Description / Abstract:
Introduction
Note: Nothing in this standard supercedes applicable laws and regulations.
Note: In the event of conflict between the English and domestic language, the English language shall take precedence.
Purpose. The purpose of this standard is to verify the validity of data sent to the structural durability laboratory and ensure the data conform to the standards defined for the structural durability laboratories. This data is time history data from either physically measured Road Load Data Acquisitions (RLDA) or analytical “virtual RLDA” (vRLDA). Standards described in this document: Standard Channel Measurement Conventions (Channel Nomenclature, Coordinate System, Positive Direction, Static Offsets), Data File Format and Data Quality Checks.
Note: Throughout this procedure, “RLDA” means both RLDA and vRLDA unless noted otherwise.
Applicability. This procedure is applicable to all structural durability related time history data. It will not guarantee perfect data every time, but using these suggested data quality checks will eliminate the most significant errors.
Note: Nothing in this standard supercedes applicable laws and regulations.
Note: In the event of conflict between the English and domestic language, the English language shall take precedence.
Purpose. The purpose of this standard is to verify the validity of data sent to the structural durability laboratory and ensure the data conform to the standards defined for the structural durability laboratories. This data is time history data from either physically measured Road Load Data Acquisitions (RLDA) or analytical “virtual RLDA” (vRLDA). Standards described in this document: Standard Channel Measurement Conventions (Channel Nomenclature, Coordinate System, Positive Direction, Static Offsets), Data File Format and Data Quality Checks.
Note: Throughout this procedure, “RLDA” means both RLDA and vRLDA unless noted otherwise.
Applicability. This procedure is applicable to all structural durability related time history data. It will not guarantee perfect data every time, but using these suggested data quality checks will eliminate the most significant errors.
