Adaptive stochastic resonance quantified by a novel evaluation index for rotating machinery fault diagnosis

Lin, Yan; Xu, Xingang; Ye, Chao

doi:10.1016/j.measurement.2021.109920

Cited by 20 publications

(9 citation statements)

References 42 publications

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“…To further verify the performance of the established state identification system in health status identification, the results are statistically analyzed in this subsection. Firstly, MSE between the predicted and real health status under the two navigational speeds is calculated, and the formula for calculating MSE is equation (9). Figure 9 shows that MSE under the two navigational speeds is 2.8956 and 1.5256, respectively, which shows that the MSE values are small at both navigational speeds.…”

Section: Discussionmentioning

confidence: 99%

“…Hence, it is necessary to establish a mapping relationship between multiple signals and device status. Currently, many researchers tried to establish numerical models of devices [8,9] and used the operating signals as the input of numerical models, thereby realizing the state identification of devices. However, it is difficult to establish an accurate numerical model for complex devices, such as UAVs and marine engines, that exhibit strong nonlinear and unsteady characteristics [10].…”

Section: Introductionmentioning

confidence: 99%

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Wireless Communication System and Its Application in Big Data Remote Monitoring and Decision-Making

Kou

2022

Mathematical Problems in Engineering

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The development of computer technology has promoted the widespread application of unmanned technology. Remote monitoring of wireless devices is an application of unmanned technology. To improve the remote monitoring of wireless devices, this study establishes a remote monitoring and decision-making framework based on wireless communication systems. With the wireless communication system, signals that characterize the operating status of devices can be obtained in real-time. Based on the collected signals, the remote monitoring system can identify the current health status of wireless devices, thereby providing auxiliary decision-making for device operation. In the case study, the main engine of an unmanned surface vehicle is used as the study object. The results show that most of the relative errors corresponding to the state identification results of the established remote monitoring framework are within 5%. Moreover, the results present that the linear correlation coefficients between the predicted and real results are greater than 0.95. Therefore, the established remote monitoring framework based on the wireless communication system has good reliability in the state identification of wireless devices.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wireless Communication System and Its Application in Big Data Remote Monitoring and Decision-Making

Kou

2022

Mathematical Problems in Engineering

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“…As a qualitative evaluation index, information entropy is often used in the evaluation of image quality. The higher the information entropy [ 51 ], the better the image quality, and more information can be obtained from the image. Its expression is shown in Equation (7).…”

Section: Methodsmentioning

confidence: 99%

Three-Stage Pavement Crack Localization and Segmentation Algorithm Based on Digital Image Processing and Deep Learning Techniques

Yang

Lin

et al. 2022

Sensors

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The image of expressway asphalt pavement crack disease obtained by a three-dimensional line scan laser is easily affected by external factors such as uneven illumination distribution, environmental noise, occlusion shadow, and foreign bodies on the pavement. To locate and extract cracks accurately and efficiently, this article proposes a three-stage asphalt pavement crack location and segmentation method based on traditional digital image processing technology and deep learning methods. In the first stage of this method, the guided filtering and Retinex methods are used to preprocess the asphalt pavement crack image. The processed image removes redundant noise information and improves the brightness. At the information entropy level, it is 63% higher than the unpreprocessed image. In the second stage, the newly proposed YOLO-SAMT target detection model is used to locate the crack diseases in asphalt pavement. The model is 5.42 percentage points higher than the original YOLOv7 model on mAP@0.5, which enhances the recognition and location ability of crack diseases and reduces the calculation amount for the extraction of crack contour in the next stage. In the third stage, the improved k-means clustering algorithm is used to extract cracks. Compared with the traditional k-means clustering algorithm, this method improves the accuracy by 7.34 percentage points, the true rate by 6.57 percentage points, and the false positive rate by 18.32 percentage points to better extract the crack contour. To sum up, the method proposed in this article improves the quality of the pavement disease image, enhances the ability to identify and locate cracks, reduces the amount of calculation, improves the accuracy of crack contour extraction, and provides a new solution for highway crack inspection.

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“…e specific steps of the PSO algorithm can be found in Ref. [22]. After setting the range of design elements to be selected, a government website design scheme can be obtained by randomly selecting design elements and combining them.…”

Section: Pso-based Government Website Design Systemmentioning

confidence: 99%

Interface Design and Optimization Methods of Government Websites from a Flat Perspective

Zhong¹,

Liu

2022

Discrete Dynamics in Nature and Society

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Flat website design has become more and more popular in recent years due to its simplicity and elegance. Nevertheless, the current flat design thinking is mainly applied to conventional websites such as corporate websites. Recently, the increase in public demands has significantly increased the browsing frequency of government websites. To optimize the government website, this study establishes a government website design framework from the perspective of flattening. The established framework can extract flat design elements from the massive flat website design schemes in the past. Based on flat design elements, the particle swarm algorithm (PSO) algorithm in the established framework realizes the design and optimization of government websites. Subsequently, the performance of the CNN, which is used as the fitness function of the PSO algorithm, in predicting public acceptance is analyzed with a case study. The case results show that the average relative errors between the prediction results predicted by CNN and the real public acceptance in two provinces are 2.5416% and 1.4788%, respectively, which indicates that the predicted and real results are in good agreement. Moreover, the linear correlation coefficients between predicted and real public acceptance are 0.9553 and 0.9937, respectively, which further indicates that CNN is reliable as a fitness function of the PSO algorithm. Therefore, it is feasible to use the PSO algorithm to optimize the government website design scheme.

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Adaptive stochastic resonance quantified by a novel evaluation index for rotating machinery fault diagnosis

Cited by 20 publications

References 42 publications

Wireless Communication System and Its Application in Big Data Remote Monitoring and Decision-Making

Wireless Communication System and Its Application in Big Data Remote Monitoring and Decision-Making

Three-Stage Pavement Crack Localization and Segmentation Algorithm Based on Digital Image Processing and Deep Learning Techniques

Interface Design and Optimization Methods of Government Websites from a Flat Perspective

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