Measurement data obtained from Weigh-in-Motion systems support protection of road pavements from the adverse phenomenon of vehicle overloading. For this protection to be effective, WIM systems must be accurate and obtain a certificate of metrological legalization. Unfortunately there is no legal standard for accuracy assessment of Weigh-in-Motion (WIM) systems. Due to the international range of road transport, it is necessary to standardize methods and criteria applied for assessing such systems’ accuracy. In our paper we present two methods of determining accuracy of WIM systems. Both are based on the population of weighing errors determined experimentally during system testing. The first method is called a reliability characteristic and was developed by the authors. The second method is based on determining boundaries of the tolerance interval for weighing errors. Properties of both methods were assessed on the basis of simulation studies as well as experimental results obtained from a 16-sensor WIM system.
The paper presents the problem of assessing the accuracy of reconstructing free-form surfaces in the CMM/CAD/CAM/CNC systems. The system structure comprises a coordinate measuring machine (CMM) PMM 12106 equipped with a contact scanning probe, a 3-axis Arrow 500 Vertical Machining Center, QUINDOS software and Catia software. For the purpose of surface digitalization, a radius correction algorithm was developed. The surface reconstructing errors for the presented system were assessed and analysed with respect to offset points. The accuracy assessment exhibit error values in the reconstruction of a free-form surface in a range of ± 0.02 mm, which, as it is shown by the analysis, result from a systematic error.
Understanding the factors that influence the quality of unmanned aerial vehicle (UAV)-based products is
a scientifically ongoing and relevant topic. Our research focused on the impact of the interior orientation
parameters (IOPs) on the positional accuracy of points in a calibration field, identified and measured in an
orthophoto and a point cloud. We established a calibration field consisting of 20 materialized points and
10 detailed points measured with high accuracy. Surveying missions with a fixed-wing UAV were carried
out in three series. Several image blocks that differed in flight direction (along, across), flight altitude
(70 m, 120 m), and IOPs (known or unknown values in the image-block adjustment) were composed. The
analysis of the various scenarios indicated that fixed IOPs, computed from a good geometric composition,
can especially improve vertical accuracy in comparison with self-calibration; an image block composed
from two perpendicular flight directions can yield better results than an image block composed from a single
flight direction.