基于MODWT和BP神经网络的微电网故障诊断方法

近年来,随着微电网技术的持续发展,电力用户对其供电可靠性的要求也不断提高,因此微电网故障诊断研究也变得越来越重要。提出了一种基于极大重叠离散小波变换(MODWT)和反向传播(BP)神经网络的微电网故障诊断新方法,并通过仿真与算例进行了验证。结果表明:该方法能快速、准确地识别出故障类型,且不受故障初始相位角和过渡电阻等因素的影响;与现有的基于离散小波变换和反向传播神经网络的诊断方法相比所提出的方法可以提供更好的故障分类精度。     

虚拟环境下机床主传动系统故障诊断的仿真实现

本文介绍了用AutoCAD完成机床主传动系统三维实体造型，用VisualC 、Visual LISP等工具完成主轴箱轴承、齿轮、轴等部位在运行中出现故障时的立体动画。经压电晶体加速度传感器实时检测机床的振动信号，对这些信号进行分析(统计处理、频谱分析等)提取出故障特征，经人工神经网络、模糊决策及专家系统等手段进行决策，判定故障部位和程度，可在微机上直观地观察主轴箱在运行过程中，各故障具体部位及损伤程度的虚拟现实情况。     

基于时序特征的发电机转子故障诊断方法

提出了一种利用时序特征进行发电机转子的故障诊断方法.利用时间序列法中的AR或ARMA模型得到的脉冲传递函数的特点,并根据不同故障类别振动信号的格林函数变化的规律性,提出了利用格林函数的统计量特征作为故障诊断的特征参数进行故障诊断的方法.     

基于断电后残余电压的感应电机定子故障诊断

为了提高感应电机定子绕组故障诊断的准确性,提出了一种基于Hilbert-Huang变换(HHT)的故障诊断新方法.选取断电后零序电压的基波分量作为定子故障特征,可有效避免电源不平衡和负荷波动的影响,直接反映电机定子的不对称度.利用Hilbert-Huang变换中经验模态分解(EMD)方法对断电后的零序电压进行了分解,提取出基波分量,通过计算其均方根值可以诊断出电机定子绕组故障.在一台4 kW的感应电机上进行的实验证明了该方法的可行性和有效性.     

基于长短期记忆网络的电网故障区域定位与故障传播路径推理

为了在发生故障后维持电力系统的安全稳定,有必要实现对故障区域的快速定位并确定故障冲击的传播路径,提出基于长短期记忆网络(LSTM)的故障区域定位和故障传播路径推理方法.首先,利用LSTM建立2个故障诊断模型分别实现在线检测故障时刻和确定故障区域;然后,通过计算故障点附近线路的端口供给能量确定故障冲击的传播路径;最后,以8机36节点电网为例进行算例验证,结果表明所提模型可在发生故障后短时间内检测到故障,给出故障区域和故障冲击传播的路径,且对噪声有较强的鲁棒性.     

一种基于CGAN-CNN的同步电机转子绕组匝间短路故障诊断方法

由于同步电机故障样本数量较少,为解决同步电机故障诊断中普遍存在的样本不平衡问题,提出了一种基于条件生成式对抗网络(CGAN)和卷积神经网络(CNN)的同步电机转子绕组匝间短路故障诊断方法.首先,对传感器收集到的数据进行预处理,对正常样本和故障样本分别添加标签后输入CGAN中生成大量新样本,将生成的新样本与原始样本混合并划分训练集和测试集;然后,利用CNN训练平衡后的数据集,充分、精准地提取有效故障特征;最后,在输出端利用Softmax分类器输出故障分类结果.通过实验证明,与非平衡数据集相比,利用平衡数据集后的故障识别准确率十分稳定且达到99.5％以上,同时与平衡的原始样本数据相比,生成样本避免了噪声和其他干扰,故障诊断的准确率也更高.     

Current Diagnosis and Treatment Options for Cutaneous Adnexal Neoplasms with Follicular Differentiation

Neoplasms derived from follicular tissue are extremely rare. Clinically, they are reported as non-symptomatic, slow-growing nodules. These lesions are mainly benign, but the malignant type can occur. Mainly middle-aged people (50–60 years of age) are affected. These carcinomas are mainly localized on the head and neck or torso. They can be locally aggressive and infiltrate surrounding tissue and metastasize to regional lymph nodes. In the minority of cases, distant metastases are diagnosed. Quick and relevant diagnosis is the basis of a treatment for all types of tumors. The patient’s life expectancy depends on multiple prognostic factors, including the primary tumor size and its mitotic count. Patients should be referred to a specialized skin cancer center to receive optimal multidisciplinary treatment. This article tries to summarize all the information that is currently available about pathogenesis, diagnosis, and treatment methods of follicular tumors.     

Vibrational Spectroscopy in Assessment of Early Osteoarthritis—A Narrative Review

Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.     

电磁换向阀的卡死故障诊断

本文将提出一种直流电磁换向阀故障诊断的新方法。它利用线圈电流在启动或复位过程中的变化特征，来判断阀芯是否卡死，并且分析产生此故障的原因。此方法简单、实用、快捷，为直流电磁换向阀故障诊断技术开辟了新的途径。     

矢功率谱与RBF网络结合在旋转机械故障诊断中的应用

与传统功率谱相比,矢功率谱融合了多通道的能量信息,反映的信息更全面.径向基函数网络具有良好的推广能力和分类能力.基于此,本文结合矢功率谱和径向基函数网络,提出了一种新的故障识别方法,该方法以矢功率谱为特征向量,径向基函数网络为分类器.并以转子裂纹、转子不对中、油膜涡动为例进行实验研究,实验结果表明,该方法是有效的.