The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit ...The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit faults of Voltage Source Inverter(VSI). The stator current serves as a common indicator for detecting open-circuit faults. Due to the identical changes of the stator current between the open-phase faults in the PMSM and failures of double switches within the same leg of the VSI, this paper utilizes the zero-sequence voltage component as an additional diagnostic criterion to differentiate them.Considering the variable conditions and substantial noise of the ARDS, a novel Multi-resolution Network(Mr Net) is proposed, which can extract multi-resolution perceptual information and enhance robustness to the noise. Meanwhile, a feature weighted layer is introduced to allocate higher weights to characteristics situated near the feature frequency. Both simulation and experiment results validate that the proposed fault diagnosis method can diagnose 25 types of open-circuit faults and achieve more than98.28% diagnostic accuracy. In addition, the experiment results also demonstrate that Mr Net has the capability of diagnosing the fault types accurately under the interference of noise signals(Laplace noise and Gaussian noise).展开更多
经典AOD-Net(All in One Dehazing Network)去雾后的图像存在细节清晰度不足、明暗反差过大和画面昏暗等问题。为了解决这些图像去雾问题,提出一种在AOD-Net基础上改进的多尺度算法。改进的网络结构采用深度可分离卷积替换传统卷积方式...经典AOD-Net(All in One Dehazing Network)去雾后的图像存在细节清晰度不足、明暗反差过大和画面昏暗等问题。为了解决这些图像去雾问题,提出一种在AOD-Net基础上改进的多尺度算法。改进的网络结构采用深度可分离卷积替换传统卷积方式,减少了冗余参数量,加快了计算速度并有效地减少了模型的内存占用量,从而提高了算法去雾效率;同时采用多尺度结构在不同尺度上对雾图进行分析和处理,更好地捕捉图像的细节信息,提升了网络对图像细节的处理能力,解决了原算法去雾时存在的细节模糊问题;最后在网络结构中加入金字塔池化模块,用于整合图像不同区域的上下文信息,扩展了网络的感知范围,从而提高网络模型获取有雾图像全局信息的能力,进而改善图像色调失真、细节丢失等问题。此外,引入一个低照度增强模块,通过明确预测噪声实现去噪的目标,从而恢复曝光不足的图像。在低光去雾图像中,峰值信噪比(PSNR)和结构相似性(SSIM)指标均有显著提升,处理后的图片具有更高的整体自然度。实验结果表明:与经典AOD-Net去雾的结果相比,改进算法能够更好地恢复图像的细节和结构,使得去雾后的图像更自然,饱和度和对比度也更加平衡;在RESIDE的SOTS数据集中的室外和室内场景,相较于经典AOD-Net,改进算法的PSNR分别提升了4.5593 dB和4.0656 dB,SSIM分别提升了0.0476和0.0874。展开更多
为提升弹载成像制导中运动模糊图像目标检测的精确性与效率,提出一种轻量化且高效的运动模糊图像目标检测(Lighter and More Effective Motion-blurred Image Object Detection,LEMBD)网络。通过深入分析运动模糊图像的成因,基于成像机...为提升弹载成像制导中运动模糊图像目标检测的精确性与效率,提出一种轻量化且高效的运动模糊图像目标检测(Lighter and More Effective Motion-blurred Image Object Detection,LEMBD)网络。通过深入分析运动模糊图像的成因,基于成像机理构建了专用的运动模糊图像数据集。在不增加网络参数的前提下,采用共享权重的孪生网络设计,并引入先验知识,将清晰图像的特征学习用于模糊图像的特征提取,以同时实现对清晰与模糊图像的精准检测。此外,设计了部分深度可分离卷积替代普通卷积,显著减少了网络的参数量与计算量,并提升了学习性能。为进一步优化特征融合质量,提出跨层路径聚合特征金字塔网络,有效利用低级特征的细节信息和高级特征的语义信息。实验结果表明,所提LEMBD网络在运动模糊图像目标检测任务中的性能优于传统目标检测方法和主流运动模糊检测算法,能够为精确制导任务提供更精准的目标相对位置信息。展开更多
基金supported by the Natural Science Foundation of Jiangsu Province (Grant Nos. BK20210347)。
文摘The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit faults of Voltage Source Inverter(VSI). The stator current serves as a common indicator for detecting open-circuit faults. Due to the identical changes of the stator current between the open-phase faults in the PMSM and failures of double switches within the same leg of the VSI, this paper utilizes the zero-sequence voltage component as an additional diagnostic criterion to differentiate them.Considering the variable conditions and substantial noise of the ARDS, a novel Multi-resolution Network(Mr Net) is proposed, which can extract multi-resolution perceptual information and enhance robustness to the noise. Meanwhile, a feature weighted layer is introduced to allocate higher weights to characteristics situated near the feature frequency. Both simulation and experiment results validate that the proposed fault diagnosis method can diagnose 25 types of open-circuit faults and achieve more than98.28% diagnostic accuracy. In addition, the experiment results also demonstrate that Mr Net has the capability of diagnosing the fault types accurately under the interference of noise signals(Laplace noise and Gaussian noise).
文摘经典AOD-Net(All in One Dehazing Network)去雾后的图像存在细节清晰度不足、明暗反差过大和画面昏暗等问题。为了解决这些图像去雾问题,提出一种在AOD-Net基础上改进的多尺度算法。改进的网络结构采用深度可分离卷积替换传统卷积方式,减少了冗余参数量,加快了计算速度并有效地减少了模型的内存占用量,从而提高了算法去雾效率;同时采用多尺度结构在不同尺度上对雾图进行分析和处理,更好地捕捉图像的细节信息,提升了网络对图像细节的处理能力,解决了原算法去雾时存在的细节模糊问题;最后在网络结构中加入金字塔池化模块,用于整合图像不同区域的上下文信息,扩展了网络的感知范围,从而提高网络模型获取有雾图像全局信息的能力,进而改善图像色调失真、细节丢失等问题。此外,引入一个低照度增强模块,通过明确预测噪声实现去噪的目标,从而恢复曝光不足的图像。在低光去雾图像中,峰值信噪比(PSNR)和结构相似性(SSIM)指标均有显著提升,处理后的图片具有更高的整体自然度。实验结果表明:与经典AOD-Net去雾的结果相比,改进算法能够更好地恢复图像的细节和结构,使得去雾后的图像更自然,饱和度和对比度也更加平衡;在RESIDE的SOTS数据集中的室外和室内场景,相较于经典AOD-Net,改进算法的PSNR分别提升了4.5593 dB和4.0656 dB,SSIM分别提升了0.0476和0.0874。
文摘为提升弹载成像制导中运动模糊图像目标检测的精确性与效率,提出一种轻量化且高效的运动模糊图像目标检测(Lighter and More Effective Motion-blurred Image Object Detection,LEMBD)网络。通过深入分析运动模糊图像的成因,基于成像机理构建了专用的运动模糊图像数据集。在不增加网络参数的前提下,采用共享权重的孪生网络设计,并引入先验知识,将清晰图像的特征学习用于模糊图像的特征提取,以同时实现对清晰与模糊图像的精准检测。此外,设计了部分深度可分离卷积替代普通卷积,显著减少了网络的参数量与计算量,并提升了学习性能。为进一步优化特征融合质量,提出跨层路径聚合特征金字塔网络,有效利用低级特征的细节信息和高级特征的语义信息。实验结果表明,所提LEMBD网络在运动模糊图像目标检测任务中的性能优于传统目标检测方法和主流运动模糊检测算法,能够为精确制导任务提供更精准的目标相对位置信息。
