pre-processing enhances the studied response upon comparison to the control reference samples. Our results show that adjusting data analysis algorithms to consider this multi-set structure may greatly benefit immunological insight and classification performance of Flow Cytometry data.

scholarly journals Performance of Implementing Smart DFT in Micro Phasor Measurement Unit

2018 ◽  
Vol 69 ◽  
pp. 01005
Author(s):  
Chao-Yuan Lai ◽  
Tien-Yen Yang ◽  
Chih-Wen Liu
Keyword(s):  
Power System ◽  
Fourier Transforms ◽  
Dft Method ◽  
Phasor Measurement Unit ◽  
Measurement Unit ◽  
Digital Measurement ◽  
Waveform Generator ◽  
Discrete Fourier Transforms ◽  
Frequency Information ◽  
Phasor Measurement

The advance of the signal processing, this paper implement a more accurate digital measurement algorithm, Smart DFT(SDFT) in Micro Phasor Measurement Unit(μPMU), which is based on Discrete Fourier Transforms(DFT) to estimate frequency information from Taiwan power system. μPMU, the sensor we plan to acquire the information from the power system by using the signal of outlet voltage-level 110V in Taiwan, such as frequency, voltage and angle. The performance of SDFT implemented in μPMU represents a more precise frequency information when frequency fluctuation occurred just as the frequency of power system. We offer the results of simulations, stable frequency generated from waveform generator and real frequency from main electricity to compare SDFT with DFT method which implemented in μPMU.

scholarly journals Principal Characteristics of Affected and Unaffected Side Trunk Movement and Gait Event Parameters during Hemiplegic Stroke Gait with IMU Sensor

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7338
Author(s):  
Jeong-Woo Seo ◽  
Seul-Gee Kim ◽  
Joong Il Kim ◽  
Boncho Ku ◽  
Kahye Kim ◽  
...  
Keyword(s):  
Principal Component ◽  
Assessment Tools ◽  
Measurement Unit ◽  
Control Group ◽  
Trunk Movement ◽  
Unaffected Side ◽  
Principal Characteristics ◽  
Diagnosis Method ◽  
Healthy Side ◽  
The Difference

This study describe the characteristics of hemiplegic stroke gait with principal component analysis (PCA) of trunk movement (TM) and gait event (GE) parameters by the inertial measurement unit (IMU) sensors: (1) Background: This process can determine dominant variables through multivariate examination to identify the affected, unaffected, and healthy lower-limb sides; (2) Methods: The study monitored forty patients with stroke and twenty-eight healthy individuals comprising the control group for comparison. The IMU sensors were attached to each subject while performing a 6 m walking test. Sixteen variables extracted from the measured data were divided into 7 GE and 9 TM variables explaining pelvis tilt, oblique, and rotation. (3) Results: The tilt range variables of the trunk movement on the affected and unaffected sides were lower than those of the healthy side; this showed between-group differences in various GE variables. For the healthy and affected sides, 80% of variances were explained with 2 or 3 PCs involving only a few dominant variables; and (4) Conclusions: The difference between each side leg should be considered during the development of a diagnosis method. This research can be utilized to develop functional assessment tools for personalized treatment and to design appropriate training protocols.

scholarly journals Application of Circuit Modeling in the Study of Spark Formation During Electroerosion Treatment

2021 ◽  
Vol 248 ◽  
pp. 04016
Author(s):  
Artur Porvatov ◽  
Mikhail Kozochkin ◽  
Ilya Minin ◽  
Andrey Maslov ◽  
Vladimir Kuptsov ◽  
...  
Keyword(s):  
Pulse Generator ◽  
Electrical Discharge Machining ◽  
Short Circuit ◽  
Electrical Parameters ◽  
Time Period ◽  
Interelectrode Gap ◽  
Functional Blocks ◽  
The Difference ◽  
Two Parameters ◽  
Edm Process

Electrical discharge machining (EDM) of a workpiece is a complex, fast-flowing process characterized by alternating (intermittent) states: short circuit, idle and spark formation. The discontinuity of the EDM process means that the processing is carried out in single pulses, which are formed by a special pulse generator. The parameters of the generator pulses can be divided into time and electrical. The time period and duration of the pulses, as well as the difference between these two parameters (the “silence” interval), are considered temporary. The electric ones include the amplitude value of the voltage, the maximum permissible current, and the polarity of the pulses. in addition, depending on the device of the generator, the pulses can be composite, for example, have an igniting pulse with a higher voltage and a lower current than the main (working) pulse. In this work, we have developed a interelectrode gap model that allows not only to obtain values of electrical parameters, but also to evaluate and to optimize the electrical parameters of materials being processed with known electrical properties. The key advantage of this model is its modularity, which allows to add new functional blocks, which describe external and internal influences, for example, the concentration of erosion products, uneven electrical conductivity of the workpiece, and others, without changing its structure.

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