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테스트 데이터 처리 및 내구성 분석

Estimating rigid body motion from accelerometer measurements


Acceleration data is often collected on vehicle cabs for heavy-duty trucks with accelerometers placed at various locations throughout the cab. The center of mass of the cab is of particular interest as is represents a convenient location for computational models. Additionally, the number of acceleration channels collected may exceed the required six degrees of freedom needed to fully define the equations of motion for the cab center of mass. This presentation details a method utilizing the Moore-Penrose pseudo inverse to find a best fit for the cab center of mass to an over constrained set of acceleration channels. This method may also be extended to find accelerations at other locations on the cab, so long as the rigid body assumption is not violated.


  • Difficult to measure the rigid body motion of vehicle components such as powertrain, cab, cooling module, etc.


  • Standard data reduction process using nCode GlyphWorks and the Python scripting glyph


  • Quantify rigid body motion of vehicle components
  • Identify fundamental information regarding the performance of suspension systems
  • Automate processing of road load and vehicle dynamics data

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Test data processing and durability analysis


nCode GlyphWorks is a data processing system that contains a powerful set of pre-defined tools for performing durability analysis and other insightful tasks such as digital signal processing. Designed to handle huge amounts of data, GlyphWorks provides a graphical, process-oriented environment that contains leading analysis capabilities for saving both time and money in environmental qualification and product validation.

Data storage and automated reporting


nCode Automation is a web-based environment for the automated storage, analysis and reporting of engineering data. It is built on robust technology including Java EE to provide a collaborative platform for sharing test data and associated information throughout an organization.

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