Compatibility: While BLF is a proprietary format used primarily by Vector tools like CANalyzer and CANoe, MF4 (ASAM MDF4) is an industry-standard format compatible with a wide range of analysis software, including MATLAB, Tableau, and various Python libraries. Signal Decoding: Conversion often involves "translating" raw message-based data into human-readable signal-based data using database files (like .DBC or .LDF). Method 1: Using Professional Vector Tools If you have access to the Vector ecosystem, their built-in converters are the most reliable way to handle high-fidelity logging data. Vector CANape or vSignalyzer These tools include the Vector Logging Converter , which supports both BLF and MF4. Open the Converter: In CANape or vSignalyzer, go to Tools | Measurement File Converters . Add Databases: Open the Options dialog to attach the relevant DBC or LDF files. This is required to convert message-based logs into signal-based MF4 logs. Import & Convert: Add your .blf files and start the process. The resulting .mf4 files can then be loaded for symbolic analysis. Vector CANoe/CANalyzer You can also use the built-in logging capabilities to export or convert existing log files directly within the measurement configuration. Method 2: Open-Source Python Solutions (asammdf & candas) For automation and batch processing without expensive licenses, Python is the preferred route. The asammdf Library The asammdf library is a powerful tool for reading, writing, and editing MF4 files. How it works: You can use the asammdf GUI for manual tasks or its API for automated scripts. Conversion Workflow: Because asammdf primarily handles MDF, you often use it alongside a library like candas to first read the BLF data. Example Python Script: Database Selection for Vector Logging Converter
Converting BLF (Binary Logging Format) to MF4 (Measurement Data Format v4) is a standard procedure in automotive engineering to move from proprietary log formats to industry-standard data structures. Understanding the Formats BLF (Binary Logging Format): A proprietary binary format developed by Vector Informatik. It is primarily used by tools like CANalyzer and CANoe to store raw network traffic (CAN, LIN, Ethernet) efficiently. MF4 (MDF4): An ASAM-standardized measurement data format. It is designed for high-performance storage of time-series data and is widely supported by third-party analysis tools like MATLAB and ETAS INCA. Methods for Conversion 1. Professional Software Tools The most reliable way to convert BLF to MF4 is using established automotive software suites that handle the complex decoding requirements. Logging Formats - KnowledgeBase - Vector Support
The Complete Guide: Converting BLF to MF4 (Modern Workflow) 1. Introduction In the world of automotive engineering, data logging is the backbone of development, validation, and diagnostics. Two formats dominate the landscape:
BLF (Binary Logging Format): Vector Informatik’s proprietary, highly compressed format. It is optimized for minimal file size and high write speeds during long-term logging (e.g., driving tests, fleet monitoring). BLF files are indexed internally, allowing for fast random access. MF4 (Measurement Data Format 4): The ASAM standard (MDF – Measuring Data Format) version 4. It is an open, vendor-neutral format designed for post-processing, analysis, and simulation. MF4 supports multiple CAN, LIN, FlexRay, Ethernet, and even video data in a single, structured file.
Why convert BLF to MF4?
Interoperability: MF4 is accepted by almost all third-party tools (MATLAB, Python asammdf , NI DIAdem, ETAS INCA, etc.). Anchoring & Metadata: MF4 supports extensive metadata (VIN, test ID, driver info) and allows attaching external XML descriptions. Future-proofing: ASAM standards ensure long-term readability, whereas BLF is tied to Vector’s ecosystem. Data reduction: You can filter, resample, or scale signals during conversion.
2. Prerequisites Before starting, ensure you have:
Source BLF file(s) – ideally with a matching .dbc , .arxml , or .fibex database if you want symbolic signal names. Target storage – MF4 files can be larger than BLF due to less aggressive compression (though MF4 supports zlib deflate). Software (choose one from Section 3).
3. Available Conversion Tools (2026 Update) | Tool | Type | OS | Speed | Signal Names | Scripting | Cost | |------|------|-----|-------|--------------|-----------|------| | Vector CANape | GUI/COM | Win | Fast | Yes (DBC/ARXML) | VBScript | Commercial | | Vector CANalyzer/CANoe | GUI/COM | Win | Fast | Yes | CAPL/Python | Commercial | | asammdf (Python) | CLI/Python | All | Medium | Yes (with dbc) | Full Python | Free (Open Source) | | PyViSim (Python) | CLI/Python | All | Slow | Yes | Python | Free | | MDF4 Lib (C/Python) | Library | All | Very Fast | Limited | C/Python | Free (LGPL) | | NI Diadem | GUI/script | Win | Fast | Yes (via Vector add-on) | VBS/Python | Commercial | | CANetc MDF4 Converter | GUI | Win | Medium | Yes | – | Free/Paid | Recommendation for most users: asammdf (free, cross‑platform, powerful). For production/embedded: Vector CANape or custom C with MDF4 lib.
4. Method 1: Using asammdf (Python – Free & Cross‑Platform) asammdf is the de facto standard open-source MDF library. It reads BLF natively via the python-can backend. Step‑by‑step 4.1 Installation pip install asammdf[gui,plot,blf]
This installs:
Core MDF handling BLF reader (via can package) Optional GUI ( mdf4-gui )