Environmental and Material-Related Factors

The physical environment and the nature of the material being measured are primary sources of potential error. An accurate system must be engineered to account for these variables.

1. Surface Irregularity and Angle of Repose

No stockpile has a perfectly uniform surface. The natural slope at which a granular material settles is known as the angle of repose. This angle can vary based on the material's properties (e.g., grain size, moisture content). If the LiDAR system's scanning resolution is too low, it may fail to capture the subtle peaks and valleys of the pile. This can lead to an over or underestimation of volume as the software interpolates data between sparse points, effectively "smoothing over" the true surface shape.

2. Material Properties and Dust

The reflectivity of the material being measured directly impacts the LiDAR's performance. Dark materials like coal absorb more light and return a weaker signal than bright materials like sand. Furthermore, the process of loading and unloading bulk materials often generates significant airborne dust. This dust can scatter the LiDAR's laser beam, creating false data points or attenuating the signal, which prevents it from reaching the material surface and returning accurately.

System and Installation-Related Factors

The configuration and properties of the LiDAR system itself are equally critical for achieving high-precision measurements.

1. Inadequate Point Cloud Density

Volume calculation is fundamentally a geometric exercise based on the 3D point cloud. If the point cloud is not dense enough, the resulting 3D model of the stockpile will be a rough approximation rather than a precise digital twin. The density is a function of the scanner's angular resolution and scan speed. A system that scans too quickly or with too large a step interval between scan lines will not capture sufficient detail, leading to significant volumetric errors.

2. Incorrect System Configuration

A LiDAR volume measurement system must be precisely configured for the specific environment. This includes accurately defining the "zero" reference point, such as the floor of the silo or the base of the stockpile area. Any error in defining the boundaries of the container or an incorrect cone angle setting in the software will introduce a systemic error into every calculation.

3. Environmental Buildup on the Sensor

In industrial environments, dust, dirt, and moisture can accumulate on the LiDAR's optical window. This buildup can obstruct the laser beam, leading to weakened signals and inaccurate distance readings. Without a mechanism to keep the sensor clean, performance will degrade over time, compromising the reliability of the measurements.

Benewake is a global technology leader with a business presence in over 90 countries, holding hundreds of patents in the LiDAR field. We provide innovative, high-performance LiDAR solutions that empower enterprises worldwide to build more intelligent, efficient, and secure automated systems across industries like rail transit, civil aviation, shipping, and industrial automation.

Our LiDAR tank inspection systems are engineered to address these challenges head-on, with features like high-density arc scanning, configurable parameters, and self-cleaning capabilities to ensure maximum accuracy in demanding industrial environments.

Contact our team to discover how Benewake's advanced LiDAR solutions can deliver the high-precision volume measurements your operation requires.