Multi-Object Detection Method in Construction Machinery Swarm Operations Based on the Improved YOLOv4 Model

Abstract

To handle the problem of low detection accuracy and missed detection caused by dense detection objects, overlapping, and occlusions in the scenario of complex construction machinery swarm operations, this paper proposes a multi-object detection method based on the improved YOLOv4 model. Firstly, the K-means algorithm is used to initialize the anchor boxes to improve the learning efficiency of the depth features of construction machinery objects. Then, the pooling operation is replaced with dilated convolution to solve the problem that the pooling layer reduces the resolution of feature maps and causes a high missed detection rate. Finally, focus loss is introduced to optimize the loss function of YOLOv4 to improve the imbalance of positive and negative samples during the model training process. To verify the effectiveness of the above optimizations, the proposed method is verified on the Pytorch platform with a self-build dataset. The experimental results show that the mean average precision(mAP) of the improved YOLOv4 model for multi-object detection of construction machinery can reach 97.03%, which is 2.16% higher than that of the original YOLOv4 detection network. Meanwhile, the detection speed is 31.11 fps, and it is reduced by only 0.59 fps, still meeting the real-time requirements. The research lays a foundation for environment perception of construction machinery swarm operations and promotes the unmanned and intelligent development of construction machinery swarm operations.

Design and application of electronic control system platform for construction machinery

“…The PWM control method is a traditional relay logic control system, which works by using a microcontroller as the controller to adjust the motor speed by changing the input and output signals. The expression of the output signal is shown in Equation (1).…”

“…In recent years, with the continuous development of science and technology, engineering mechanical and electronic technology has made great progress in the construction of national economy, and it has been widely used in all walks of life. But our country is in high speed development at the present stage, so how to improve the electronic control system of construction machinery is of great significance for the industrial and urban economic construction [1]. At present, most of the domestic manufacturers are using the traditional control scheme of the single chip microcomputer as the control system equipment, field operation, data acquisition and processing and other workflow.…”

OMOFuse: An Optimized Dual-Attention Mechanism Model for Infrared and Visible Image Fusion

“…Within the OMOFuse network, we have set the number of iterations to 100, the batch size to 24, and the initial learning rate to 1 × 10 −2 . For the data augmentation phase, the size is randomly center-cropped to 224 × 224, and mosaic data augmentation [51] has been applied. As the optimizer, we selected AdamW [52].…”

Wavelet LSTM for Fault Forecasting in Electrical Power Grids

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