Dual-field measurement system for real-time material flow on conveyor belt

Qiao, Weiyang; Lan, Yuan; Dong, Huijie; Xiong, Xuejian; Qiao, Tiezhu

doi:10.1016/j.flowmeasinst.2021.102082

Cited by 11 publications

(6 citation statements)

References 15 publications

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“…To confirm the measurement quality and reliability, the mean relative error of indication s ¯, the standard deviation of error s , and the mean value of indication m were used as verification standards [39]. Where m i denotes the weight value of the ith time through attitude compensated algorithm, and n is the number of weights.…”

Section: The Test Results and The Evaluationmentioning

confidence: 99%

Research on attitude compensated algorithm for shipborne dynamic weighing

Xie,

Zhang,

Wang

et al. 2023

Phys. Scr.

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Shipborne dynamic weighing is fundamental in developing marine fishery resources and oceanographic research. It enables the weighing and sorting of seafood, quantitative baiting, and measurement of research sample weights in marine environments. Therefore, developing shipborne dynamic weighing systems is crucial for the integrated exploitation of marine fishery resources. However, research on shipborne dynamic weighing is limited. To address this issue, the study initially analyzed the impact of ship’s attitude information on weighing results. Subsequently, a mathematical model for shipborne dynamic weighing, incorporating compensation factors, was constructed. The compensation factors were determined using the Recursive Least Squares (RLS) method. And then real-time weight estimation was updated using Kalman filtering, effectively mitigating the influence of ship oscillations and swaying on weight measurements. Furthermore, a shipborne dynamic weighing system with a 24-bit analog-to-digital converter (ADC) and STM32F4 processor was developed. The system performance was evaluated by simulating the sail of a ship under different sea conditions on a swing platform. The results demonstrate that the average absolute percentage error of the test meets the requirement of less than 1%, and the standard deviation of the error is less than 1% F. S., which essentially meets the weight measurement requirements of marine dynamic weighing and sorting.

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Section: The Test Results and The Evaluationmentioning

confidence: 99%

Research on attitude compensated algorithm for shipborne dynamic weighing

Xie,

Zhang,

Wang

et al. 2023

Phys. Scr.

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“…At present, the laser CCD image measurement method has mature products in China. Reference [10] used the CCD camera with the upper and lower double viewpoints in the same measurement plane to measure the coal profile, and the measurement accuracy was over 96%. Because of the poor lighting conditions in coal mines, it has a great impact on coal image acquisition, and the image processing time is long and the algorithm is complex, so the speed of laser CCD image measurement is relatively slow.…”

Section: Laser Ccd Image Measurement Methodsmentioning

confidence: 99%

Research on Measuring Method of Conveying Capacity of Mining Belt Conveyor

Zhu

Zhang

2023

J. Phys.: Conf. Ser.

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This paper introduces the background of the use of mining belt conveyors, and summarizes the current research status and application of the commonly used methods for measuring the conveying capacity of belt conveyors. The development trend of belt conveyor conveying capacity measurement method in the future is put forward, that is, high measurement accuracy, strong anti-interference, and strong adaptability. At the same time, it is pointed out that a variety of combined measurement methods or non-contact measurement methods will become the belt conveyor conveying capacity. The mainstream method of measurement, the future development needs to be accompanied by the common development of artificial intelligence, image processing, machinery, electronics and other technologies.

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“…Area ratio method 32 Simple but practical The height of the material is ignored, which belongs to the fuzzy measurement method Line-laser-assisted vision method (laser triangulation method) 28,29,48 High measurement accuracy There is a breakpoint and disconnection problem of the laser line that needs to be solved Deep-learning-based classification method 49 Simple and practical, only need to replace the corresponding dataset to complete Manually labeled data are required, which are greatly affected by human subjective factors…”

Section: Declaration Of Conflicting Interestsmentioning

confidence: 99%

“…Commonly used networks include the improved single-shot detector (SSD), 23 U-net, 24 You Only Look Once (Yolo), 25,26 and temporal convolutional networks. 27 For load measurement, the mainstream methods are the optical measurement method 28,29 and the laser point cloud-based measurement method. 28,29 All of these methods have proven to be effective.…”

Section: Introductionmentioning

confidence: 99%

Deep-learning-based multistate monitoring method of belt conveyor turning section

Zhang,

Jiang,

Zhao

et al. 2023

Structural Health Monitoring

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During transportation, bulk materials are susceptible to spillage due to equipment instability and environmental factors, resulting in increased maintenance costs and environmental pollution. Thus, intelligent and efficient condition monitoring is crucial for maintaining operational efficiency of transfer equipment. It facilitates the timely identification of potential safety hazards, preventing accidents from occurring or their impact from spreading, thereby minimizing production and maintenance costs. This study presents a deep-learning-based multioperation synchronous monitoring method suitable for belt conveyors that integrate target segmentation and detection networks to simultaneously diagnose belt deviation, measure conveying load, identify idlers, and do other tasks on a self-made dataset. This method effectively reduces the complexity of multistate simultaneous monitoring and monitoring costs, thereby avoiding environmental pollution caused by transportation accidents. Experimental results show that the segmentation accuracy of the proposed method can be up to 88.72%, with a detection accuracy of 91.3% and an overall inference speed of 90.9 frames per second. Furthermore, by extending the dataset, the proposed method can incorporate additional tasks, such as belt damage, scattered material, and foreign object identifications. This study has practical significance in ensuring the normal and eco-friendly operation of bulk material transportation. Our source dataset is available at https://github.com/zhangzhangzhang1618/dataset-for-turnning-section

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Dual-field measurement system for real-time material flow on conveyor belt

Cited by 11 publications

References 15 publications

Research on attitude compensated algorithm for shipborne dynamic weighing

Research on attitude compensated algorithm for shipborne dynamic weighing

Research on Measuring Method of Conveying Capacity of Mining Belt Conveyor

Deep-learning-based multistate monitoring method of belt conveyor turning section

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