Define event detection rules
Translate an engineering symptom into explicit conditions over selected measurement channels, including thresholds, duration requirements, and the context needed around each match.
Vehicle Data & Measurement
Find recurring events across vehicle measurements
Automated measurement analysis applies the same engineering checks across MF4/MDF recordings. I define event conditions, compare selected signals around each occurrence, and produce reviewable results that preserve the recording, time window, units, and analysis assumptions.
Discuss Automated Vehicle Measurement AnalysisProblems I can investigate
Find the behavior behind the symptom
- 01
Measurement events are hard to locate
Relevant vehicle behavior can be buried in long or numerous recordings. Automated searches can narrow measurements to the conditions and signals associated with an observed event.
- 02
Measurement files are too large for practical inspection
Measurement size or volume can make interactive inspection and repeated manual processing impractical. Batch-oriented analysis helps apply the same evaluation across recordings.
- 03
Signal correlation is unknown
The signals associated with an observed vehicle behavior may not be clear. Analysis can compare signal activity around an event and document relationships supported by the available measurements.
- 04
Vehicle behavior is intermittent
Irregular symptoms require evidence across recordings and logs. Repeatable processing can identify comparable occurrences and organize findings for anomaly investigation.
What I can help with
Focused engineering work in Vehicle Data & Measurement
Preserve time and signal meaning
Check channel availability, units, and time bases before comparing values. Document resampling or alignment choices and report recordings that do not support the rule.
Process a collection of recordings
Apply versioned rules to the supplied files and produce an event index with recording identifiers and time windows, including separate reporting for incomplete inputs.
Review detections against evidence
Plot signal windows around representative matches, compare flagged and unflagged cases, and adjust rule definitions with the engineering team before repeat use.
What to send
Start with the evidence you already have
MF4/MDF measurement
Provide the ASAM MDF measurement containing the timestamped signals and metadata to inspect.
DBC
Provide the CAN database when message and signal definitions are needed for interpretation.
Problem description
Describe observed symptoms, context, reproduction steps, and expected behavior so the analysis can target useful evidence.
How the analysis works
From recorded data to engineering findings
- 01
Define the analysis question
Review the problem description, available measurements, and expected behavior to establish the events and evidence to evaluate.
- 02
Inspect measurement structure
Parse the MF4/MDF data, review available signals and metadata, and use the DBC where CAN interpretation is required.
- 03
Implement the evaluation
Build focused Python processing for event searches, signal correlation, anomaly investigation, or batch processing across recordings.
- 04
Review findings
Visualize relevant signals, compare occurrences, and check the generated results against the supplied engineering context.
- 05
Package the workflow
Deliver a maintainable analysis workflow and repeatable outputs suitable for continued engineering use.
What you receive
Deliverables matched to the investigation
Python analysis script
A maintainable Python workflow for engineering-data analysis.
Automated report
A repeatably generated report containing analysis or test results.
Engineering analysis
A documented technical analysis with evidence and findings.
Measurement viewer
An application for navigating and plotting measurement signals.
Technologies & formats
Automotive data and analysis environments
- MF4
MDF 4 Measurement
The fourth-generation ASAM MDF format for synchronized measurement data.
- Python
Python
A general-purpose language widely used for automotive analysis, tooling, and automation.
- MDF
Measurement Data Format
The ASAM family of binary measurement-data formats.
- MDA
ETAS MDA
A measurement-data analysis and visualization application.
- 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
- How do you compare events across measurement files?
- First check channel meaning, units, timestamps, and recording coverage. Then define an event condition and a surrounding time window that can be applied consistently. Different sample rates or time bases need an explicit alignment method; temporal correlation alone does not establish causation.
- What measurement data can be analyzed?
- The service is centered on MF4/MDF measurements containing timestamped signals and metadata. A DBC can be used when CAN messages and signals need to be interpreted.
- Can this process many recordings?
- Yes. A Python workflow can apply the same event search, signal correlation, or anomaly investigation steps across multiple measurements for repeatable comparison.
- Will the analysis identify the root cause?
- The analysis documents evidence and findings from the supplied data. It can narrow relevant signals and occurrences, but it does not guarantee a root cause when the measurements are inconclusive.
- What do I need to provide to begin?
- Provide an MF4/MDF measurement, the relevant DBC when available, and a problem description covering symptoms, context, reproduction steps, and expected behavior.
Discuss the evidence
Discuss Automated Vehicle Measurement Analysis
Share a measurement, DBC, and problem description to scope a focused analysis workflow or investigation.