Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm
As an important tool for loading, unloading, and distributing palletized goods, forklifts are widely used in different links of industrial production process. However, due to the rapid increase in the types and quantities of goods, item statistics have become a major bottleneck in production. Based...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/5808221 |
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| _version_ | 1832563008229867520 |
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| author | Zhenyu Li Ke Lu Yanhui Zhang Zongwei Li Jia-Bao Liu |
| author_facet | Zhenyu Li Ke Lu Yanhui Zhang Zongwei Li Jia-Bao Liu |
| author_sort | Zhenyu Li |
| collection | DOAJ |
| description | As an important tool for loading, unloading, and distributing palletized goods, forklifts are widely used in different links of industrial production process. However, due to the rapid increase in the types and quantities of goods, item statistics have become a major bottleneck in production. Based on machine vision, the paper proposes a method to count the amount of goods loaded and unloaded within the working time limit to analyze the efficiency of the forklift. The proposed method includes the data preprocessing section and the object detection section. In the data preprocessing section, through operations such as framing and clustering the collected video data and using the improved image hash algorithm to remove similar images, a new dataset of forklift goods was built. In the object detection section, the attention mechanism and the replacement network layer were used to improve the performance of YOLOv5. The experimented results showed that, compared with the original YOLOv5 model, the improved model is lighter in size and faster in detection speed without loss of detection precision, which could also meet the requirements for real-time statistics on the operation efficiency of forklifts. |
| format | Article |
| id | doaj-art-4649d8c8825141ae9a8d5bf944d66ec0 |
| institution | Kabale University |
| issn | 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-4649d8c8825141ae9a8d5bf944d66ec02025-02-03T01:21:09ZengWileyJournal of Mathematics2314-47852021-01-01202110.1155/2021/5808221Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 AlgorithmZhenyu Li0Ke Lu1Yanhui Zhang2Zongwei Li3Jia-Bao Liu4School of Economics and ManagementSchool of Management Science and EngineeringBusiness SchoolSchool of Economics and ManagementSchool of Mathematics and PhysicsAs an important tool for loading, unloading, and distributing palletized goods, forklifts are widely used in different links of industrial production process. However, due to the rapid increase in the types and quantities of goods, item statistics have become a major bottleneck in production. Based on machine vision, the paper proposes a method to count the amount of goods loaded and unloaded within the working time limit to analyze the efficiency of the forklift. The proposed method includes the data preprocessing section and the object detection section. In the data preprocessing section, through operations such as framing and clustering the collected video data and using the improved image hash algorithm to remove similar images, a new dataset of forklift goods was built. In the object detection section, the attention mechanism and the replacement network layer were used to improve the performance of YOLOv5. The experimented results showed that, compared with the original YOLOv5 model, the improved model is lighter in size and faster in detection speed without loss of detection precision, which could also meet the requirements for real-time statistics on the operation efficiency of forklifts.http://dx.doi.org/10.1155/2021/5808221 |
| spellingShingle | Zhenyu Li Ke Lu Yanhui Zhang Zongwei Li Jia-Bao Liu Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm Journal of Mathematics |
| title | Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm |
| title_full | Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm |
| title_fullStr | Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm |
| title_full_unstemmed | Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm |
| title_short | Research on Energy Efficiency Management of Forklift Based on Improved YOLOv5 Algorithm |
| title_sort | research on energy efficiency management of forklift based on improved yolov5 algorithm |
| url | http://dx.doi.org/10.1155/2021/5808221 |
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