CAN Bus Logging
Capture, store, and replay CAN traffic for offline analysis and compliance
Whether you need to record hours of vehicle data during road tests or capture intermittent faults in a factory, reliable CAN bus logging is the foundation of every analysis workflow. Helix provides continuous, high-speed dual-channel logging with intelligent storage management — so you never miss a frame.
How It Works
Key Capabilities
What Helix brings to the table for can bus logging.
Partition management
Intelligent disk partitioning ensures long-running logs are stored efficiently with automatic rotation and retention policies.
Signal decoding
Apply database files like DBC to decode raw frames into named signals with physical units, scaling, and value descriptions.
Cloud upload via MQTT
Stream logged data to your infrastructure automatically via MQTT when Helix is connected to a network — for example via Ethernet or a USB LTE dongle in USB host mode.
CSV export
Export both raw CAN frames and decoded signal values as CSV for seamless integration with MATLAB, Python, or Excel workflows.
Events
Mark important moments in your logs with events — triggered manually, automatically on log start and stop, or by user-defined rules such as a temperature threshold being exceeded.
Common Challenges
Problems engineers face with can bus logging — and why they matter.
Data volume
High-traffic CAN buses can generate gigabytes of raw data per day, quickly filling available storage. Without intelligent management, devices require frequent manual intervention to clear old logs — or worse, silently stop recording when disk space runs out.
Signal context
Raw hex frames are nearly impossible to interpret without database definitions. Engineers are forced to manually cross-reference CAN IDs, start bits, and scaling factors just to understand what a single message means — slowing down every analysis task.
Remote collection
Retrieving logged data from vehicles or equipment in the field often means physically travelling to each device. For fleets or distributed installations, this creates a bottleneck where valuable data sits stranded until someone can collect it.
Export compatibility
Analysis toolchains like MATLAB, Python, and Excel each expect specific data formats. Proprietary log file formats force engineers to write custom conversion scripts, adding friction to every analysis workflow.
Finding what matters
On a high-throughput bus, the signal you care about is buried in thousands of frames per second. Manually scrubbing through hours of log data to find the exact moment a fault occurred is tedious and error-prone — critical events are easily missed.
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