J1939 Python

J1939 WiFi Logger - Auto Data Analysis via 4G, S3 & Python

Case Studies / Anoynomous OEM

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Large OEM (anonymous)

About: This case study was provided anonymously by a transmissions manufacturer of gearbox and axle solutions for off-highway equipment.

What problem did you solve?

We quickly needed to commission a system that would capture data from test machines in the field to understand driving habits and help identify why a particular behaviour was occurring. We needed a standalone system that would collect both J1939 data and CAN data from an analogue-to-CAN converter (using 2 separate buses), and reliably allow remote transfer/collection of the acquired data.

Having a low power device with a small form factor was essential, to ensure the hardware did not reduce the space in the operators cabin. Furthermore, due to the cyclic and variable nature of off-highway machine usage, we needed a device with configurable acquisition triggers, allowing us to only log data of interest.

How did you solve it?

We discovered the CANedge2 facilitates the above requirements, and we quickly received our logger which we used with a mobile broadband dongle to allow remote upload of data to the AWS S3 server. Within a couple days we had the system up and running, helped by the clear and detailed setup documents available from CSS Electronics.

Far exceeding our initial requirements we were also able develop a script to automate the transfer and analysis of the uploaded data, then notifying us of any exceptions/alarms. The guys at CSS Electronics were extremely helpful in assisting with the code development.

J1939 telematics predictive maintenance

"Both the hardware and support from CSS Electronics have been outstanding!"

What benefit has this led to?

The CANedge2 allowed us to reliably measure CAN data as part of an un-manned system, while allowing the remote collection of data. This allows us to place the machines in their natural working environment, while giving us the capability to support and analyse the data remotely.

Furthermore, the data processing script removed the need for hours of repetitive analysis, and instead auto-collected data from the cloud, concatenated it into desired file sizes, DBC converted into engineering values, conducted additional computations between multiple variables and then looked for any exceptions in the data while notifying the engineer.

Why did you choose the CANedge?

The CANedge2 was a clear winner when looking for low cost, standalone CAN loggers with support for remote data transfer - the features exactly matched our requirements. Being such a small and low cost device, the next question was: Would the CANedge2 be reliable enough for truly un-manned data capture? It absolutely was, and the extensive configuration options also proved impressive.

   — Senior Development Engineer (anonymous)

Comments by CSS Electronics

With the CANedge2, you have 100% control over how you process your data. In particular, the Python API enables practically any use case - including in this case automated J1939 data analysis & alerting.

Further, with the API you can either perform your data processing within Python - or simply use the API as an intermediary between your raw data on S3 and e.g. an output database with decoded physical values.

This case study is also a good example of how simple CAN bus alert logics can be deployed to either speed up maintenance/reactions - or to set up basic predictive maintenance.

Predictive Maintenance J1939 Python

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