Due to its large size, the maintenance services are divided into strategic areas to serve the 16 existing lines optimally and exclusively. A breakdown in a train can jeopardize the proper functioning and punctuality of a line. That is why the maintenance service needs to have technological test tools to anticipate problems through predictive maintenance.
Based on periodic, systematically conducted braking performance tests, Metro de Madrid can reliably and safely roll out condition-based maintenance.
A series of measurements on three different braking systems (pneumatic brake, electrical brake, and emergency brake) lets Metro de Madrid better plan their maintenance cycles and deploy their predictive maintenance concept.
To perform brake testing on a total of 276 different metro cars, Metro de Madrid required a precise, robust, and portable system that it could install on the different trainsets. The portable and rugged Q.brixx X system proofed to be the ideal system for this application. A Q.brixx XL A108-4M1 measurement module acquires an acceleration signal from a Dytran series 7577 high precision MEMS sensor. The signal is sampled at a rate of 100 Hz, and unwanted noise is then filtered out with a fourth-order lowpass Butterworth filter. For improved robustness, the Q.brixx X system is installed inside a custom-made Pelicase.
Before the braking test, the metro car is placed on a horizontal track, and the accelerometer offset is eliminated. The metro then performs an acceleration and deceleration cycle. The braking and rest endpoints are selected for each cycle. The average steady-state acceleration and deceleration values are then calculated. Next, the average acceleration value during the rest phase after the braking is calculated. This value represents the mean value. Finally, the average deceleration is calculated as the absolute value of the difference between braking deceleration and rest acceleration.
For user convenience and to ensure test repeatability, instrutechSOLUTIONS developed a custom software application. The application was written in Python, benefiting from the open and flexible interfaces known as GI.connectivity, which came free of charge with the DAQ system. The Python application allows setting the accelerator offset, displaying the measured acceleration/deceleration signal, and providing a pass/fail indication for the average deceleration measured during brake testing.
This test & measurement application showcases the versatility of Gantner’s Q.series X data acquisition system. Combining of a flexible and modular hardware platform, in combination with reliable data exchange and interoperability through various read/write interfaces, makes Gantner Instruments one of the most sought-after companies for data acquisition systems.
Modules used:
- 1x Q.brixx X station B
- 1x Q.brixx XL A108-4M1
- 1x GI.bench Data Acquisition Software
More articles
Q.series interface with the Moog Aerospace Test Controller
The amount of data generated in an aircraft structural test program continues to grow. The density of load introduction points (actuators) and sensors (strain gauges, thermocouples, LVDTs) on a test article is increasing progressively and model validation requires higher data sample rates to capture more detail. The risks and costs involved in aircraft validation and certification are significant, and the requirement for quick entry-into-service is high. To minimize the impact of retrofitting in-service aircrafts, the ability to generate test results quickly is crucial to the success of a test program.
Read more...Experience a New Level of Possibilities With Our New Website!
We are thrilled to announce the launch of the new Gantner Instrumentswebsite and introduce you to a few of its features.Here’s a sneak peek of what you can expect to […]
Read more...Enhanced Functionality with GI.bench’s Newest Release: Revamped UI, Powerful Tools and More!
Introducing the latest update to our powerful and intuitive testing and measurement software - GI.bench. This update promises to elevate your testing capabilities with features designed to streamline your workflow and maximize productivity.
Read more...Gantner Instruments presents new Machine Learning and Fault detection routines at leading PV and Energy conference in Brussels, Belgium
Within the EU founded project “IPERMON” (“Innovative Performance Monitoring System for Improved Reliability and Optimized Levelized Cost of Electricity”) Gantner Instruments was developing different fault detection routines and failure classification methods for time series data sets.
Read more...