The Experts below are selected from a list of 123 Experts worldwide ranked by ideXlab platform
Jinzhong Li - One of the best experts on this subject based on the ideXlab platform.
-
Method of automated BIT false alarms Simulation based on EDA
2011 6th IEEE Conference on Industrial Electronics and Applications, 2011Co-Authors: Jinzhong LiAbstract:The principle of built-in test false alarm Simulation (BFAS) is analyzed, with the definition of BFAS in this paper. Related false alarm inducing factors simulated by electronic design automation (EDA) techniques are determined, including load variations, power supply disturbances and electromagnetic interferences. The concept of false alarm Simulation Profile is proposed. The types and Simulation modes of false alarm inducing events are analyzed. The automated insertion algorithm of false alarm inducing events and the flow of BFAS are established, and verified using a typical circuit. It is shown that this method is feasible and effective, and can be used to analyze false alarms in the development stage.
J M Rodriguezizquierdo - One of the best experts on this subject based on the ideXlab platform.
-
the interpretation of hrem images of supported metal catalysts using image Simulation Profile view images
Ultramicroscopy, 1998Co-Authors: S Bernal, F J Botana, J J Calvino, C Lopezcartes, J A Perezomil, J M RodriguezizquierdoAbstract:Abstract The inherent problems of image Simulation when applied to the study of supported metal catalysts are analysed and discussed. The paper focuses on the consideration of Profile view images with reference to the fine details of the contrasts both in the metal particles and in the outer support layers. As a general conclusion we prove that complex contrasts which very often appear in the images can be interpreted on the grounds of the structural features of the catalysts and on the recording conditions in the microscope. This conclusion is supported by Simulation of several experimental images showing excellent fitting with the simulated ones. One key feature to face for a successful interpretation of metal/support discrete interfaces is the availability of a methodology to construct the complex supercells which are required as input data for the multislice Simulation programs. The paper includes a description of the approach followed for this aim in our lab, allowing to model size, shape, faceting, and relative orientation of metal and support particles. Some other definite aspects addressed specifically in this contribution are: (a) influence of support thickness, (b) influence of the metal particle position on the support, (c) effect of the metal particle size on its visibility and resolution, (d) assessment to the determination of reliable metal particle size by direct measurement from the images, and (e) influence of the crystal tilts in the imaging process. The influence of such variables in the image contrasts are analysed.
Dennis Fitzpatrick - One of the best experts on this subject based on the ideXlab platform.
-
Chapter 6 – Stimulus Editor
Analog Design and Simulation using OrCAD Capture and PSpice, 2020Co-Authors: Dennis FitzpatrickAbstract:Publisher Summary The Stimulus Editor is a graphical tool to help users define transient analog and digital sources. The sourcestm library contains three source parts each of which provides the interface with the defined stimulus in the Stimulus Editor. When users first place one of the sources from the sourcestm library, the implementation property is displayed in the schematic. This property refers to the name of the stimulus which is defined in the Stimulus Editor. Users can either enter a name of the stimulus on the schematic to start with, or get prompted for the stimulus name in the Stimulus Editor when started. When the Stimulus Editor starts, the New Stimulus window appears. The New Stimulus window allows users to define analog and digital signals, and prompts users to enter the stimulus name if they have not already defined the name in Capture. Stimulus editor transient sources include exponential (Exp) source, pulse source, VPWL, SIN (Sinusoidal), and SSFM (Single-frequency FM). Users can also use the waveforms generated by a transient analysis in Probe as a time–voltage source. An alternative method to create a time–voltage text file is to select the trace name in Probe, select copy, and paste the data into a text file. From version 16.3 onwards, the stimulus file is associated with the current active Simulation Profile and can be accessed via the Simulation Profile under the Configuration Files tab. In previous versions, there were separate tabs for Stimulus, Library, and Include options.
-
Chapter 15 – Temperature Analysis
Analog Design and Simulation using OrCAD Capture and PSpice, 2020Co-Authors: Dennis FitzpatrickAbstract:Publisher Summary A change in temperature can affect the performance and characteristics of a circuit. The components most affected by a change in temperature include semiconductors, resistors, capacitors, and inductors. All of these components have an inbuilt temperature dependence model parameter such that performing a temperature sweep will change component and subsequent circuit behavior. The temperature coefficients specified for resistors are given in parts per million per degree Celsius (ppm/°C). In previous versions of OrCAD, the temperature coefficients were not readily available on the Capture parts therefore to add TC1 and TC2. Breakout parts as used for Monte Carlo analysis are used, where the temperature coefficients are added to the PSpice model definition. An AC, DC, or transient analysis is normally run using the default nominal temperature (TNOM) of 27_C, which is set in the Simulation Profile under the Options tab. TNOM is the default nominal temperature and is also the temperature at which model parameters were measured. If users want to run a transient analysis at a different temperature then they need to specify the Simulation temperature by selecting Temperature (Sweep) in the Simulation Profile and then entering either a single Simulation temperature or a list of temperatures values.
-
Chapter 19 – Mixed Simulation
Analog Design and Simulation using OrCAD Capture and PSpice, 2020Co-Authors: Dennis FitzpatrickAbstract:Publisher Summary PSpice uses the same Simulation engine for analog and digital circuits. The Simulation results in Probe share the same time axis, but are split into separate analog and digital plot windows. Analog and digital components in a circuit are connected together at nodes. In PSpice there are three types of connecting nodes: analog (where all connected parts are analog), digital (where all connected parts are digital), and interface (where there is a mixture of analog and digital parts). Interface nodes are automatically separated into one analog node and one or more digital nodes by inserting analog and digital interface subcircuits, which are either analog to digital (AtoD), or digital to analog (DtoA) interface subcircuits. These subcircuits will also have their own power supply. As this process is automatic and runs behind the scenes, one does not normally have to worry about the interface subcircuits, although they are available as traces in Probe. The pull-up resistor is connected to the digital power supply and the output ground for the comparator is connected to digital ground. The digital waveforms being plotted in the upper area of Probe and the analog waveforms plotted in the lower area are also presented. Mixed analog and digital circuits follow the same procedure for placing parts, creating a Simulation Profile, and Simulation.
-
Monte Carlo Analysis
Analog Design and Simulation using OrCAD Capture and PSpice, 2020Co-Authors: Dennis FitzpatrickAbstract:Monte Carlo analysis is essentially a statistical analysis that calculates the response of a circuit when device model parameters are randomly varied between specified tolerance limits according to a specified statistical distribution. Monte Carlo analysis provides statistical data predicting the effect of randomly varying model parameters or component values (variance) within specified tolerance limits. The generated values follow a statistically defined distribution. The circuit analysis (DC, AC, or transient) is repeated a number of specified times with each Monte Carlo run generating a new set of randomly derived component or model parameter values. The greater the number of runs, the greater the chances that every component value within its tolerance range will be used for Simulation. Monte Carlo, in effect, predicts the robustness or yield of a circuit by varying component or model parameter values up to their specified tolerance limits. Although the results of a Monte Carlo analysis can be seen as a spread of waveforms in the PSpice waveform viewer (Probe), a Performance Analysis can be used to generate and display histograms for the statistical data together with a summary of the statistical data. This provides a more visual representation of the statistical results of a Monte Carlo analysis. A Monte Carlo analysis is run in conjunction with another analysis, AC, DC, or transient analysis. Tolerances are applied to parts in the schematic via the Property Editor and the required analysis is created in the Simulation Profile.
-
Chapter 3 – DC Analysis
Analog Design and Simulation using OrCAD Capture and PSpice, 2020Co-Authors: Dennis FitzpatrickAbstract:Publisher Summary The DC analysis calculates the circuit's bias point over a range of values when sweeping a voltage or current source, temperature, a global parameter, or a model parameter. The swept value can increase in a linear or a logarithmic range, or can be a list of increasing values. This is useful, for example, if users want to see the circuit response for a change in the supply voltage, or to see how a change in a resistor value affects the circuit response. The DC sweep also allows for nested sweeps such that one of the two variables is kept constant while sweeping the other variable. For a DC sweep analysis, users have to select PSpice > New Simulation Profile and select DC Sweep for the Analysis type. The Sweep Variable should be set to Voltage source. Markers are used to record the voltages on nodes or currents through components, and are accessed from the PSpice menu. They enable data to be automatically displayed as a waveform in the PSpice waveform viewer, which is known as the Probe window. Voltage markers are placed on wires, whereas current markers must be placed on a component pin. A message appears if users try to place a current marker on a wire instead of a component pin. The component pin is a different color to a wire. For power markers, the markers are placed on the body of the device. When the Simulation is run, PSpice launches, and Probe plots the two voltage traces at nodes in and out.
Weiran An - One of the best experts on this subject based on the ideXlab platform.
-
A design of Simulation and analysis platform of BIT false alarm considering stochastic characteristics
2014 Prognostics and System Health Management Conference (PHM-2014 Hunan), 2014Co-Authors: Weiran AnAbstract:Base on a comprehensive analysis of causes and classification of BIT false alarm, the stochastic characteristics mechanism of BIT false alarm is summarized, the parameters for BIT false alarm assessment is proposed, and the breakthrough of the method of BIT false alarm caused by which the noise analog and the research of BIT modeling and Simulation methods considering stochastic characteristics. Therefore, the design of interface Profile of BIT false alarm considering stochastic characteristics is completed. According to the methods of Simulation, modeling and assessment of BIT false alarm considering stochastic characteristics, the Simulation platform of BIT false alarm randomness is designed, combined with typical BIT false alarm circuit Simulation cases in addition to provide technical support to apply for the practical application of engineering tools According to the existing Simulation analysis of BIT false alarm circuit, considering the description of randomness factors and stochastic characteristics considering interference, study the BIT detection threshold randomness modeling, the methods of Simulation considering the randomness of BIT, the design of false alarm Simulation Profile considering stochastic characteristics are achieved. Moreover, the process of working on the Simulation platform is completed into designing framework and the functional modules in accordance with completing the design of input and output data structure, and the overall algorithm of Simulation platform, through the communication interface of Matlab, Orcad and Labview joint Simulation to complete the final design of each function, and the randomness of BIT false alarm.
S Bernal - One of the best experts on this subject based on the ideXlab platform.
-
the interpretation of hrem images of supported metal catalysts using image Simulation Profile view images
Ultramicroscopy, 1998Co-Authors: S Bernal, F J Botana, J J Calvino, C Lopezcartes, J A Perezomil, J M RodriguezizquierdoAbstract:Abstract The inherent problems of image Simulation when applied to the study of supported metal catalysts are analysed and discussed. The paper focuses on the consideration of Profile view images with reference to the fine details of the contrasts both in the metal particles and in the outer support layers. As a general conclusion we prove that complex contrasts which very often appear in the images can be interpreted on the grounds of the structural features of the catalysts and on the recording conditions in the microscope. This conclusion is supported by Simulation of several experimental images showing excellent fitting with the simulated ones. One key feature to face for a successful interpretation of metal/support discrete interfaces is the availability of a methodology to construct the complex supercells which are required as input data for the multislice Simulation programs. The paper includes a description of the approach followed for this aim in our lab, allowing to model size, shape, faceting, and relative orientation of metal and support particles. Some other definite aspects addressed specifically in this contribution are: (a) influence of support thickness, (b) influence of the metal particle position on the support, (c) effect of the metal particle size on its visibility and resolution, (d) assessment to the determination of reliable metal particle size by direct measurement from the images, and (e) influence of the crystal tilts in the imaging process. The influence of such variables in the image contrasts are analysed.
