Draft:Volumetric load scanning

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Volumetric load scanning is a method of determining the volume of bulk materials using three-dimensional scanning technologies. Depending on the system, measurements may also be used to characterize the surface profile or distribution of material within a vehicle, railcar, or conveyor stream. Systems commonly use laser ranging or lidar to generate a three-dimensional representation from which volume is calculated.

Principle of operation

Volumetric load-scanning systems use LiDAR (light detection and ranging). LiDAR determines distance by emitting laser pulses and measuring the time it takes for reflected light to return to the sensor. Repeated distance measurements are combined into a three-dimensional point cloud, in which individual points represent measured locations on the surfaces of the load, its container, and the surrounding environment.

To estimate volume, operators use software to distinguish the load from surrounding objects, align the point-cloud data within a coordinate system, remove noise or outlying measurements, and reconstruct or approximate the material boundaries. Software can then calculate the enclosed volume from the reconstructed geometry. A 2025 study of truckload measurement described a workflow involving point-cloud filtering, truck isolation, orientation adjustment, load segmentation, cross-sectional projections, and reconstruction of a closed three-dimensional load shape.

To reduce environmental interference, systems may use multi-echo analysis. Multi-echo technology evaluates multiple reflections returned from a single measuring laser beam. Intervening surfaces or airborne particles can produce additional echoes. In applications that must reject environmental interference, the last echo can identify the intended material surface. Since plants and industrial environments often have harsh conditions with dust, fog, rain, snow, and other airborne interference, evaluating multiple returns improves measurement reliability.

The SICK LMS5xx sensor family can see up to five echo signals for each measuring beam. Its echo filter can be configured to output the first echo, the last echo, or all five echoes. Additional fog and particle filters can screen out unwanted measurement data associated with close-range fog, raindrops, snowflakes, dust particles, and other ambient conditions.

Data acquisition and processing

Data may be acquired from a single sensor position or from multiple overlapping scans. Multiple viewpoints can be used when parts of a load or stockpile are obscured from one position. The resulting partial point clouds are combined through point-cloud registration, which aligns the scans within a common coordinate system by estimating the rotation and translation between overlapping measurements.

Raw point-cloud data may contain noise, outlying measurements, occluded areas, or reflections that do not represent the material being measured. Processing can therefore include filtering, registration, coordinate normalization, and segmentation. Normalization aligns the measured scene with a defined reference plane, while segmentation separates the bulk material from the ground, vehicle body, container, conveyor, or other surrounding structures.

Some processing methods convert irregularly spaced point-cloud measurements into a regular grid or elevation model. Once the material boundary and its reference or base surface have been identified, the measured surface can be reconstructed as a mesh. Volume may then be calculated by dividing the enclosed geometry into smaller volume elements, such as triangular prisms, and summing their volumes.

Applications

Truck and vehicle loads

Three-dimensional scanning can be used to estimate the volume of bulk material carried by trucks or other open-top vehicles. A scanning system records the surface geometry of the loaded vehicle and separates the material from the vehicle body and surrounding scene. Depending on the system design, the measured load profile may be compared with a stored reference model or an earlier scan of the empty vehicle to determine the volume occupied by the material.

A LiDAR-derived three-dimensional representation of bulk material carried in an open-top truck.

A 2025 study evaluated an automated volume-estimation method using point clouds collected from 48 timber truckloads. Measurements obtained using a professional mobile lidar platform showed no statistically significant difference from detailed manual reference measurements, while measurements obtained using a smartphone lidar system showed larger deviations from the reference values.

Conveyor systems

Zeng and colleagues developed and experimentally evaluated a non-contact system that used laser scanning to acquire the surface profile of bulk material moving on a conveyor belt. Their method extracted the material contour, calculated its cross-sectional area, and combined those measurements with belt speed to determine material flow.

A LiDAR-derived surface profile of bulk material moving on a conveyor belt.

Successive scan profiles can also show non-uniform material distribution, intermittent feeding, and changes in the amount of material carried by the belt. Experimental research has used real-time laser measurements of conveyor cross sections to model changes in bulk-material distribution and support conveyor monitoring and control.

Rail transport

Lidar systems may be positioned above railway tracks to record the surface profile of material carried in passing open-top railcars. Processing can include locating the railcar, correcting motion-related distortion, joining successive scan profiles, separating the material surface from the railcar structure, and calculating the volume contained within the vehicle.

A LiDAR-derived three-dimensional representation of bulk material carried in an open-top railcar.

A 2025 study used a rotating multi-line lidar system to estimate the volume of residual frozen coal in railway carriages. The researchers corrected contour tilt and motion distortion, filtered and simplified the resulting point cloud, and extracted cross-sectional contours for volume estimation.

Inventory control and material reconciliation

Volumetric load scanning does not directly measure a stationary stockpile. Instead, cumulative measurements of material moving through trucks, railcars, or conveyor systems can contribute to records of material entering, leaving, or moving within an operation. These records may be compared with production totals, shipment records, or periodic physical inventory measurements.

Continuous flow measurements can also help identify upstream process deviations before they appear as discrepancies during later inventory reconciliation. Research in aggregate-production systems has shown that measured material-flow data, mass-balance calculations, and data-reconciliation methods can be used to detect deviations, improve the reliability of process data, and identify problems that may not be detected by existing control systems.

Comparison with weighing

Volumetric load scanning and weighing determine different physical quantities. A volumetric scanner reconstructs the external geometry of a material load and calculates the volume that it occupies, whereas a scale is a weighing device. In the case of a belt-conveyor scale, NIST Handbook 44 specifies that the system combines belt travel with belt load to determine the weight of material that has passed over the scale.

Mass and volume are related through mass density. The National Institute of Standards and Technology defines mass density as mass divided by volume, expressed as $\rho =m/V$. Consequently, a mass estimate may be calculated from a measured volume using $m=\rho V$ when an appropriate density value is known.

For loose granular materials, the relevant value is generally bulk density, which includes the void spaces between particles. The reliability of a mass value derived from volumetric measurements therefore depends on whether the density value represents the material under the conditions in which it is being measured. Bulk density may not remain constant in operating environments, and changes in particle composition, packing, porosity, or moisture can affect the relationship between measured volume and mass. Research into conveyor measurement has consequently examined methods for determining bulk density dynamically rather than assuming a fixed conversion value.

The measurement outputs also contain different information. A weighing system provides a total weight value but does not, by that measurement alone, describe the shape or spatial distribution of the material. Volumetric scanning retains a three-dimensional representation or a sequence of cross-sectional profiles, which can be used to examine the load surface, fill level, and distribution of material. It does not independently determine mass unless density information or a separate weighing measurement is available.

The technologies may also be used together. Simultaneous measurements of mass flow and volume flow allow bulk density to be calculated and monitored over time. In a study of mixed solid-waste processing, Curtis and Sarc measured both quantities in real time and observed that the resulting bulk density fluctuated with changes in the material stream.

Neither method is universally interchangeable with the other. The appropriate measurement method depends on whether the required quantity is mass or volume, whether material density is sufficiently stable or can be measured, whether information about load geometry is needed, and which legal-metrology requirements apply to the transaction or process.

Accuracy and sources of error

Accuracy in volumetric load scanning is application-specific and depends on the sensor, installation geometry, scanning coverage, reference model, movement of the measured object, and the algorithms used to filter and reconstruct the point cloud. Reported accuracy values are therefore meaningful only when accompanied by the measurement range, test method, operating conditions, and reference standard used for comparison.

Incomplete scanning coverage and occlusion can cause portions of a load surface to be missing from the point cloud. The volume-processing algorithm must then either exclude the obscured region or estimate its geometry. In a 2025 truckload study, point clouds collected using a professional mobile lidar system had a mean absolute error of approximately 2.06 m³ (73 cu ft) and a root mean square error of approximately 2.46 m³ (87 cu ft) relative to manual reference measurements. Point clouds collected using a handheld smartphone lidar system produced larger errors and a tendency to overestimate volume. The researchers attributed part of the difference to lower scan resolution, incomplete coverage of the top of the load, and greater occlusion.

Sensor positioning and calibration also affect the measured coordinates. Installation tilt, differences between sensor and site coordinate systems, limited fields of view, and obstruction by vehicle walls or loading equipment can introduce positional errors or leave portions of the target unmeasured. Research on lidar-based grain-loading measurement has identified dust, duplicate points, outliers, occlusion, sensor angle, detection range, and incomplete perception as potential sources of error requiring calibration, filtering, and—in some installations—overlapping measurements from multiple sensors.

For measurements collected while a truck, railcar, conveyor belt, or scanner is moving, errors can also result from inaccurate speed data, timing differences, vibration, or motion distortion. Successive scan profiles must be positioned at the correct distance from one another to reconstruct the measured load. A study of rotating lidar applied to railway carriages therefore included correction for sensor tilt, movement during each scan, and displacement between successive point-cloud frames before calculating volume.

Weather and airborne particles can affect laser returns by scattering or blocking emitted light and by introducing unwanted points into the point cloud. Rain, fog, snow, and dust may reduce visibility of the intended surface or create additional returns. Multi-echo processing and point-cloud filtering can reduce some of these effects, but environmental protection, sensor configuration, and suitable installation remain relevant to measurement performance.

For commercial multiple dimension measuring devices in the United States, NIST Handbook 44 specifies verification using test objects of known and stable dimensions and reference standards traceable to NIST or an equivalent national laboratory. Tests include measurements at different object positions, zero-stability checks, and evaluation under applicable influence factors and field disturbances. The code expresses acceptance and maintenance tolerance as plus or minus one device division rather than as a single universal percentage. Devices that measure while the object and sensor move relative to one another must also be marked with the minimum and maximum speeds at which measurements remain within the applicable tolerances.

When volume measurements are converted into estimated mass, uncertainty in the selected bulk-density value is an additional source of error. Variations in material composition, moisture, particle size, packing, and void space can change the relationship between measured volume and actual mass.

Legal metrology

Classification as a multiple dimension measuring device

In United States legal metrology, devices that automatically make multiple measurements to determine volume may be evaluated under Section 5.58 of NIST Handbook 44 as multiple dimension measuring devices (MDMDs). The code applies to dimension and volume measuring devices used for calculating freight, storage, or postal charges and, where its provisions are applicable, to other devices that automatically determine volume for commercial or law-enforcement applications. The handbook states that the National Type Evaluation Program accepts for type evaluation only devices that comply with the applicable requirements of the code.

NTEP evaluation

The National Type Evaluation Program (NTEP) evaluates types or models of weighing and measuring devices intended for commercial use. Following a successful evaluation, the National Council on Weights and Measures may issue a Certificate of Conformance indicating that the specific device type described in the certificate was found capable of complying with the applicable requirements of NIST Handbook 44.

In January 2026, the National Council on Weights and Measures issued provisional Certificate of Conformance 26-001P for the Wingfield Scale Company WingScan-T 3D-M, classifying it as an in-motion multiple dimension measuring device for volume measurement. The evaluated configuration had a measurement range of 2.4 to 88.6 cubic yards, a minimum division value of 0.2 cubic yards, and a dynamic operating-speed range of 0.5 to 5 miles per hour.

A truck passing beneath an in-motion volumetric measuring device during National Type Evaluation Program testing.

The device was evaluated using multiple types of dump trucks at minimum, intermediate, and maximum speeds. Testing included bidirectional measurements, stop-and-go operation, temperatures ranging from −10 °C (14 °F) to 40 °C (104 °F), and variations in power-supply voltage. The certificate states that the evaluation results indicated compliance with the applicable requirements of the 2025 edition of NIST Handbook 44 and the relevant provisions of NCWM Publication 14.

The certificate was issued provisionally because the applicable NCWM Publication 14 checklist, procedures, and technical policy for this device type were still under development. The certificate states that the evaluation and test report will be reviewed after that work is completed to determine whether the provisional designation can be removed.

Industrial development and adoption

Research into non-contact measurement of moving bulk materials has developed alongside advances in laser ranging, lidar, automated point-cloud processing, and three-dimensional reconstruction. In 2015, Zeng and colleagues described and experimentally evaluated a system that combined laser-scanned cross-sectional profiles with belt-speed measurements to calculate the flow of material on a conveyor. Subsequent research has applied automated three-dimensional volume estimation to material transported by trucks and railcars.

Commercial systems have been developed for conveyor belts, open-top trucks, and railcars. In 2023, International Mining reported that Wingfield Scale & Measure partnered with the German industrial-laser company LASE Industrielle Lasertechnik to develop a lidar-based volumetric load-scanning product line for those three forms of bulk-material transport.

In 2024, the specialist publication LiDAR News described the same product line as applying lidar-based volume measurement to material moving on conveyors, in open-top vehicles, and in railcars. The publication distinguished these load and flow measurements from periodic lidar surveys used to determine stationary stockpile inventory.

Adoption has also extended into United States legal metrology. In January 2026, the National Type Evaluation Program issued provisional Certificate of Conformance 26-001P for the Wingfield Scale Company WingScan-T 3D-M, an in-motion multiple dimension measuring device used to determine the volume of specified bulk commodities transported in dump trucks. The certificate states that the evaluated device configuration complied with the applicable technical requirements of the 2025 edition of NIST Handbook 44 and the applicable provisions of NCWM Publication 14.

In 2026, the National Council on Weights and Measures advanced proposal MDM-25.1 as a Voting item for its 111th Annual Meeting. The proposal would rename Section 5.58 of NIST Handbook 44 as “Multiple Dimension and Volumetric Measuring Devices” and distinguish volumetric measuring devices that determine the volume of a bulk commodity directly from traditional multiple dimension measuring devices that measure three dimensions to calculate volume. The proposed provisions would apply to bulk commodities such as sand, gravel, rock, and dirt measured either statically or in motion while transported in a truck or another conveyance. The proposal would also add or amend device specifications, test procedures, tolerances, and user requirements. Following comments at the 2026 Interim Meeting, the Specifications and Tolerances Committee stated that the proposal was fully developed and assigned it Voting status.

See also

• 3D scanning
• Lidar
• Point cloud
• Truck scale
• Belt weigher
• Photogrammetry