I am new to image processing toolbox in Matlab and I wanted some directions or steps on how I could do this process. In the center of this image in the center of the hole (on the cross hair), I have a piece of material which is almost hexagonal in shape with reddish color. I have multiple pictures similar to this where the material is oriented slightly differently.
Could someone please tell me how can I isolate this object from the rest of the image and then find its orientation? I tried to use image contrast and segmentation, but it wasnt super clean.I am new to image processing toolbox in Matlab and I wanted some directions or steps on how I could do this process. In the center of this image in the center of the hole (on the cross hair), I have a piece of material which is almost hexagonal in shape with reddish color. I have multiple pictures similar to this where the material is oriented slightly differently.
Could someone please tell me how can I isolate this object from the rest of the image and then find its orientation? I tried to use image contrast and segmentation, but it wasnt super clean. I am new to image processing toolbox in Matlab and I wanted some directions or steps on how I could do this process. In the center of this image in the center of the hole (on the cross hair), I have a piece of material which is almost hexagonal in shape with reddish color. I have multiple pictures similar to this where the material is oriented slightly differently.
Could someone please tell me how can I isolate this object from the rest of the image and then find its orientation? I tried to use image contrast and segmentation, but it wasnt super clean. image processing MATLAB Answers — New Questions

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Given an Nx1 colum vector of strings containing lines of mfunction code, it is possible to use the undocumented function mtree() to parse it into its constituent functions. For example, given,
load Inputs
str1,
the function below will find the starting and ending lines of each of the three function blocks.
[firstLine,lastLine] = functionBlocks(str1)
This works for nested functions as well:
str2,
[firstLine,lastLine] = functionBlocks(str2)
However, I would really like to have the function be able to group the output separately into top-level function blocks and nested function blocks. I know it is possible to do this through a post-analysis of the outputs firstLine and lastLine, but I wonder if it is possible to get information about whether a function block is top-level or nested directly from mtree, i.e., by modifying,
fnSet = T.mtfind(‘Kind’,’FUNCTION’);
Unfortunately, because mtree() is undocumented, it is difficult to fathom its full capabilities. Does anyone know if/how this can be done?
function [firstLine,lastLine] = functionBlocks(str)

T = mtree(strjoin(str,newline));

fnSet = T.mtfind(‘Kind’,’FUNCTION’);
K=fnSet.count;
kset=fnSet.indices;

for k = K:-1:1

fn = fnSet.select(kset(k));

firstLine(k) = fn.lineno;

lastLine(k) = fn.lastone;

end

endGiven an Nx1 colum vector of strings containing lines of mfunction code, it is possible to use the undocumented function mtree() to parse it into its constituent functions. For example, given,
load Inputs
str1,
the function below will find the starting and ending lines of each of the three function blocks.
[firstLine,lastLine] = functionBlocks(str1)
This works for nested functions as well:
str2,
[firstLine,lastLine] = functionBlocks(str2)
However, I would really like to have the function be able to group the output separately into top-level function blocks and nested function blocks. I know it is possible to do this through a post-analysis of the outputs firstLine and lastLine, but I wonder if it is possible to get information about whether a function block is top-level or nested directly from mtree, i.e., by modifying,
fnSet = T.mtfind(‘Kind’,’FUNCTION’);
Unfortunately, because mtree() is undocumented, it is difficult to fathom its full capabilities. Does anyone know if/how this can be done?
function [firstLine,lastLine] = functionBlocks(str)

T = mtree(strjoin(str,newline));

fnSet = T.mtfind(‘Kind’,’FUNCTION’);
K=fnSet.count;
kset=fnSet.indices;

for k = K:-1:1

fn = fnSet.select(kset(k));

firstLine(k) = fn.lineno;

lastLine(k) = fn.lastone;

end

end Given an Nx1 colum vector of strings containing lines of mfunction code, it is possible to use the undocumented function mtree() to parse it into its constituent functions. For example, given,
load Inputs
str1,
the function below will find the starting and ending lines of each of the three function blocks.
[firstLine,lastLine] = functionBlocks(str1)
This works for nested functions as well:
str2,
[firstLine,lastLine] = functionBlocks(str2)
However, I would really like to have the function be able to group the output separately into top-level function blocks and nested function blocks. I know it is possible to do this through a post-analysis of the outputs firstLine and lastLine, but I wonder if it is possible to get information about whether a function block is top-level or nested directly from mtree, i.e., by modifying,
fnSet = T.mtfind(‘Kind’,’FUNCTION’);
Unfortunately, because mtree() is undocumented, it is difficult to fathom its full capabilities. Does anyone know if/how this can be done?
function [firstLine,lastLine] = functionBlocks(str)

T = mtree(strjoin(str,newline));

fnSet = T.mtfind(‘Kind’,’FUNCTION’);
K=fnSet.count;
kset=fnSet.indices;

for k = K:-1:1

fn = fnSet.select(kset(k));

firstLine(k) = fn.lineno;

lastLine(k) = fn.lastone;

end

end mtree, undocumented, parsing, functions MATLAB Answers — New Questions

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I am trying to generate a chirp signal with both up chirp and down chirp for one of my project, upchirp – which has start frequency of 57 GHz and Bandwidth of 150MHz then after 2microseconds and again have to generate down chirp with the same bandwidth and frequencyI am trying to generate a chirp signal with both up chirp and down chirp for one of my project, upchirp – which has start frequency of 57 GHz and Bandwidth of 150MHz then after 2microseconds and again have to generate down chirp with the same bandwidth and frequency I am trying to generate a chirp signal with both up chirp and down chirp for one of my project, upchirp – which has start frequency of 57 GHz and Bandwidth of 150MHz then after 2microseconds and again have to generate down chirp with the same bandwidth and frequency fmcw, radar, fft MATLAB Answers — New Questions

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I am using Simulink Real-Time with a Speedgoat target as my main device for my EtherCAT network. I have used Beckhoff’s TwinCAT3 to configure my ENI file that I plan to use.
I may also be having an issue with my subdevices not responding to commands or my EtherCAT network not getting to OP state, and I suspect my ENI configuration file may have issues.
How can I test this configuration?I am using Simulink Real-Time with a Speedgoat target as my main device for my EtherCAT network. I have used Beckhoff’s TwinCAT3 to configure my ENI file that I plan to use.
I may also be having an issue with my subdevices not responding to commands or my EtherCAT network not getting to OP state, and I suspect my ENI configuration file may have issues.
How can I test this configuration? I am using Simulink Real-Time with a Speedgoat target as my main device for my EtherCAT network. I have used Beckhoff’s TwinCAT3 to configure my ENI file that I plan to use.
I may also be having an issue with my subdevices not responding to commands or my EtherCAT network not getting to OP state, and I suspect my ENI configuration file may have issues.
How can I test this configuration? ethercat, validation, slrt MATLAB Answers — New Questions

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Hi.
I’m using the General flexible Beam model given in Simscape Multibody. In which you can define the "Damping constant (beta)" in s.
My problem is that I don’t know a damping coeffizient with seconds as the unit. I want to implement results from real life experiments out of which I calculated the logarithmic decrement in s^-1.
So my main question is, what kind of damping coefficient is used in the simscape model as I want to implement my test results?

Thanks and best regardsHi.
I’m using the General flexible Beam model given in Simscape Multibody. In which you can define the "Damping constant (beta)" in s.
My problem is that I don’t know a damping coeffizient with seconds as the unit. I want to implement results from real life experiments out of which I calculated the logarithmic decrement in s^-1.
So my main question is, what kind of damping coefficient is used in the simscape model as I want to implement my test results?

Thanks and best regards Hi.
I’m using the General flexible Beam model given in Simscape Multibody. In which you can define the "Damping constant (beta)" in s.
My problem is that I don’t know a damping coeffizient with seconds as the unit. I want to implement results from real life experiments out of which I calculated the logarithmic decrement in s^-1.
So my main question is, what kind of damping coefficient is used in the simscape model as I want to implement my test results?

Thanks and best regards simscape multibody, damping MATLAB Answers — New Questions

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I’m trying to create a minimal model in Simscape to replicate the Venturi effect in a Simscape Gas model: Gas is flowing from point A to point B, and the cross-sectional area of the duct at point A is smaller than B; as a result, the static pressure at A must be lower than B (assuming negligible energy loss from A to B).
I tried two different setups to replicate this. First, I used a "Local Restriction (G)" block (with a fixed restriction area), which has this orifice structure built in. The flow is provided by a Flow Rate Source block, and I added a Flow Resistance block downstream to allow the pressure at the port B of the Local Restriction to vary. Here is a screenshot of the model:

I expect that at least for some combination of restriction area and flow rate, the pressure at the restriction, p_R, must be lower than port B. I tried running the simulation with different values of flow rate and restriction area, but p_R was always higher than pressure at B.
Next, I used two consecutive Pipe (G) elements: the first one with a smaller surface area and hydraulic diameter, and the second with larger values for both. The rest of the setup is similar:

Again, I expect the internal pressure of the Small Pipe to be lower than the internal pressure of the Big Pipe, but this was never the case. I ran the simulation for different values of pipe surface area and hydraulic diameter for the two pipes, and kept the pipe length, internal surface roughness, and the laminar friction constants low to reduce the pressure loss due to friction. I also tried reducing the dynamic viscosity in the Gas Properties block, and disabling/enabling gas compressibility in the pipes.

In both models, I kept the rest of the settings and parameters as default (e.g., perfect gas with properties of dry air, daessc solver, etc.). The models are attached.

Am I doing something wrong, or are there any limitations and theoretical assumptions in Simscape Gas that do not allow replicating this effect?

Thanks in advance!I’m trying to create a minimal model in Simscape to replicate the Venturi effect in a Simscape Gas model: Gas is flowing from point A to point B, and the cross-sectional area of the duct at point A is smaller than B; as a result, the static pressure at A must be lower than B (assuming negligible energy loss from A to B).
I tried two different setups to replicate this. First, I used a "Local Restriction (G)" block (with a fixed restriction area), which has this orifice structure built in. The flow is provided by a Flow Rate Source block, and I added a Flow Resistance block downstream to allow the pressure at the port B of the Local Restriction to vary. Here is a screenshot of the model:

I expect that at least for some combination of restriction area and flow rate, the pressure at the restriction, p_R, must be lower than port B. I tried running the simulation with different values of flow rate and restriction area, but p_R was always higher than pressure at B.
Next, I used two consecutive Pipe (G) elements: the first one with a smaller surface area and hydraulic diameter, and the second with larger values for both. The rest of the setup is similar:

Again, I expect the internal pressure of the Small Pipe to be lower than the internal pressure of the Big Pipe, but this was never the case. I ran the simulation for different values of pipe surface area and hydraulic diameter for the two pipes, and kept the pipe length, internal surface roughness, and the laminar friction constants low to reduce the pressure loss due to friction. I also tried reducing the dynamic viscosity in the Gas Properties block, and disabling/enabling gas compressibility in the pipes.

In both models, I kept the rest of the settings and parameters as default (e.g., perfect gas with properties of dry air, daessc solver, etc.). The models are attached.

Am I doing something wrong, or are there any limitations and theoretical assumptions in Simscape Gas that do not allow replicating this effect?

Thanks in advance! I’m trying to create a minimal model in Simscape to replicate the Venturi effect in a Simscape Gas model: Gas is flowing from point A to point B, and the cross-sectional area of the duct at point A is smaller than B; as a result, the static pressure at A must be lower than B (assuming negligible energy loss from A to B).
I tried two different setups to replicate this. First, I used a "Local Restriction (G)" block (with a fixed restriction area), which has this orifice structure built in. The flow is provided by a Flow Rate Source block, and I added a Flow Resistance block downstream to allow the pressure at the port B of the Local Restriction to vary. Here is a screenshot of the model:

I expect that at least for some combination of restriction area and flow rate, the pressure at the restriction, p_R, must be lower than port B. I tried running the simulation with different values of flow rate and restriction area, but p_R was always higher than pressure at B.
Next, I used two consecutive Pipe (G) elements: the first one with a smaller surface area and hydraulic diameter, and the second with larger values for both. The rest of the setup is similar:

Again, I expect the internal pressure of the Small Pipe to be lower than the internal pressure of the Big Pipe, but this was never the case. I ran the simulation for different values of pipe surface area and hydraulic diameter for the two pipes, and kept the pipe length, internal surface roughness, and the laminar friction constants low to reduce the pressure loss due to friction. I also tried reducing the dynamic viscosity in the Gas Properties block, and disabling/enabling gas compressibility in the pipes.

In both models, I kept the rest of the settings and parameters as default (e.g., perfect gas with properties of dry air, daessc solver, etc.). The models are attached.

Am I doing something wrong, or are there any limitations and theoretical assumptions in Simscape Gas that do not allow replicating this effect?

Thanks in advance! simscape, gas, fluid dynamics, simulation MATLAB Answers — New Questions

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Hello everyone,
I am creating an IMU simulation using the built-in imuSensor model in MATLAB. The block includes several parameters that define IMU noise characteristics, but I do not fully understand how these parameters relate to Allan variance–derived noise coefficients.
Here is the list of gyroscope parameters available in
——————————————————————————————
gyroparams with properties:

MeasurementRange: Inf rad/s
Resolution: 0 (rad/s)/LSB
ConstantBias: [0 0 0] rad/s
AxesMisalignment: [3⨯3 double] %

NoiseDensity: [0 0 0] (rad/s)/√Hz
BiasInstability: [0 0 0] rad/s
RandomWalk: [0 0 0] (rad/s)*√Hz
NoiseType: "double-sided"
BiasInstabilityCoefficients: [1⨯1 struct]

TemperatureBias: [0 0 0] (rad/s)/°C
TemperatureScaleFactor: [0 0 0] %/°C
AccelerationBias: [0 0 0] (rad/s)/(m/s²)
——————————————————————————————

I have estimated my sensor noise parameters from Allan variance analysis, specifically:
ARW (N)
Bias Instability (B)
Rate Random Walk (K)
My goal is to correctly map these Allan variance parameters N, B, and K to the corresponding imuSensor block parameters:
NoiseDensity
BiasInstability
RandomWalk
I would appreciate clarification on how these quantities correspond mathematically and physically, and how to correctly convert Allan variance results into the parameters expected by MATLAB’s IMU sensor model.Hello everyone,
I am creating an IMU simulation using the built-in imuSensor model in MATLAB. The block includes several parameters that define IMU noise characteristics, but I do not fully understand how these parameters relate to Allan variance–derived noise coefficients.
Here is the list of gyroscope parameters available in
——————————————————————————————
gyroparams with properties:

MeasurementRange: Inf rad/s
Resolution: 0 (rad/s)/LSB
ConstantBias: [0 0 0] rad/s
AxesMisalignment: [3⨯3 double] %

NoiseDensity: [0 0 0] (rad/s)/√Hz
BiasInstability: [0 0 0] rad/s
RandomWalk: [0 0 0] (rad/s)*√Hz
NoiseType: "double-sided"
BiasInstabilityCoefficients: [1⨯1 struct]

TemperatureBias: [0 0 0] (rad/s)/°C
TemperatureScaleFactor: [0 0 0] %/°C
AccelerationBias: [0 0 0] (rad/s)/(m/s²)
——————————————————————————————

I have estimated my sensor noise parameters from Allan variance analysis, specifically:
ARW (N)
Bias Instability (B)
Rate Random Walk (K)
My goal is to correctly map these Allan variance parameters N, B, and K to the corresponding imuSensor block parameters:
NoiseDensity
BiasInstability
RandomWalk
I would appreciate clarification on how these quantities correspond mathematically and physically, and how to correctly convert Allan variance results into the parameters expected by MATLAB’s IMU sensor model. Hello everyone,
I am creating an IMU simulation using the built-in imuSensor model in MATLAB. The block includes several parameters that define IMU noise characteristics, but I do not fully understand how these parameters relate to Allan variance–derived noise coefficients.
Here is the list of gyroscope parameters available in
——————————————————————————————
gyroparams with properties:

MeasurementRange: Inf rad/s
Resolution: 0 (rad/s)/LSB
ConstantBias: [0 0 0] rad/s
AxesMisalignment: [3⨯3 double] %

NoiseDensity: [0 0 0] (rad/s)/√Hz
BiasInstability: [0 0 0] rad/s
RandomWalk: [0 0 0] (rad/s)*√Hz
NoiseType: "double-sided"
BiasInstabilityCoefficients: [1⨯1 struct]

TemperatureBias: [0 0 0] (rad/s)/°C
TemperatureScaleFactor: [0 0 0] %/°C
AccelerationBias: [0 0 0] (rad/s)/(m/s²)
——————————————————————————————

I have estimated my sensor noise parameters from Allan variance analysis, specifically:
ARW (N)
Bias Instability (B)
Rate Random Walk (K)
My goal is to correctly map these Allan variance parameters N, B, and K to the corresponding imuSensor block parameters:
NoiseDensity
BiasInstability
RandomWalk
I would appreciate clarification on how these quantities correspond mathematically and physically, and how to correctly convert Allan variance results into the parameters expected by MATLAB’s IMU sensor model. allan variance imu sensör MATLAB Answers — New Questions

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Hi,
I used the 2FSK example Simulink model, changed the M‑ary value to 4, and tested it on the ADALM‑PLUTO transmitter with a sample rate of 32 MHz. However, in the spectrum, I am seeing continuous harmonics. What are the recommended values for samples per symbol (SPS), samples per frame (SFS), and frequency separation?Hi,
I used the 2FSK example Simulink model, changed the M‑ary value to 4, and tested it on the ADALM‑PLUTO transmitter with a sample rate of 32 MHz. However, in the spectrum, I am seeing continuous harmonics. What are the recommended values for samples per symbol (SPS), samples per frame (SFS), and frequency separation? Hi,
I used the 2FSK example Simulink model, changed the M‑ary value to 4, and tested it on the ADALM‑PLUTO transmitter with a sample rate of 32 MHz. However, in the spectrum, I am seeing continuous harmonics. What are the recommended values for samples per symbol (SPS), samples per frame (SFS), and frequency separation? fsk, adalm-pluto MATLAB Answers — New Questions

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not workingnot working not working not working MATLAB Answers — New Questions

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As the title, I am trying to use external mode to model the PMSM board (STM32H7) to tune, I used the display block or scope but it is not working.
The image is attached below, as you see, when the switch changed between 0 and 1, the display block was always 0 while the system was working normally.
I know in external mode, we could use the data inspecter or logic analyzer which is of the tool, but it is inconvenient.
Therefore, I really would like to know how to config the MATLAB/Simulink to use these block in external mode. (I tried some ways but not work)
I use the 2024b version.
Thank you in advance for any help you can provide.
Best regards,
Raven PhamAs the title, I am trying to use external mode to model the PMSM board (STM32H7) to tune, I used the display block or scope but it is not working.
The image is attached below, as you see, when the switch changed between 0 and 1, the display block was always 0 while the system was working normally.
I know in external mode, we could use the data inspecter or logic analyzer which is of the tool, but it is inconvenient.
Therefore, I really would like to know how to config the MATLAB/Simulink to use these block in external mode. (I tried some ways but not work)
I use the 2024b version.
Thank you in advance for any help you can provide.
Best regards,
Raven Pham As the title, I am trying to use external mode to model the PMSM board (STM32H7) to tune, I used the display block or scope but it is not working.
The image is attached below, as you see, when the switch changed between 0 and 1, the display block was always 0 while the system was working normally.
I know in external mode, we could use the data inspecter or logic analyzer which is of the tool, but it is inconvenient.
Therefore, I really would like to know how to config the MATLAB/Simulink to use these block in external mode. (I tried some ways but not work)
I use the 2024b version.
Thank you in advance for any help you can provide.
Best regards,
Raven Pham simulink, external mode, scope block MATLAB Answers — New Questions

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