具有天气抑制功能的多层关注网络无人机风电场站故障检测

IF 2.9 4区 工程技术 Q3 ENERGY & FUELS
Zhijie Zeng, Ye Tian, Dawei Chen, Xiaojian Wang, Rui Wang, Mingyuan Shi
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引用次数: 0

摘要

随着风电行业的不断发展,风电场的检测工作越来越复杂,人工检测已难以满足实际需要。无人机智能检测技术的应用为风电场带来了一种新的检测方式。然而,无人机检查可能会受到许多因素的影响,如风电场站特定地点的光照条件、雨、雪、雾等天气因素。为此,本文提出了风电场站无人机故障巡检天气因素抑制的多层关注神经网络策略,以实现对风电场站的高精度无人巡检。首先,本文提出了一种具有天气抑制功能的多层关注网络,通过天气抑制模块可以有效降低甚至消除天气条件的影响,并通过多层关注网络提高模型对小目标的检测能力。本文基于多层关注网络,构建了风电场无人机云侧智能巡检系统总体设计方案,融合了基于视觉与点云信息融合的多场景巡检与感知方法,实现了高精度无人巡检。设计了正常和恶劣条件下的控制实验对模型进行了测试,测试结果表明本文所构建的模型具有良好的性能。通过对相关经济效益指标的比较,表明本文模型兼顾了准确性和复杂性,具有较好的实际应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations

Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations

Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations

Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations

Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations

With the continuous development of the wind power industry, the inspection work of wind farms is becoming more and more complex, and it is difficult for manual inspection to meet the actual needs. The application of unmanned aerial vehicle (UAV) intelligent inspection technology has brought a new inspection method to wind farms. However, drone inspection may be affected by many factors such as light conditions, rain, snow, fog and other weather factors at the specific site of the wind farm station. Therefore, this paper proposes a multi-layer attention neural network strategy for weather factor suppression of UAV fault inspection of wind farm stations to achieve high-precision unmanned inspection of wind farm stations. Firstly, this paper proposes a multi-layer attention network with a weather suppression function, which can effectively reduce or even eliminate the influence of weather conditions through the weather suppression module and improve the ability of the model to detect small targets through the multi-layer attention network. Based on the multi-layer attention network, this paper constructs the overall design scheme of the cloud-side intelligent inspection system of the wind farm UAV and integrates the multi-scene inspection and perception method based on the fusion of visual and point cloud information to achieve high-precision unmanned inspection. Furthermore, control experiments under normal and harsh conditions are designed to test the model, and the test results show that the model constructed in this paper has excellent performance. According to the comparison of relevant economic benefit indicators, the model in this paper takes into account both accuracy and complexity, and has good practical application value.

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来源期刊
IET Renewable Power Generation
IET Renewable Power Generation 工程技术-工程:电子与电气
CiteScore
6.80
自引率
11.50%
发文量
268
审稿时长
6.6 months
期刊介绍: IET Renewable Power Generation (RPG) brings together the topics of renewable energy technology, power generation and systems integration, with techno-economic issues. All renewable energy generation technologies are within the scope of the journal. Specific technology areas covered by the journal include: Wind power technology and systems Photovoltaics Solar thermal power generation Geothermal energy Fuel cells Wave power Marine current energy Biomass conversion and power generation What differentiates RPG from technology specific journals is a concern with power generation and how the characteristics of the different renewable sources affect electrical power conversion, including power electronic design, integration in to power systems, and techno-economic issues. Other technologies that have a direct role in sustainable power generation such as fuel cells and energy storage are also covered, as are system control approaches such as demand side management, which facilitate the integration of renewable sources into power systems, both large and small. The journal provides a forum for the presentation of new research, development and applications of renewable power generation. Demonstrations and experimentally based research are particularly valued, and modelling studies should as far as possible be validated so as to give confidence that the models are representative of real-world behavior. Research that explores issues where the characteristics of the renewable energy source and their control impact on the power conversion is welcome. Papers covering the wider areas of power system control and operation, including scheduling and protection that are central to the challenge of renewable power integration are particularly encouraged. The journal is technology focused covering design, demonstration, modelling and analysis, but papers covering techno-economic issues are also of interest. Papers presenting new modelling and theory are welcome but this must be relevant to real power systems and power generation. Most papers are expected to include significant novelty of approach or application that has general applicability, and where appropriate include experimental results. Critical reviews of relevant topics are also invited and these would be expected to be comprehensive and fully referenced. Current Special Issue. Call for papers: Power Quality and Protection in Renewable Energy Systems and Microgrids - https://digital-library.theiet.org/files/IET_RPG_CFP_PQPRESM.pdf Energy and Rail/Road Transportation Integrated Development - https://digital-library.theiet.org/files/IET_RPG_CFP_ERTID.pdf
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