Difficulty assessment of shoveling stacked materials based on the fusion of neural network and radar chart information

J Li, C Chen, Y Li, H Wu, X Li - Automation in Construction, 2021 - Elsevier
This study aims to solve the problem of material detection and shovel difficulty judgment of
earth moving machinery and characterize the material shovel difficulty by using radar chart …

Online prediction of loader payload based on a multi-stage progressive model

J Feng, W Chen, T Wang, P Tan, C Li - Automation in Construction, 2022 - Elsevier
In earthmoving equipment, overloading and underloading transport vehicles reduce the
production efficiency. This paper presents a novel online loader payload prediction method …

Study on noncontact aviation bearing faults and speed monitoring

J Ma, S Zhuo, C Li, L Zhan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Aircraft bearings are the supporting part of aeroengines, so their stable operation
guarantees engine safety. At present, multisensor information fusion is very common in the …

LiDAR-based benchmark approach development and validation for unloading-on-the-go systems incorporating stereo camera-based perception

C Jiang, Z Liu, JT Evans, GM Shaver… - Biosystems …, 2023 - Elsevier
Highlights•In-situ LiDAR grain surface height mapping system developed.•Developed a dust
filtering algorithm to reduce LiDAR sensor noise.•Grain level stereo camera-based …

A bucket fill factor estimation method in construction environments by fusing deep learning and machine vision

W Guan, S Wang, Z Chen, G Wang, Z Liu, J Guo… - Journal of Cleaner …, 2023 - Elsevier
The need for high productivity in the construction field is becoming increasingly urgent, and
the efficiency of loading and unloading materials by construction vehicles is one of the main …

[HTML][HTML] Prediction of Bucket Fill Factor of Loader Based on Three-Dimensional Information of Material Surface

S Wang, S Yu, L Hou, B Wu, Y Wu - Electronics, 2022 - mdpi.com
The bucket fill factor is a core evaluation indicator for the optimization of the loader's
autonomous shoveling operation. Accurately predicting the bucket fill factor of the loader …

Computer vision-based excavator bucket fill estimation using depth map and faster R-CNN

B Helian, X Huang, M Yang, Y Bian, M Geimer - Automation in Construction, 2024 - Elsevier
Excavators are crucial in the construction industry, and developing autonomous excavator
systems is vital for enhancing productivity and reducing the reliance on manual labor …

A deep learning approach for construction vehicles fill factor estimation and bucket detection in extreme environments

W Guan, Z Chen, S Wang, G Wang… - Computer‐Aided Civil …, 2023 - Wiley Online Library
The development of autonomous detection technology is imperative in the field of
construction. The bucket fill factor is one of the main indicators for evaluating the productivity …

A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations

W Saif, A Alshibani - Construction Innovation, 2024 - emerald.com
Purpose This paper aims to present a highly accessible and affordable tracking model for
earthmoving operations in an attempt to overcome some of the limitations of current tracking …

Irregular object measurement method based on improved adaptive slicing method

H Chen, H Wu, N Yang, H Huang, W Liang - Multimedia Tools and …, 2024 - Springer
Surface shape feature is a very important index for monitoring objects. However, in the
existing slicing methods, the volume measurement accuracy of point cloud is easy to be low …