MF4/MDF measurement parsing
Read MF4/MDF measurements, inspect timestamped signals and metadata, and prepare recordings for focused analysis or conversion.
Vehicle Data & Measurement
MF4 Measurement Analysis
Turn MF4/MDF recordings into focused engineering evidence. I analyze measurement data, correlate signals, investigate intermittent behavior, and build repeatable workflows for large or numerous files.
Discuss a MF4 ProjectProblems I can investigate
Find the behavior behind the symptom
- 01
Measurement events are hard to locate
Relevant events can be difficult to find within long or numerous MF4 recordings. Analysis can focus the search on symptoms, timing, and signal changes.
- 02
Large measurement files slow inspection
Measurement size or volume can make interactive inspection and manual comparison impractical. Automated parsing and batch processing can reduce repetitive review.
- 03
Signal correlation is unknown
The signals associated with an observed vehicle behavior may not be known. Measurement analysis can compare available signals around the relevant event and identify useful relationships.
- 04
Vehicle behavior is intermittent
An irregular symptom requires evidence across recordings and logs. Structured investigation can compare occurrences, surrounding conditions, and available measurement data without assuming a single cause.
What I can help with
Focused engineering work in Vehicle Data & Measurement
Signal correlation and visualization
Compare signal behavior around an event, visualize relevant measurement sections, and organize findings for engineering review.
DBC-assisted CAN analysis
Use a DBC to interpret CAN messages and signals in measurement data, supporting investigation of relationships between recorded values.
Repeatable measurement automation
Build Python workflows for batch processing, anomaly investigation, and automated report generation across measurement recordings.
What to send
Start with the evidence you already have
MF4/MDF measurement
An ASAM MDF measurement containing timestamped signals and metadata.
DBC
A CAN database defining messages and signals.
Problem description
Observed symptoms, context, reproduction steps, and expected behavior.
How the analysis works
From recorded data to engineering findings
- 01
Define the analysis question
Review the problem description, expected behavior, available recordings, and the evidence needed to assess the issue.
- 02
Inspect and prepare measurements
Parse the MF4/MDF data, review signal and metadata availability, and use the DBC where CAN signal interpretation is required.
- 03
Locate events and correlate signals
Search recordings for relevant conditions, compare signal behavior around candidate events, and investigate similarities or differences across files.
- 04
Automate repeatable checks
Convert proven analysis steps into a Python workflow for batch processing, consistent evaluation, or repeatable report generation.
- 05
Document findings
Summarize the analyzed evidence, signal relationships, limitations, and useful next steps in an engineering analysis.
What you receive
Deliverables matched to the investigation
Engineering analysis
A documented technical analysis with evidence and findings.
Python analysis script
A maintainable Python workflow for engineering-data analysis.
Measurement viewer
An application for navigating and plotting measurement signals.
Automated report
A repeatably generated report containing analysis or test results.
Technologies & formats
Automotive data and analysis environments
- MF4
MDF 4 Measurement
The fourth-generation ASAM MDF format for synchronized measurement data.
- MDF
Measurement Data Format
The ASAM family of binary measurement-data formats.
- MDA
ETAS MDA
A measurement-data analysis and visualization application.
- Python
Python
A general-purpose language widely used for automotive analysis, tooling, and automation.
- DBC
CAN Database
A text format describing CAN messages, signals, nodes, scaling, and metadata.
- python-can
python-can
A Python library providing a common API for CAN interfaces and messages.
- cantools
cantools
A Python package for parsing CAN databases and encoding or decoding messages.
- CSV
Comma-Separated Values
A tabular text format often used for exchanging decoded engineering data.
- REST API
REST API
An HTTP resource-oriented interface used for software and cloud integration.
FAQ
Practical questions before an investigation
- What measurement data can be analyzed?
- The service is focused on MF4/MDF measurements containing timestamped signals and metadata. A DBC can be used when CAN messages and signals need interpretation.
- Can you investigate an intermittent vehicle behavior?
- Yes. The analysis can compare multiple recordings and logs, search for recurring conditions, and document evidence around observed occurrences. It does not assume a root cause before the data supports one.
- Can a manual analysis be automated?
- Yes. Repeatable steps can be implemented as a Python analysis script for batch processing, signal evaluation, or automated report generation.
- What should be provided to start?
- Provide the MF4/MDF measurement, the relevant DBC when available, and a problem description covering symptoms, context, reproduction steps, and expected behavior.
Discuss the evidence
Discuss an MF4 Measurement Analysis Project
Share the measurement data, DBC, and problem description to scope a focused analysis or repeatable MF4 workflow.