Real-time Load Determination  of Wheel Loader Components

Brinkschulte, Lars; Hafner, Julian; Geimer, Marcus

doi:10.1007/s41321-019-0043-5

Cited by 5 publications

(10 citation statements)

References 2 publications

(2 reference statements)

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“…In practical operation, the gravity centre of the materials in the bucket is not in the ideal position, namely the gravity centre is not in the vertical plane passing through the O 1 -axis (Figure 4). At this time, the phenomenon of so-called bias load (unbalanced load) appears, which causes the generation of the tilt cylinder force (some scholars ignored it 5,11–17,26–30 ). If this factor is not taken into account in the weighing model, the weight measurement of the materials will have greater errors (it has been confirmed in Validation analysis Section).…”

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

“…In fact, the moment of inertia of the whole mechanism (including the bucket) around the fixed O 0 -axis is a time-varying variable in the process of up-down motion of the working mechanism. It has been found through many simulations that the influence of the change on the measurement accuracy of the weighing model could not be ignored (but the scholars ignored it 5,11–20,26–30 ). So 0Jmechw needs to be refined in (15).…”

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

“…Similarly, the gravity centre of the whole mechanism (including the bucket) is also changing in real time during the movement process and its influence on the measurement accuracy of the weighing model can’t be ignored (but the scholars also ignored it 5,11–20,26–30 ). Therefore, the following items of the model need to be refined in (16).…”

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

“…It has been found through many simulations that the influence on the measurement accuracy of the weighing model could not be ignored, but the scholars ignored it. 5,11–20,26–30 As a result, the term 0Jmechw in the Model N is regarded as a constant term while in the Model Y it is a time-varying term as shown in (37) (38).…”

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

“…At present, some scholars have carried on the research in the kinematics or dynamics (ignored the load effect) and the control for the front-end mechanism of LHD or loader. 25–30 Therefore, a more accurate load dynamic model could be considered to be built to achieve high accurate weighing and adaptability.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Dynamic modelling and accuracy analysis for front-end weighing system of LHD vehicles

Liang

Liu

Meng

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part K:

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Automatically and accurately obtaining payload information from Load-Haul-Dump (LHD) vehicles is a typical application of information and intelligence technology in engineering equipment, which provides an important support for efficient and safe construction. In this paper, a novel comprehensive weighing model for LHD with high accuracy and adaptability is proposed by Newton-Euler method. The accuracy of the model has been greatly improved with the consideration of some critical factors such as materials randomness, driving cylinders coupling, dynamic characteristics of mechanism, system damping and working pavement. The effect of the critical factors on the accuracy of weighing model is deeply analysed through significance analysis and comparison tests, which provides an important basis for the improvement of weighing model. Validation shows that the novel model is superior to traditional models in accuracy and adaptability. In theory, the accuracy of novel model is at least 3 times higher than that of traditional models, and its accuracy can still achieve ±0.3% in complex velocity or acceleration motion, and the larger the load mass, the higher the accuracy. As a result, the novel comprehensive weighing model can provide accurate load information for LHD vehicles without affecting working efficiency. It is of great theory and application value to the development of information and intelligence technology in engineering equipment and contributes to efficient and safe construction.

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Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

Section: Weighing Mathematical Model Of Front-end Mechanismmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Dynamic modelling and accuracy analysis for front-end weighing system of LHD vehicles

Liang

Liu

Meng

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part K:

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Rock Extraction with Scrapers, Bulldozers and Loaders

Elbeblawi

Elsaghier

Amin

et al. 2021

Surface Mining Technology

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Machine Learning-Based Shoveling Trajectory Optimization of Wheel Loader for Fuel Consumption Reduction

et al. 2023

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The difference in fuel consumption of wheel loaders can be more than 30% according to different shoveling trajectories for shoveling operations, and the optimization of shoveling trajectories is an important way to reduce the fuel consumption of shoveling operations. The existing shoveling trajectory optimization method is mainly through theoretical calculation and simulation analysis, which cannot fully consider the high randomness and complexity of the shoveling process. It is difficult to achieve the desired optimization effect. Therefore, this paper takes the actual shoveling operation data as the basis. The factors that have a high impact on the fuel consumption of shoveling are screened out through Kernel Principal Component Analysis. Moreover, the mathematical model of fuel consumption of shoveling operation is established by Support Vector Machine and combined with the Improved Particle Swarm Optimization algorithm to optimize the shoveling trajectory. To demonstrate the generalization ability of the model, two materials, gravel, and sand, are selected. Meanwhile, the influence of different engine speeds on the shoveling operation is considered. We optimize the shoveling trajectories for three different engine speeds. The optimized trajectories are verified and compared with the sample data and manually controlled shoveling data. The results show that the optimized trajectory can reduce the fuel consumption of shoveling operation by 27.66% and 24.34% compared with the manually controlled shoveling of gravel and sand, respectively. This study provides guidance for the energy-efficient operation of wheel loaders.

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Real-time Load Determination of Wheel Loader Components

Cited by 5 publications

References 2 publications

Dynamic modelling and accuracy analysis for front-end weighing system of LHD vehicles

Dynamic modelling and accuracy analysis for front-end weighing system of LHD vehicles

Rock Extraction with Scrapers, Bulldozers and Loaders

Machine Learning-Based Shoveling Trajectory Optimization of Wheel Loader for Fuel Consumption Reduction

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