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High-precision solution to the moving load problem using an improved spectral element method 被引量:3
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作者 Shu-Rui Wen Zhi-Jing Wu Nian-Li Lu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2018年第1期68-81,共14页
In this paper, the spectral element method(SEM)is improved to solve the moving load problem. In this method, a structure with uniform geometry and material properties is considered as a spectral element, which means t... In this paper, the spectral element method(SEM)is improved to solve the moving load problem. In this method, a structure with uniform geometry and material properties is considered as a spectral element, which means that the element number and the degree of freedom can be reduced significantly. Based on the variational method and the Laplace transform theory, the spectral stiffness matrix and the equivalent nodal force of the beam-column element are established. The static Green function is employed to deduce the improved function. The proposed method is applied to two typical engineering practices—the one-span bridge and the horizontal jib of the tower crane. The results have revealed the following. First, the new method can yield extremely high-precision results of the dynamic deflection, the bending moment and the shear force in the moving load problem.In most cases, the relative errors are smaller than 1%. Second, by comparing with the finite element method, one can obtain the highly accurate results using the improved SEM with smaller element numbers. Moreover, the method can be widely used for statically determinate as well as statically indeterminate structures. Third, the dynamic deflection of the twin-lift jib decreases with the increase in the moving load speed, whereas the curvature of the deflection increases.Finally, the dynamic deflection, the bending moment and the shear force of the jib will all increase as the magnitude of the moving load increases. 展开更多
关键词 Moving load spectral element method improved function Dynamic response High precision
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Single-Channel Speech Enhancement Based on Improved Frame-Iterative Spectral Subtraction in the Modulation Domain 被引量:3
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作者 Chao Li Ting Jiang Sheng Wu 《China Communications》 SCIE CSCD 2021年第9期100-115,共16页
Aiming at the problem of music noise introduced by classical spectral subtraction,a shorttime modulation domain(STM)spectral subtraction method has been successfully applied for singlechannel speech enhancement.Howeve... Aiming at the problem of music noise introduced by classical spectral subtraction,a shorttime modulation domain(STM)spectral subtraction method has been successfully applied for singlechannel speech enhancement.However,due to the inaccurate voice activity detection(VAD),the residual music noise and enhanced performance still need to be further improved,especially in the low signal to noise ratio(SNR)scenarios.To address this issue,an improved frame iterative spectral subtraction in the STM domain(IMModSSub)is proposed.More specifically,with the inter-frame correlation,the noise subtraction is directly applied to handle the noisy signal for each frame in the STM domain.Then,the noisy signal is classified into speech or silence frames based on a predefined threshold of segmented SNR.With these classification results,a corresponding mask function is developed for noisy speech after noise subtraction.Finally,exploiting the increased sparsity of speech signal in the modulation domain,the orthogonal matching pursuit(OMP)technique is employed to the speech frames for improving the speech quality and intelligibility.The effectiveness of the proposed method is evaluated with three types of noise,including white noise,pink noise,and hfchannel noise.The obtained results show that the proposed method outperforms some established baselines at lower SNRs(-5 to +5 dB). 展开更多
关键词 short-time modulation domain single-channel speech enhancement modulation improved frame iterative spectral subtraction low SNRs
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An Improved Chirplet Transform and Its Application for Harmonics Detection 被引量:1
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作者 Guo-Sheng Hu Feng-Feng Zhu 《Circuits and Systems》 2011年第3期107-111,共5页
The chirplet transform is the generalization form of fast Fourier transform , short-time Fourier transform, and wavelet transform. It has the most flexible time frequency window and successfully used in practices. How... The chirplet transform is the generalization form of fast Fourier transform , short-time Fourier transform, and wavelet transform. It has the most flexible time frequency window and successfully used in practices. However, the chirplet transform has not inherent inverse transform, and can not overcome the signal reconstructing problem. In this paper, we proposed the improved chirplet transform (ICT) and constructed the inverse ICT. Finally, by simulating the harmonic voltages, The power of the improved chirplet transform are illustrated for harmonic detection. The contours clearly showed the harmonic occurrence time and harmonic duration. 展开更多
关键词 HARMONICS improved CHIRPLET Transform (ICT) s-transform TIME-FREQUENCY Representation (TFR)
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Fractional S-transform-part 2:Application to reservoir prediction and fluid identification
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作者 杜正聪 胥德平 张金明 《Applied Geophysics》 SCIE CSCD 2016年第2期343-352,419,共11页
The fractional S-transform (FRST) has good time-frequency focusing ability. The FRST can identify geological features by rotating the fractional Fourier transform frequency (FRFTfr) axis. Different seismic signals... The fractional S-transform (FRST) has good time-frequency focusing ability. The FRST can identify geological features by rotating the fractional Fourier transform frequency (FRFTfr) axis. Different seismic signals have different optimal fractional parameters which is not conducive to multichannel seismic data processing. Thus, we first decompose the common-frequency sections by the FRST and then we analyze the low-frequency shadow. Second, the combination of the FRST and blind-source separation is used to obtain the independent spectra of the various geological features. The seismic data interpretation improves without requiring to estimating the optimal fractional parameters. The top and bottom of a limestone reservoir can be clearly recognized on the common-frequency section, thus enhancing the vertical resolution of the analysis of the low-frequency shadows compared with traditional ST. Simulations suggest that the proposed method separates the independent frequency information in the time-fractional-frequency domain. We used field seismic and well data to verify the proposed method. 展开更多
关键词 fractional s-transform FASTICA fractional time-frequency analysis spectral decomposition
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改进谱聚类算法的商业空间区域划分方法研究
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作者 阮涛 杨沙 《信息技术》 2026年第1期103-108,共6页
常规商业空间区域划分方法主要通过采用仿真软件对研究区域进行建模,忽略空间区域节点之间的非线性关系,导致划分效果不佳。对此,提出改进谱聚类算法的商业空间区域划分方法研究。通过对商业空间视觉图像数据进行获取,得到空间数据谱密... 常规商业空间区域划分方法主要通过采用仿真软件对研究区域进行建模,忽略空间区域节点之间的非线性关系,导致划分效果不佳。对此,提出改进谱聚类算法的商业空间区域划分方法研究。通过对商业空间视觉图像数据进行获取,得到空间数据谱密度特征向量。判断空间单元区域是否相邻,从而构建二元权重矩阵。引入高阶转移概率对节点之间的非线性关系进行表征,将交叉口和道路之间关系映射为谱图关系,结合顶点聚类结果,实现空间区域划分。实验结果表明,所提方法对空间区域进行划分后,子区域空间相关度较高,划分效果好。 展开更多
关键词 改进谱聚类算法 商业空间 区域划分 二元权重矩阵
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基于谱峰插值的改进空间谱估计测向算法
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作者 陈祎 蔡晔 +2 位作者 吴迎春 秦令令 张晓丽 《电子信息对抗技术》 2026年第1期30-36,共7页
空间谱估计算法在抗噪性、极化适应性、多目标适应性等方面有着独特优势,因此相较其他被动测向算法具有更广泛的应用。工程中常对谱估计导向矢量在不同角度进行标校来修正模型误差,由于标校角度的离散性会导致空间谱估计测向结果的不连... 空间谱估计算法在抗噪性、极化适应性、多目标适应性等方面有着独特优势,因此相较其他被动测向算法具有更广泛的应用。工程中常对谱估计导向矢量在不同角度进行标校来修正模型误差,由于标校角度的离散性会导致空间谱估计测向结果的不连续性进而影响测向精度,甚至在连续跟踪目标时目标角度测量出现“台阶”问题。针对上述问题,研究了基于标校信号子空间的改进空间谱估计测向算法,并采用二维谱峰插值对空间谱估计测向精度进行提升,利用谱峰位置处九宫格范围内的离散谱峰值对真实谱峰位置进行修正,提升测向精度的同时解决测向“台阶”问题。实测数据仿真结果表明,该算法能够有效解决工程应用中空间谱估计测向离散化问题,具有测向精度高、计算量小、易于软硬件实现等优点。 展开更多
关键词 被动探测 台阶问题 改进空间谱估计 九宫格 谱峰插值 测向精度
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System error iterative identification for underwater positioning based on spectral clustering 被引量:1
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作者 LU Yu WANG Jiongqi +3 位作者 HE Zhangming ZHOU Haiyin XING Yao ZHOU Xuanying 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第4期1028-1041,共14页
The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by consideri... The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by considering the underwater tar-get as a mass point,as well as the observation system error,the traditional error model best estimation trajectory(EMBET)with little observed data and too many parameters can lead to the ill-condition of the parameter model.In this paper,a multi-station fusion system error model based on the optimal polynomial con-straint is constructed,and the corresponding observation sys-tem error identification based on improved spectral clustering is designed.Firstly,the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization.Then a multi-sta-tion non-oriented graph network is established,which can address the problem of the inaccurate identification for the sys-tem errors.Moreover,the similarity matrix of the spectral cluster-ing is improved,and the iterative identification for the system errors based on the improved spectral clustering is proposed.Finally,the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accu-rately identify the system errors,and moreover can improve the positioning accuracy for the underwater target positioning. 展开更多
关键词 acoustic positioning reduced parameter system error identification improved spectral clustering accuracy analy-sis
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New Abnormal Cervical Cell Detection Method of Multi-Spectral Pap Smears
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作者 CAO Feng CHEN Shuzhen ZENG Libo 《Wuhan University Journal of Natural Sciences》 CAS 2007年第3期476-480,共5页
Considering the problem of traditional cervical cancer detection method that brings high false negative rate (FNR) and high false positive rate (FPR), a new abnormal cervical cells detection method of multi-spectr... Considering the problem of traditional cervical cancer detection method that brings high false negative rate (FNR) and high false positive rate (FPR), a new abnormal cervical cells detection method of multi-spectral Pap smear is proposed in this thesis, on the basis of multi-spectral microscopic imaging technology and computer automotive recognition technology. At first, image in a specific wave band is segmented according to the relationship between intensity and spectrum of each pixel. Then, multi-spectral features of each pixel are extracted making use of improved cosine correlation analysis (CCA) algorithm. Combined with the characteristic of each cell's area, final definition is made. Experiments have proved the new approach could identify abnormal cells efficiently as well as lower FNR and FPR. 展开更多
关键词 MULTI-spectral cervical pap smears improved CCA
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计及风电出力不确定性的风电场集电网无功优化方法 被引量:2
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作者 樊玮 霍嘉兴 +3 位作者 刘宇 张勇军 秦颖婕 钟康骅 《电网与清洁能源》 北大核心 2025年第9期74-82,共9页
为有效计及风电出力不确定性对风电场集电网及并网点状态的影响,提高风电场无功电压支撑能力,改善风电场集电网机端电压,提出一种考虑概率潮流的风电场集电网无功优化方法。在明确风电出力概率分布的前提下,通过改进拉丁超立方抽样生成... 为有效计及风电出力不确定性对风电场集电网及并网点状态的影响,提高风电场无功电压支撑能力,改善风电场集电网机端电压,提出一种考虑概率潮流的风电场集电网无功优化方法。在明确风电出力概率分布的前提下,通过改进拉丁超立方抽样生成风电有功出力场景;确立以时序有功出力的净值和变化率为特征的风电出力特征向量,采用谱聚类的方式对风机进行分区;建立基于机会约束的风电场集电网无功优化模型,并运用半不变量法将机会约束转化为确定性约束。对广东地区某风电场运行数据进行仿真分析,仿真结果表明,该方法在保证经济性的同时,有效提升了风电场的电压安全性和无功调节能力。 展开更多
关键词 概率潮流 改进拉丁超立方抽样 谱聚类分区 无功优化 机会约束
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面向焦虑改善的睡眠脑电信号深度学习分析模型研究
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作者 黄辰 马耀龙 +5 位作者 张龑 王时绘 杨超 宋建华 陈侃松 杨伟平 《电子与信息学报》 北大核心 2025年第8期2935-2944,共10页
焦虑是一种常见的情绪障碍,其严重时会显著影响个体的身心健康。已有研究表明,睡眠与焦虑存在双向调控关系,高质量睡眠有助于缓解焦虑情绪。为提高在睡眠环境下对焦虑患者脑电信号的分析准确率,该文提出一种改进型特征金字塔网络(IFPN)... 焦虑是一种常见的情绪障碍,其严重时会显著影响个体的身心健康。已有研究表明,睡眠与焦虑存在双向调控关系,高质量睡眠有助于缓解焦虑情绪。为提高在睡眠环境下对焦虑患者脑电信号的分析准确率,该文提出一种改进型特征金字塔网络(IFPN)模型。在IFPN模型中,首先,对焦虑患者睡眠前后脑电信号进行预处理,采用脑电信号标准化和特征金字塔网络去噪,以统一脑电信号尺度并去除噪声。然后,将预处理后焦虑患者的睡眠脑电数据转换为脑熵地形图,以强化在睡眠环境下对焦虑改善的脑电信号分析能力,接着,利用改进型特征金字塔网络对脑熵地形图进行特征提取,生成特征脑地形图。最后,将特征脑地形图输入到ResNet-50进行脑电信号分析。本文在开源数据集上验证了IFPN模型的有效性。实验结果表明,在睡眠环境下,采用所提模型能够进一步提升针对焦虑脑电信号的分析能力和准确率,从而为分析睡眠对于焦虑的改善作用提供深入的理论和实验支撑。 展开更多
关键词 睡眠 焦虑 脑电图 改进型特征金字塔网络 奇异谱熵
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基于改进ARMAX模型的新型电力系统区域惯量评估方法 被引量:1
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作者 冯朔 武家辉 《电气自动化》 2025年第1期51-53,57,共4页
随着高比例可再生能源并网,电力系统频率的动态行为愈加复杂,准确评估系统惯量是保障电网安全稳定运行的关键。首先,通过考虑频率响应的谱聚类方法对新型电力系统进行区域划分,可以实现系统的有效分区;然后,提出改进ARMAX模型的新型电... 随着高比例可再生能源并网,电力系统频率的动态行为愈加复杂,准确评估系统惯量是保障电网安全稳定运行的关键。首先,通过考虑频率响应的谱聚类方法对新型电力系统进行区域划分,可以实现系统的有效分区;然后,提出改进ARMAX模型的新型电力系统区域惯量评估方法,方法采用含有遗忘因子的递推最小二乘算法,将惯量评估问题转化为对改进ARMAX模型的参数辨识问题。算例分析,在小扰动场景下对体现新型电力系统的改进10机39节点系统进行区域惯量评估误差为3.38%,对比系统不分区误差7.61%,本文方法评估惯量精确性有所提高。 展开更多
关键词 新型电力系统惯量 频率响应 频率分区 谱聚类 改进ARMAX模型
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基于脆弱性评估与谱聚类电网分区的关联输电断面辨识方法
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作者 皮俊波 张树卿 +4 位作者 李杰 张伟杰 齐世雄 范宏 刘琳琳 《电网与清洁能源》 北大核心 2025年第12期1-11,共11页
关联输电断面作为电力系统调度与监控的核心对象,其精准识别对保障系统安全稳定运行至关重要。提出一种融合脆弱性评估与谱聚类电网分区的关联输电断面识别方法,从元件脆弱性与系统结构特性双维度提升识别效能。首先,构建涵盖复杂图论... 关联输电断面作为电力系统调度与监控的核心对象,其精准识别对保障系统安全稳定运行至关重要。提出一种融合脆弱性评估与谱聚类电网分区的关联输电断面识别方法,从元件脆弱性与系统结构特性双维度提升识别效能。首先,构建涵盖复杂图论边界数、改进传输介数及潮流转移熵的综合脆弱性指标体系,既全面表征线路拓扑重要性,又精准刻画其动态响应特性;其次,采用谱聚类递归算法完成电网分区,系统生成区域间输电断面候选集;最后,通过多指标综合评价模型筛选并确定核心关联输电断面。IEEE 39节点系统仿真结果验证,该方法在输电断面识别精度、抗干扰能力及系统适应性方面均表现出显著优势,为电力系统调度决策提供了可靠的技术支撑。 展开更多
关键词 关联输电断面辨识 多维度脆弱性评估 改进传输介数 谱聚类电网分区
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基于谱载荷和改进的单一曲线模型的船舶结构疲劳寿命预报方法
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作者 孙力 廖舒婷 +2 位作者 黄小平 张兆龙 王凡超 《船舶力学》 北大核心 2025年第11期1734-1745,共12页
船舶结构长期运行于海洋环境中,因承受复杂的交变载荷而易发生疲劳裂纹扩展,故准确预报船舶结构的疲劳裂纹扩展对保证结构安全具有重要意义。本文结合基于谱分析法构建的载荷谱和改进单一曲线裂纹扩展模型,提出了一种更为精确预报船舶... 船舶结构长期运行于海洋环境中,因承受复杂的交变载荷而易发生疲劳裂纹扩展,故准确预报船舶结构的疲劳裂纹扩展对保证结构安全具有重要意义。本文结合基于谱分析法构建的载荷谱和改进单一曲线裂纹扩展模型,提出了一种更为精确预报船舶结构含近门槛区疲劳裂纹扩展的方法;并以某邮轮阳台开口角隅为例,给出了改进单一曲线模型中形状指数的确定方式,预报了该结构在谱载荷作用下的疲劳裂纹扩展,分析了初始裂纹大小、裂纹扩展模型等对裂纹扩展的影响。结果表明,本文提出的预报方法能更精确预报含近门槛区的裂纹扩展,且较CCS规范中推荐的单一曲线模型的预报结果更保守。本文的方法亦可为其它船海结构物的疲劳寿命评估提供参考。 展开更多
关键词 谱载荷 改进单一曲线模型 近门槛区 阳台开口角隅 裂纹扩展预报
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Improved common-path spectral interferometer for single-shot terahertz detection 被引量:6
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作者 SHUIQIN ZHENG QINGGANG LIN +5 位作者 YI CAI XUANKE ZENG YING LI SHIXIANG XU JINGZHEN LI DIANYUAN FAN 《Photonics Research》 SCIE EI 2018年第3期177-181,共5页
To seek high signal-to-noise ratio(SNR) is critical but challenging for single-shot intense terahertz(THz)coherent detection. This paper presents an improved common-path spectral interferometer for single-shot THz det... To seek high signal-to-noise ratio(SNR) is critical but challenging for single-shot intense terahertz(THz)coherent detection. This paper presents an improved common-path spectral interferometer for single-shot THz detection with a single chirped pulse as the probe for THz electro-optic(EO) sampling. Here, the spectral interference occurs between the two orthogonal polarization components with a required relative time delay generated with only a birefringent plate after the EO sensor. Our experiments show that this interferometer can effectively suppress the noise usually suffered in a non-common-path interferometer. The measured single-shot SNR is up to 88.85, and the measured THz waveforms are independent of the orientation of the used Zn Te EO sensor, so it is easy to operate and the results are more reliable. These features mean that the interferometer is quite qualified for applications where strong THz pulses, usually with single-shot or low repetition rate, are indispensable. 展开更多
关键词 THz improved common-path spectral interferometer for single-shot terahertz detection EOC BBO
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Improved perceptually non-uniform spectral compression for robust speech recognition 被引量:1
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作者 ZHANG Yi HE Chun-jiang +2 位作者 LUO Yuan CHEN Kai XING Wu-chao 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2013年第4期122-126,132,共6页
According to the decline of recognition rate of speech recognition system in the noise environments, an improved perceptually non-uniform spectral compression feature extraction algorithm is put forward in this paper.... According to the decline of recognition rate of speech recognition system in the noise environments, an improved perceptually non-uniform spectral compression feature extraction algorithm is put forward in this paper. This method can realize an effective compression of the speech signals and make the training and recognition environments more matching, so the recognition rate can be improved in the noise environments. By experimenting on the intelligent wheelchair platform, the result shows that the algorithm can effectively enhance the robustness of speech recognition, and ensure the recognition rate in the noise environments. 展开更多
关键词 robust speech recognition improved perceptually non-uniform spectral compression intelligent wheelchair mel-frequencycepstrum coefficients
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基于循环谱相干的IAS信号滚动轴承故障检测
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作者 王红伟 郭瑜 +2 位作者 钟辉 杨新敏 高国泽 《航空动力学报》 北大核心 2025年第12期161-169,共9页
针对循环谱相干(cyclic spectral coherence,CSCoh)故障信息丰富频带选取困难的问题,结合编码器信号的优势,以瞬时角速度(instantaneous angular speed,IAS)为信号源,提出一种基于重加权峭度(reweighted kurtosis,RK)指标自适应确定CSCo... 针对循环谱相干(cyclic spectral coherence,CSCoh)故障信息丰富频带选取困难的问题,结合编码器信号的优势,以瞬时角速度(instantaneous angular speed,IAS)为信号源,提出一种基于重加权峭度(reweighted kurtosis,RK)指标自适应确定CSCoh优化解调频带的方法。首先,基于编码器瞬时角位移信号,采用向前差分法估计IAS信号;其次,采用CSCoh分析提取滚动轴承故障分量,获得以循环阶次和谱阶次组成的双变量谱图;然后,沿谱阶次积分得到子频带改进包络谱(improved envelope spectrum,IES),再采用RK指标表征各子频带中滚动轴承故障信息的丰富性,随后沿谱阶次轴对子频带合并重构,选择合并重构后最大RK值所对应的合并后的子频带作为优化解调频带;最后通过包络分析揭示滚动轴承故障特征。采用本文所提方法对仿真信号和实验数据进行分析,并对比现有方法,所提方法能够有效提取到滚动轴承内圈和外圈故障特征。 展开更多
关键词 故障特征提取 瞬时角速度 自适应解调频带选取 循环谱相干 改进包络谱
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140 MPa超高压旋塞阀随机振动分析及安装结构改进 被引量:1
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作者 高峰 《石油机械》 北大核心 2025年第4期88-95,共8页
针对超高压旋塞阀结构的随机振动问题,利用振动自相关函数和振动功率谱密度函数对其进行分析。建立了旋塞阀系统的三维模型,使用加速度传感器采集该系统的振动信号,并利用有限元法和三区间法对模型进行了模态分析和随机振动分析,根据所... 针对超高压旋塞阀结构的随机振动问题,利用振动自相关函数和振动功率谱密度函数对其进行分析。建立了旋塞阀系统的三维模型,使用加速度传感器采集该系统的振动信号,并利用有限元法和三区间法对模型进行了模态分析和随机振动分析,根据所分析结果对结构提出优化方案,然后进行分析验证。分析结果表明:应力最大的位置位于阀体和约束件侧表面的接触位置,危险节点的最大响应频率接近该结构2阶频率,易发生共振;改进后结构的最大应力位置转移到了支撑架的斜架上,应力减小了7.3%,可有效避免振动对阀体的影响;最大应力随右侧约束件的厚度增大而减小,考虑到效果和成本,最终采用了厚度为30 mm的约束件。改进后的结构可有效避免共振。 展开更多
关键词 压裂设备 超高压旋塞阀 随机振动 三区间法 功率谱密度 模态分析 结构改进
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基于量子神经网络的语音增强算法研究
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作者 黎华 杨浩 《电声技术》 2025年第9期72-75,共4页
针对改进型谱减法的不足,提出基于量子神经网络的语音增强算法。分析听觉侧抑制网络模型,为语音的前期处理奠定基础。随后研究量子神经网络,将量子神经网络与改进型谱减法相结合进行语音增强。仿真结果表明,与改进型谱减法相比,所提语... 针对改进型谱减法的不足,提出基于量子神经网络的语音增强算法。分析听觉侧抑制网络模型,为语音的前期处理奠定基础。随后研究量子神经网络,将量子神经网络与改进型谱减法相结合进行语音增强。仿真结果表明,与改进型谱减法相比,所提语音增强算法在信噪比与听觉质量两项指标上均表现出更优的性能。 展开更多
关键词 量子神经网络 侧抑制网络 改进型谱减法 语音增强
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基于改进迁移学习的红外光谱图像自适应分割研究
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作者 陈静 徐伟 张磊 《自动化技术与应用》 2025年第1期163-167,共5页
为了从红外光谱图像中获取有用信息,设计基于改进迁移学习的红外光谱图像自适应分割方法。采集系统获取红外光谱图像,采用直方图均衡技术对红外光谱图像进行增强处理,依据增强后图像各帧像素的高斯正态分布,重建红外光谱图像,将红外光... 为了从红外光谱图像中获取有用信息,设计基于改进迁移学习的红外光谱图像自适应分割方法。采集系统获取红外光谱图像,采用直方图均衡技术对红外光谱图像进行增强处理,依据增强后图像各帧像素的高斯正态分布,重建红外光谱图像,将红外光谱图像重建结果输入双分支卷积神经网络模型,利用迁移学习子网提取红外光谱图像全局特征,结合残差注意力子网提取的图像细小特征;通过集成学习融合差异红外光谱图像特征,输出分割后的红外光谱图像。测试结果表明:该方法可实现红外光谱图像分割,且分割结果清晰,具有显著细节特征。 展开更多
关键词 改进迁移学习 红外光谱图像 自适应分割 双分支卷积 残差注意力 扩散平滑
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基于IESMD-功率谱熵-能量熵增量的泵站厂房振源辨识研究
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作者 江琦 王建康 +2 位作者 张建伟 刘喜珠 赵瑜 《振动与冲击》 北大核心 2025年第9期45-56,共12页
针对多源激励和强背景噪声干扰的泵站厂房结构难以准确辨识振源的难题,提出一种改进的极点对称模态分解(improved extreme-point symmetric mode decomposition, IESMD)-功率谱熵(power spectral entropy, PSE)-能量熵增量(energy entro... 针对多源激励和强背景噪声干扰的泵站厂房结构难以准确辨识振源的难题,提出一种改进的极点对称模态分解(improved extreme-point symmetric mode decomposition, IESMD)-功率谱熵(power spectral entropy, PSE)-能量熵增量(energy entropy increment, EEI)联合振源辨识方法。对小波阈值降噪预处理信号进行IESMD自适应分离,引入噪声频谱理论确定功率谱熵和能量熵增量阈值,定量筛选本征模态分量(intrinsic mode function, IMF)实现振源精准辨识。对打渔张泵站厂房5个典型部位的实测振动数据进行振源辨识,引入振动能量计算各分频能量占比。结果表明:该方法能够将多源信号分解为多个有效的调频调幅分量,运行期动静干涉(rotor-stator interaction, RSI)引起的水力激振是厂房振动的主振源,其振动主频为33.32 Hz,在泵座、出口弯管和电机位置能量占比最大高达84.54%、98.53%和97.15%,是引起泵站厂房振动的主要原因。 展开更多
关键词 振源辨识 改进的极点对称模态分解(IESMD) 功率谱熵(PSE) 能量熵增量(EEI) 贡献率
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