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Weak Fault Diagnosis of Rolling Bearing Based on Improved Stochastic Resonance
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作者 Xiaoping Zhao Yifei Wang +2 位作者 Yonghong Zhang Jiaxin Wu Yunging Shi 《Computers, Materials & Continua》 SCIE EI 2020年第7期571-587,共17页
Stochastic resonance can use noise to enhance weak signals,effectively reducing the effect of noise signals on feature extraction.In order to improve the early fault recognition rate of rolling bearings,and to overcom... Stochastic resonance can use noise to enhance weak signals,effectively reducing the effect of noise signals on feature extraction.In order to improve the early fault recognition rate of rolling bearings,and to overcome the shortcomings of lack of interaction in the selection of SR(Stochastic Resonance)method parameters and the lack of validation of the extracted features,an adaptive genetic random resonance early fault diagnosis method for rolling bearings was proposed.compared with the existing methods,the AGSR(Adaptive Genetic Stochastic Resonance)method uses genetic algorithms to optimize the system parameters,and further optimizes the parameters while considering the interaction between the parameters.This method can effectively extract the weak fault features of the bearing.In order to verify the effect of feature extraction,the feature signal extracted by AGSR method was input into the Fully connected neural network for fault diagnosis.the practicality of the algorithm is verified by simulation data and rolling bearing experimental data.the results show that the proposed method can effectively detect the early weak features of rolling bearings,and the fault diagnosis effect is better than the existing methods. 展开更多
关键词 Rolling bearing weak fault stochastic resonance genetic algorithm neural network
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Weak Fault Detection of Rotor Winding Inter-Turn Short Circuit in Excitation System Based on Residual Interval Observer
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作者 Gang Liu Xinqi Chen +4 位作者 Lijuan Bao Linbo Xu Chaochao Dai Lei Yang Chengmin Wang 《Structural Durability & Health Monitoring》 EI 2023年第4期337-351,共15页
Aiming at the fact that the rotor winding inter-turn weak faults can hardly be detected due to the strong electromagnetic coupling effect in the excitation system,an interval observer based on current residual is desi... Aiming at the fact that the rotor winding inter-turn weak faults can hardly be detected due to the strong electromagnetic coupling effect in the excitation system,an interval observer based on current residual is designed.Firstly,the mechanism of the inter-turn short circuit of the rotor winding in the excitation system is modeled under the premise of stable working conditions,and electromagnetic decoupling and system simplification are carried out through Park Transform.An interval observer is designed based on the current residual in the two-phase coordinate system,and the sensitive and stable conditions of the observer is preset.The fault diagnosis process based on the interval observer is formulated,and the observer gain matrix is convexly optimized by linear matrix inequality.The numerical simulation and experimental results show that the inter-turn short circuit weak fault is hardly detected directly through the current signal,but the fault is quickly and accurately diagnosed through the residual internal observer.Compared with the traditional fault diagnosis method based on excitation current,the diagnosis speed and accuracy are greatly improved,and the probability of misdiagnosis also decreases.This method provides a theoretical basis for weak fault identification of excitation systems,and is of great significance for the operation and maintenance of excitation systems. 展开更多
关键词 Excitation system interval observer rotor winding weak fault detection inter-turn shortcut
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Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction 被引量:7
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作者 Jianhong Wang Liyan Qiao +1 位作者 Yongqiang Ye YangQuan Chen 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2017年第2期353-360,共8页
The bearing weak fault feature extraction is crucial to mechanical fault diagnosis and machine condition monitoring. Envelope analysis based on Hilbert transform has been widely used in bearing fault feature extractio... The bearing weak fault feature extraction is crucial to mechanical fault diagnosis and machine condition monitoring. Envelope analysis based on Hilbert transform has been widely used in bearing fault feature extraction. A generalization of the Hilbert transform, the fractional Hilbert transform is defined in the frequency domain, it is based upon the modification of spatial filter with a fractional parameter, and it can be used to construct a new kind of fractional analytic signal. By performing spectrum analysis on the fractional envelope signal, the fractional envelope spectrum can be obtained. When weak faults occur in a bearing, some of the characteristic frequencies will clearly appear in the fractional envelope spectrum. These characteristic frequencies can be used for bearing weak fault feature extraction. The effectiveness of the proposed method is verified through simulation signal and experiment data. © 2017 Chinese Association of Automation. 展开更多
关键词 Bearings (machine parts) Condition monitoring EXTRACTION fault detection Feature extraction Frequency domain analysis Hilbert spaces Mathematical transformations Spectrum analysis
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Weak thruster fault detection for AUV based on stochastic resonance and wavelet reconstruction 被引量:5
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作者 刘维新 王玉甲 +1 位作者 刘星 张铭钧 《Journal of Central South University》 SCIE EI CAS CSCD 2016年第11期2883-2895,共13页
When the bi-stable stochastic resonance method was applied to enhance weak thruster fault for autonomous underwater vehicle(AUV), the enhancement performance could not satisfy the detection requirement of weak thruste... When the bi-stable stochastic resonance method was applied to enhance weak thruster fault for autonomous underwater vehicle(AUV), the enhancement performance could not satisfy the detection requirement of weak thruster fault. As for this problem, a fault feature enhancement method based on mono-stable stochastic resonance was proposed. In the method, in order to improve the enhancement performance of weak thruster fault feature, the conventional bi-stable potential function was changed to mono-stable potential function which was more suitable for aperiodic signals. Furthermore, when particle swarm optimization was adopted to adjust the parameters of mono-stable stochastic resonance system, the global convergent time would be long. An improved particle swarm optimization method was developed by changing the linear inertial weighted function as nonlinear function with cosine function, so as to reduce the global convergent time. In addition, when the conventional wavelet reconstruction method was adopted to detect the weak thruster fault, undetected fault or false alarm may occur. In order to successfully detect the weak thruster fault, a weak thruster detection method was proposed based on the integration of stochastic resonance and wavelet reconstruction. In the method, the optimal reconstruction scale was determined by comparing wavelet entropies corresponding to each decomposition scale. Finally, pool-experiments were performed on AUV with thruster fault. The effectiveness of the proposed mono-stable stochastic resonance method in enhancing fault feature and reducing the global convergent time was demonstrated in comparison with particle swarm optimization based bi-stochastic resonance method. Furthermore, the effectiveness of the proposed fault detection method was illustrated in comparison with the conventional wavelet reconstruction. 展开更多
关键词 autonomous underwater vehicle(AUV) THRUSTER weak fault particle swarm optimization(PSO) mono-stable stochastic resonance wavelet reconstruction
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A Preliminary Study on a Seismotectonic Model for the Active Faults in the Xining Urban Area 被引量:2
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作者 Tian Qinjian Li Zhimin +1 位作者 Zhang Junlong Ren Zhikun 《Earthquake Research in China》 2008年第1期15-23,共9页
On the basis of the Xining active urban fault survey, we studied the relationship between the active urban fault and fold deformation. The result of this research shows that the Huangshuihe fault and the NW-striking f... On the basis of the Xining active urban fault survey, we studied the relationship between the active urban fault and fold deformation. The result of this research shows that the Huangshuihe fault and the NW-striking fault on the northern bank of the Huangshulbe River are tensional faults on top of an anticline, the Nanchuanhe fault is a transverse tear fault resulting from differential folding on two sides of the fault, the east bank of the Beichuanhe River fault is a compressional fault developed on the core or climb of a syncline. By balance profile analysis of fold deformation and inversion of gravity anomaly data, we obtained the depth of the detachment plane and established the seismotectonic model of the )fining urban area. Based on the seismotectonic model, we analyzed the earthquake potential of the active urban fault. 展开更多
关键词 Urban active fault weak active fault Seismotectonic model Earthquake risk Xining
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Sandbox modeling of fault formation and evolution in the Weixinan Sag, Beibuwan Basin, China 被引量:9
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作者 Tong Hengmao 《Petroleum Science》 SCIE CAS CSCD 2012年第2期121-128,共8页
Fault formation and evolution in the presence of multiple pre-existing weaknesses has not been investigated extensively in rift basins. The fault systems of Weixinan Sag, Beibuwan Basin of China, which is fully covere... Fault formation and evolution in the presence of multiple pre-existing weaknesses has not been investigated extensively in rift basins. The fault systems of Weixinan Sag, Beibuwan Basin of China, which is fully covered with high-precision 3-D seismic data and is rich in oil-gas resources, have been successfully reproduced by sandbox modeling in this study with inclusion of multiple pre-existing weaknesses in the experimental model. The basic characteristics of fault formation and evolution revealed by sandbox modeling are as follows. 1) Weakness-reactivation faults and weakness-related faults are formed much earlier than the distant-weakness faults (faults far away from and with little or no relationship to the weakness). 2) Weakness-reactivation faults and weakness-related faults develop mainly along or parallel to a pre-existing weakness, while distant-weakness faults develop nearly perpendicular to the extension direction. A complicated fault system can be formed in a fixed direction of extension with the existence of multiple pre-existing weaknesses, and the complicated fault system in the Weixinan Sag formed gradually in a nearly N-S direction with multiple pre-existing weaknesses. 3) The increase in the length and number of faults is closely tied to the nature of pre-existing weaknesses. The sandbox model may provide a new clue to detailed fault system research for oil and gas exploration in rift basins. 展开更多
关键词 fault system rift basin multiple pre-existing weaknesses Weixinan Sag sandbox modeling
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Application of the Duffing Chaotic Oscillator Model for Early Fault Diagnosis-Ⅰ. Basic Theory 被引量:1
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作者 HU Niao-qing, WEN Xi-sen, CHEN MinCollege of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, P. R. China 《International Journal of Plant Engineering and Management》 2002年第2期67-75,共9页
In this paper, the well-known Duffing equation and the nonlinear equation describing vibration of the human eardrum are introduced from elastic nonlinear system theory. According to the fact that the human ear can dis... In this paper, the well-known Duffing equation and the nonlinear equation describing vibration of the human eardrum are introduced from elastic nonlinear system theory. According to the fact that the human ear can distinguish weak sound with small difference, the idea that the Duffing oscillator can be used to detect a weak signal and diagnose early fault of machinery is proposed. In order to obtain a model for weak signal detection via the Duffing oscillator, the first step is to seek all forms of solutions of the Duffing equation. The second step is to study global bifurcations of the Duffing equation using qualitative analysis theory of a dynamic system. That is to say, a series of bifurcations thresholds of the Duffing equation can be analyzed by the Melnikov function and a subharmonics Melnikov function. Then the three types of bifurcations thresholds varying with damping and external exciting amplitude are discussed. The analysis concludes that the bifurcation threshold corresponding to the maximum orbit of solutions outside the homo-clinic orbit of the Duffing equation can be used to detect a weak signal. Finally, the implementing model of the Duffing oscillator for weak signal detection is given. 展开更多
关键词 fault diagnosis Duffing oscillator weak signal detection BIFURCATION
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参数自适应FMD在轴承早期故障诊断中的应用
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作者 王红 王泽宇 何勇 《振动工程学报》 北大核心 2025年第8期1788-1798,共11页
针对特征模态分解(FMD)的轴承早期微弱故障诊断效果易受滤波器长度L、频段分割数K、模态分解个数n影响的问题,提出用遗传算法优化FMD预设参数,并以峭度、包络熵和修正的自适应包络谱特征能量比为综合目标函数的诊断方法。该方法利用遗... 针对特征模态分解(FMD)的轴承早期微弱故障诊断效果易受滤波器长度L、频段分割数K、模态分解个数n影响的问题,提出用遗传算法优化FMD预设参数,并以峭度、包络熵和修正的自适应包络谱特征能量比为综合目标函数的诊断方法。该方法利用遗传算法比较不同预设参数下经FMD分解各分量信号的综合目标函数值,并选取其中最大值对应的L、K、n作为FMD的预设参数,通过FMD处理后信号的包络谱特征判定轴承的故障类型。经西储大学和辛辛那提大学的公开故障轴承数据以及转向架轴箱轴承数据验证,该方法具有较好的抗噪声能力和有效的早期微弱故障诊断能力。 展开更多
关键词 滚动轴承 早期微弱故障 特征模态分解 遗传算法
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基于RTH-FMD和1.5维谱的滚动轴承早期故障诊断方法研究
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作者 唐贵基 张龙 +3 位作者 薛贵 徐振丽 曾鹏飞 王晓龙 《动力工程学报》 北大核心 2025年第5期714-723,共10页
针对滚动轴承的早期故障诊断问题,深入研究了一种红尾鹰(RTH)算法参数优化特征模态分解(FMD)和1.5维谱相结合的滚动轴承故障诊断方法。首先,通过理论分析,设计出脉冲能量因子指标(PEFI),并将其作为适应度函数;其次,利用RTH算法并行搜寻... 针对滚动轴承的早期故障诊断问题,深入研究了一种红尾鹰(RTH)算法参数优化特征模态分解(FMD)和1.5维谱相结合的滚动轴承故障诊断方法。首先,通过理论分析,设计出脉冲能量因子指标(PEFI),并将其作为适应度函数;其次,利用RTH算法并行搜寻FMD的关键影响参数组合,自适应地达到信号最佳分解效果;再次,通过PEFI选取分解后的最优信号分量,并进行包络解调运算;最后,计算包络信号的1.5维谱,在谱图中分析、提取轴承故障特征频率信息,实现轴承早期微弱故障的准确性诊断。模拟故障实验和工程案例分析结果表明:所研究方法解决了参数自适应的问题,大幅降低了噪声及其他干扰成分对诊断的影响,拥有良好的鲁棒性,能够有效提取轴承早期故障信号中的微弱特征信息,具有重要的实际工程参考价值。 展开更多
关键词 滚动轴承 微弱故障提取 特征模态分解 红尾鹰算法 1.5维谱
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连云港市主要断裂活动性研究
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作者 张建民 王志才 +5 位作者 付俊东 王冬雷 夏暖 王凯 许洪泰 王雷 《海洋地质与第四纪地质》 北大核心 2025年第2期98-109,共12页
采用地质地貌调查、高精度浅层地震反射波法及折射波法探测、跨断层钻孔联合地质剖面探测和年代测试等多种方法对连云港市主要断层开展了探测工作。利用高质量的第一手资料,对海州-韩山断裂(F_(1))等3条代表性断裂的第四纪活动性进行了... 采用地质地貌调查、高精度浅层地震反射波法及折射波法探测、跨断层钻孔联合地质剖面探测和年代测试等多种方法对连云港市主要断层开展了探测工作。利用高质量的第一手资料,对海州-韩山断裂(F_(1))等3条代表性断裂的第四纪活动性进行了综合研究。结果表明北北东向海州-韩山断裂(F_(1))和北东向烧香河断裂(F_(3))是早第四纪断裂,而北西向南城-新浦断裂(F_(8))是前第四纪断裂。连云港地区和山东半岛具有类似的地震构造背景,属于中国东部第四纪构造弱活动区,第四纪断裂活动较弱,地震活动水平也低,区内历史破坏性地震记录仅有一次1495年的连云港海州4?级地震。6级及以上地震活动主要集中于区内西侧北北东向郯庐断裂带和东侧南黄海盆地。按照构造类比原则,区内具有发生5级左右地震的可能。值得注意的是,来自外围的郯庐断裂带及南黄海盆地的强震对于区内影响大于本地地震,特别是1668年郯城8?级地震对研究区地震烈度影响达Ⅷ度。因此,在连云港市防震减灾工作中应综合考虑本地5级左右地震以及外围强震影响。 展开更多
关键词 断裂活动性 活动断层探测 构造弱活动区 第四纪 连云港
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极弱电网非对称故障下构网型变流器故障穿越能力提升技术
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作者 赵冬梅 裴建楠 +1 位作者 白俊辉 刘崇茹 《高电压技术》 北大核心 2025年第11期5329-5339,I0001-I0004,共15页
为了解决极弱电网非对称故障场景下构网型变流器构网能力如何表征以及如何提升的问题,首先通过理论推导建立了传统故障穿越策略下虚拟同步发电机(virtual synchronous generator,VSG)型构网变流器的构网特性表征模型,用以表征电网非对... 为了解决极弱电网非对称故障场景下构网型变流器构网能力如何表征以及如何提升的问题,首先通过理论推导建立了传统故障穿越策略下虚拟同步发电机(virtual synchronous generator,VSG)型构网变流器的构网特性表征模型,用以表征电网非对称故障阶段构网变流器的构网同步、电压支撑、过电压抑制特性。在此基础上,结合成功穿越所具备的约束条件,进而提出了构网型变流器故障阶段构网可行域的概念,用以定量衡量构网型变流器在不同策略下能够成功穿越何种程度的电网故障。其次,提出了一种全故障场景下无穿越死区的增强型VSG穿越策略。研究结果表明,所提策略具有强网场景电流限幅内无功最大支撑、弱网场景电压精准控制、过电压自主抑制、构网自主同步等优势,在限制短路电流的同时可有效提升构网型变流器在不同电网强度下对电网的支撑作用。 展开更多
关键词 极弱电网 构网技术 VSG 非对称故障 故障穿越 大干扰稳定性
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基于多尺度空洞卷积神经网络的滚动轴承故障识别方法
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作者 汪小虎 赵荣珍 +1 位作者 邓林峰 郑玉巧 《兰州理工大学学报》 北大核心 2025年第3期55-63,共9页
针对现有卷积神经网络模型参数偏多导致滚动轴承智能诊断效率低和识别准确率受限于训练样本数量的问题,提出了基于多尺度空洞卷积神经网络的滚动轴承故障识别方法.该方法首先在模型的输入层采用大尺寸的空洞卷积核和标准卷积核提取一维... 针对现有卷积神经网络模型参数偏多导致滚动轴承智能诊断效率低和识别准确率受限于训练样本数量的问题,提出了基于多尺度空洞卷积神经网络的滚动轴承故障识别方法.该方法首先在模型的输入层采用大尺寸的空洞卷积核和标准卷积核提取一维振动信号的多尺度敏感特征,然后使用尺寸为1×1和3×1的小卷积核以及2×1的最大池化操作对输入层所提取敏感特征进一步提取深层抽象特征,最后用全局平均池化层代替传统卷积神经网络的全连接层.同时,分别采用西储大学轴承故障数据和实验室轴承故障数据进行实验验证.结果表明,该方法泛化性能良好,并且能够在训练样本较少的情况下出色地完成故障识别任务,即使在一定噪声干扰下也能够对轴承微弱故障准确识别. 展开更多
关键词 多尺度空洞卷积神经网络 滚动轴承 故障识别 小样本 微弱故障
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基于稀疏引导IEWT-MOMEDA的行星齿轮箱微弱故障检测
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作者 王子博 李宏坤 +2 位作者 张孔亮 曹顺心 孙福彪 《振动.测试与诊断》 北大核心 2025年第5期961-968,1064,共9页
行星齿轮箱出现早期故障时,由于工业环境的背景噪声干扰和故障冲击在复杂传递路径中衰减,其微弱故障特征难以有效提取和识别。针对此问题,提出了稀疏引导的改进经验小波变换(improved empirical wavelet transform,简称IEWT)结合多点最... 行星齿轮箱出现早期故障时,由于工业环境的背景噪声干扰和故障冲击在复杂传递路径中衰减,其微弱故障特征难以有效提取和识别。针对此问题,提出了稀疏引导的改进经验小波变换(improved empirical wavelet transform,简称IEWT)结合多点最优最小熵解卷积(multipoint optimal minimum entropy deconvolution adjusted,简称MOMEDA)的微弱故障特征提取方法。首先,提出了一种新的故障综合指标(fault composite index,简称FCI),结合信号频谱的幅值包络线将原始信号自适应分解为一组IEWT分量;其次,通过稀疏引导方法选出敏感分量作为原始微弱故障信号的稀疏表示;最后,对敏感分量信号进行MOMEDA处理,降低信号噪声并提取微弱信号故障特征频率用于检测。仿真和实验结果表明,所提方法对含有噪声的非平稳非线性行星齿轮箱故障信号有良好的诊断效果,验证了该方法的有效性,为工程实践中行星齿轮箱弱故障的诊断和检测提供了一种方法。 展开更多
关键词 行星齿轮箱 经验小波变换 多点最优最小熵解卷积 稀疏引导 微弱故障诊断
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一种滚动轴承早期微弱故障检测与诊断方法 被引量:1
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作者 郭盼盼 张文斌 +4 位作者 崔奔 赵春林 尹治棚 刘标 刘相江 《航空动力学报》 北大核心 2025年第3期327-344,共18页
针对现有方法难以及时检测与诊断滚动轴承早期微弱故障的难题,提出一种滚动轴承早期微弱故障检测与诊断方法。基于基尼指数提取滚动轴承全寿命数据振动信号的特征指标,对轴承早期微弱故障进行及时检测;其次,基于增强奇异谱分解+蜜獾算... 针对现有方法难以及时检测与诊断滚动轴承早期微弱故障的难题,提出一种滚动轴承早期微弱故障检测与诊断方法。基于基尼指数提取滚动轴承全寿命数据振动信号的特征指标,对轴承早期微弱故障进行及时检测;其次,基于增强奇异谱分解+蜜獾算法优化最大相关峭度解卷积的方法对轴承早期微弱故障振动信号进行有效分解,最大相关峭度解卷积降噪和凸显故障冲击效果性能,对滚动轴承早期微弱故障进行有效诊断。使用辛辛那提滚动轴承全寿命数据集进行试验,并将所提方法与传统的振动峰-峰值和有效值检测方法进行对比,该方法能够分别提前1700 min和30 min检测并诊断出滚动轴承发生早期微弱故障。 展开更多
关键词 滚动轴承 早期微弱故障 基尼指数 增强奇异谱分解 蜜獾算法 最大相关峭度解卷积
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交流故障下光储弱电网电压波动传导路径及对频率变化影响分析
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作者 刘万 尹纯亚 +2 位作者 李凤婷 陈睿康 黄锡芳 《电网与清洁能源》 北大核心 2025年第7期107-115,121,共10页
针对交流故障下光储弱电网电压波动传导路径不明及电压频率耦合复杂的问题,阐述了高比例光储接入西藏电网后系统电压和频率所面临的问题及挑战。基于故障后的节点电压表达式定义了电压波动主导系数,识别了有功、无功共同影响下网内节点... 针对交流故障下光储弱电网电压波动传导路径不明及电压频率耦合复杂的问题,阐述了高比例光储接入西藏电网后系统电压和频率所面临的问题及挑战。基于故障后的节点电压表达式定义了电压波动主导系数,识别了有功、无功共同影响下网内节点电压的波动趋势。进一步考虑电压与功率之间的交互影响特性,利用灵敏度分析法明确了交流故障下电压跌落、回升传导路径及关键影响因素。结合光储电站功率特性与负荷的电压频率特性分析了交流故障下电压波动对频率的影响特性,得到暂态期间光储弱电网的特征。基于DIgSILENT/PowerFactory中的IEEE-9节点系统搭建光储弱电网仿真模型,验证了理论分析的正确性。 展开更多
关键词 光储弱电网 交流故障 电压波动 主导系数 频率变化
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基于外加信号和高斯函数的二维非对称随机共振模型研究
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作者 邓颖 杜鲁春 +1 位作者 鲁进 李思思 《云南大学学报(自然科学版)》 北大核心 2025年第3期420-429,共10页
为了提高二维随机共振的信号增强能力,提出一种基于外加信号和高斯函数的二维非对称随机共振系统(novel two-dimensional asymmetric bistable potential system based on external signal and Gaussian function,NTABPS-EG).首先,以输... 为了提高二维随机共振的信号增强能力,提出一种基于外加信号和高斯函数的二维非对称随机共振系统(novel two-dimensional asymmetric bistable potential system based on external signal and Gaussian function,NTABPS-EG).首先,以输出信噪比为衡量指标,研究了3种非对称势的系统性能,根据分析结果选取阱深阱宽非对称势进行后续研究,并探究了不同参数下系统输出信噪比随噪声强度的变化趋势.其次,采用四阶龙格库塔算法进行数值模拟,并采用遗传算法求解最佳参数,使系统得到最佳输出响应.通过与二维指数势双稳系统(two-dimensional exponential potential bi-stable potential system,TEPBPS)的对比,发现NTABPS-EG系统更能有效地驱动粒子跃迁,对微弱信号的恢复效果较好.最后,将NTABPS-EG系统应用于轴承故障检测,实验结果表明系统可以有效诊断出轴承的内外圈故障,且诊断能力优于TEPBPS,证明了系统的实用性和先进性. 展开更多
关键词 二维随机共振 遗传算法 微弱信号检测 轴承故障诊断
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考虑配电网故障重构的电压薄弱节点辨识方法
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作者 杨隽雯 尚磊 +2 位作者 叶欣智 刘承锡 董旭柱 《电力工程技术》 北大核心 2025年第1期39-49,共11页
在建设新型配电系统的背景下,电压越限问题逐渐突出,系统稳定运行日趋复杂。文中基于全纯嵌入法,研究拓扑变化下节点电压指标轨迹的偏移特性,提出考虑配电网故障重构的薄弱节点辨识方法。首先,基于电力系统解耦的思想提出节点电压指标... 在建设新型配电系统的背景下,电压越限问题逐渐突出,系统稳定运行日趋复杂。文中基于全纯嵌入法,研究拓扑变化下节点电压指标轨迹的偏移特性,提出考虑配电网故障重构的薄弱节点辨识方法。首先,基于电力系统解耦的思想提出节点电压指标与配电网电压可视化安全域;然后,通过全纯嵌入法求解出节点电压指标轨迹,定义电压指标偏移距离表征节点电压指标轨迹特性,计及配电网故障后的拓扑变化提出概率性节点电压指标轨迹求解方法;最后,综合配电网正常态工况与N-1+1故障态运行工况,根据配电网电压可视化安全域与节点电压指标轨迹的相对位置关系,构建配电网薄弱节点评价指标体系,提出薄弱节点辨识方法。基于IEEE 33节点配电系统进行分析,结果表明,所提方法可实现节点电压状态的可视化监测,准确辨识电压薄弱节点。 展开更多
关键词 全纯嵌入法 薄弱节点 故障重构 节点电压指标 电压安全域 电压稳定边界
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极弱电网、严重故障下构网型变流器故障穿越能力提升技术研究
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作者 裴建楠 赵冬梅 +1 位作者 白俊辉 刘崇茹 《中国电机工程学报》 北大核心 2025年第23期9362-9375,I0024,共15页
该文针对极弱电网、严重故障场景研究传统故障穿越策略对虚拟同步发电机(virtual synchronous generator,VSG)型构网变流器大干扰稳定性的影响。首先,通过理论推导并建立传统故障穿越策略下VSG构网特性表征模型,用以表征电网故障阶段VS... 该文针对极弱电网、严重故障场景研究传统故障穿越策略对虚拟同步发电机(virtual synchronous generator,VSG)型构网变流器大干扰稳定性的影响。首先,通过理论推导并建立传统故障穿越策略下VSG构网特性表征模型,用以表征电网故障阶段VSG构网同步特性与电压支撑特性;在此基础上,结合故障成功穿越所需具备的条件,进一步提出故障穿越可行域的概念以及故障严重程度的界定原则,明确传统VSG故障穿越策略对于不同程度故障、不同限流幅值的适用范围;并且,针对传统故障穿越无法覆盖全故障场景的问题,提出一种名为动态限幅电压控制的新型控制方式(dynamic limiting voltage control,DLVC),并在其基础上进一步提出一种增强型VSG故障穿越策略(dynamic limiting voltage control fault ride through,DLVC-FRT),其具有近区无功、远区电压控制的灵活控制特性,在限制短路电流的同时可有效提升VSG在极弱电网场景下对电网电压的支撑能力;最后,在PSCAD/EMTDC中构建仿真,并验证所提策略的有效性。 展开更多
关键词 构网技术 虚拟同步机 故障穿越 极弱电网 大扰动稳定性
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谱峭度增强循环谱的轴承早期微弱故障诊断方法
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作者 杨伟 邓晓磊 +2 位作者 孙若斌 金若尘 陈雪峰 《机械制造与自动化》 2025年第6期24-29,共6页
早期的轴承故障振动成分中包含大量的噪声成分,严重干扰了循环谱中的特征辨识。为解决这一问题,提出谱峭度增强循环谱的轴承早期微弱故障诊断方法。通过谱峭度滤波选出故障特征频带,抑制强噪声干扰;再经过谱峭度协助后在循环谱图中能够... 早期的轴承故障振动成分中包含大量的噪声成分,严重干扰了循环谱中的特征辨识。为解决这一问题,提出谱峭度增强循环谱的轴承早期微弱故障诊断方法。通过谱峭度滤波选出故障特征频带,抑制强噪声干扰;再经过谱峭度协助后在循环谱图中能够凸显故障特征,从而实现更早期轴承故障诊断。通过仿真、实验和工程数据分析证明了所提出方法的优越性和有效性。 展开更多
关键词 循环功率谱密度 谱峭度 轴承故障诊断 微弱特征提取
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有限传感条件下基于特征增强的CNN-Transformer复合故障诊断模型与可解释性研究
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作者 吕志远 白晓天 《辽宁科技学院学报》 2025年第5期24-31,共8页
针对高端机械装备在极端工况下受使用及安装条件限制导致传感器布置方案受限引起微弱故障无法准确识别的问题,文章提出一种基于特征增强的CNN-Transformer神经网络的故障诊断方法。该方法首先构建一种基于Transformer编码器的神经网络,... 针对高端机械装备在极端工况下受使用及安装条件限制导致传感器布置方案受限引起微弱故障无法准确识别的问题,文章提出一种基于特征增强的CNN-Transformer神经网络的故障诊断方法。该方法首先构建一种基于Transformer编码器的神经网络,通过设置注意力偏置矩阵,强化原始信号与对应传感器处理后信号的交互关系,弱化其与不同传感器处理后信号的交互关系,再将融合后的特征输入网络,有效提取丰富互补的故障特征。利用滑动窗口将一维时序信号输入一维CNN层进行特征嵌入,然后引入多层Transformer编码器捕捉全局信息。利用多种复合故障的轴承故障数据对所提方法进行了实验分析,实验结果表明,该方法在复合故障实验中的准确率达97.2%,并且聚类效果明显,较好地解决了复合故障中微弱故障特征无法准确提取的问题,具有很好的实际应用价值。 展开更多
关键词 微弱故障 深度学习 TRANSFORMER 滚动轴承 有限传感
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