MF4 measurement parsing
Read MF4 and MDF measurement data into an analysis workflow, preserving relevant signal and metadata context for subsequent evaluation.
Vehicle Data & Measurement
MF4 automation for repeatable vehicle-data analysis
Run the same MF4 evaluation across recurring measurement batches with configurable event rules, per-file results, and repeatable reports. The handoff includes a maintainable workflow that records failures and makes incomplete processing visible.
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 across long or numerous MF4 recordings. Automated filtering and evaluation can reduce repetitive inspection and bring candidate intervals into focus.
- 02
Large measurement files slow analysis
Measurement size or volume can make interactive inspection impractical. A structured workflow can process recordings in repeatable steps and retain the evidence needed for engineering review.
- 03
Signal correlation is unknown
The signals associated with an observed vehicle behavior may not be obvious. MF4 data, DBC definitions, and the problem description can be examined together to identify useful relationships.
- 04
Vehicle behavior is intermittent
Irregular symptoms require evidence across recordings and logs. Batch processing and consistent evaluation can help compare occurrences without relying on manual inspection alone.
What I can help with
Focused engineering work in Vehicle Data & Measurement
Event search and batch processing
Apply versioned evaluation rules to each recording, record input identity and processing status, and keep failed files separate from successful results. Define rerun behavior so repeated jobs do not silently duplicate findings.
Signal correlation
Compare signals around observed behavior and investigate relationships using measurement data, DBC definitions, and focused analysis logic.
Measurement visualization
Create a measurement viewer or analysis output for navigating and plotting signals around selected events and intervals.
Engineering-data integration
Prepare decoded results for exchange through CSV or a REST API when the analysis workflow needs to connect with existing software.
What to send
Start with the evidence you already have
MF4/MDF measurement
Provide the ASAM MDF measurement containing the timestamped signals and metadata needed for analysis.
DBC
Provide the CAN database when message and signal definitions are required for decoding or correlation.
Problem description
Describe observed symptoms, context, reproduction steps, and expected behavior so the evaluation can target relevant evidence.
How the analysis works
From recorded data to engineering findings
- 01
Define the evaluation target
Review the problem description and identify the behavior, event conditions, signals, and comparison questions that the workflow should address.
- 02
Inspect the measurement structure
Examine the available MF4/MDF data and DBC definitions, including signal availability, naming, timing, and metadata relevant to the investigation.
- 03
Build the analysis workflow
Implement focused parsing, filtering, signal correlation, visualization, or batch-processing steps in Python according to the agreed evaluation logic.
- 04
Check findings against recordings
Compare automated detections with reviewed sample intervals, exercise missing-channel and unreadable-file cases, and repeat a batch to check consistent results. Record false positives and unprocessed inputs alongside successful evaluations.
- 05
Package the result
Document the engineering findings and provide the agreed script, measurement viewer, or automated report for repeatable use.
What you receive
Deliverables matched to the investigation
Engineering analysis
A documented technical analysis with evidence, evaluation steps, and findings from the supplied measurements.
Python analysis script
A maintainable Python workflow for parsing, evaluating, correlating, or batch-processing engineering data.
Measurement viewer
An application for navigating and plotting measurement signals around relevant events or intervals.
Automated report
A repeatably generated report containing analysis or test results from the defined measurement workflow.
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.
- CAN
Controller Area Network
A priority-based broadcast bus used for in-vehicle control communication.
- CAN-FD
CAN Flexible Data-rate
An extension of CAN with larger payloads and a faster data phase.
FAQ
Practical questions before an investigation
- What measurements are needed to start?
- The primary input is an MF4/MDF measurement. A DBC is useful when CAN message and signal definitions are needed, and a problem description helps focus the evaluation.
- Can the workflow process more than one recording?
- Yes. Batch processing can be structured for multiple measurements when the recordings share enough relevant signal and metadata context.
- Can you investigate an intermittent vehicle behavior?
- Yes. The analysis can compare evidence across recordings, locate candidate events, and examine signal correlation. Findings remain tied to the supplied data and problem description.
- How are failed recordings handled?
- The agreed workflow records per-file status and useful failure details. Missing channels or unreadable files appear as unresolved inputs, with an explicit rerun procedure rather than being counted as clean evaluations.
Discuss the evidence
Discuss a MF4 Project
Share an MF4 measurement, DBC, and short problem description to discuss a focused automation or analysis workflow.