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Predictive Maintenance in Hydraulic Pump

version (11.7 MB) by Steve Miller
Predictive maintenance algorithm developed using digital twin of hydraulic pump modeled in Simscape


Updated 17 Apr 2021

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This example models a triplex pump with a predictive maintenance algorithm that can detect which parts of the pump are failing simply by monitoring the pump output pressure.

The Simscape model of the pump can be configured to model degraded behavior due to seal leakage, blocked inlets, bearing wear, and broken motor windings. MATLAB code shows how to accelerate testing by reusing results from previous simulations. The model can be used to generate training data for the machine learning algorithm and can be used to test the deployed algorithm. MATLAB Live Scripts show you how to develop the algorithm.

Mechanical, hydraulic, and electrical parameters are all defined in MATLAB which lets you easily resize the pump. The pump housing is imported from CAD.

Please read the file to get started.

Use the "Download from GitHub" button above to get files compatible with the latest release of MATLAB.
Use the links below to get files compatible with earlier releases of MATLAB.

For R2020b:
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For R2018b:
For R2018a:
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Try this free, hands-on tutorial to learn how to use Simscape:

See how to model a fluid actuation system in Simscape (7 min):

Read the e-book “Predictive Maintenance with MATLAB”

Find other Simscape examples by searching posts for the keyword "physical modeling"

Learn more about MathWorks Simscape Products:

Cite As

Steve Miller (2021). Predictive Maintenance in Hydraulic Pump (, GitHub. Retrieved .

Comments and Ratings (6)

Aman Ullah Khan

Steve Miller

@Abhijit - contact me directly via my author page and send me your email and which release you want and I can email it to you. I have this example from R2017b and higher.

Abhijit Das

Wondering how I can open this file when I don't have 2019 version for export. Do you by any chance has the older versions as well?

James Ang

Fisher Yu

great job

MATLAB Release Compatibility
Created with R2021a
Compatible with R2017b to R2021a
Platform Compatibility
Windows macOS Linux

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