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RESEARCH OF PROBLEMS ON REALIZING DIRECT ALGORITHM OF WAVELET TRANSFORM 被引量:2
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作者 Tang BaopingZhong YoumingQin ShurenDepartment of Mechanical Engineering,Chongqing University,Chongqing 400044, China 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2003年第2期136-140,共5页
Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the dire... Direct algorithm of wavelet transform (WT) is the numerical algorithmobtained from the integral formula of WT by directly digitization. Some problems on realizing thealgorithm are studied. Some conclusions on the direct algorithm of discrete wavelet transform (DWT),such as discrete convolution operation formula of wavelet coefficients and wavelet components,sampling principle and technology to wavelets, deciding method for scale range of wavelets, measuresto solve edge effect problem, etc, are obtained. The realization of direct algorithm of continuouswavelet transform (CWT) is also studied. The computing cost of direct algorithm and Mallat algorithmof DWT are still studied, and the computing formulae are obtained. These works are beneficial todeeply understand WT and Mallat algorithm. Examples in the end show that direct algorithm can alsobe applied widely. 展开更多
关键词 wavelet transform direct algorithm mallat algorithm
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Power Quality Disturbance Classification Method Based on Wavelet Transform and SVM Multi-class Algorithms 被引量:1
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作者 Xiao Fei 《Energy and Power Engineering》 2013年第4期561-565,共5页
The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wav... The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wavelet transform coefficients and wavelet transform energy distribution constitute feature vectors. These vectors are then trained and tested using SVM multi-class algorithms. Experimental results demonstrate that the SVM multi-class algorithms, which use the Gaussian radial basis function, exponential radial basis function, and hyperbolic tangent function as basis functions, are suitable methods for power quality disturbance classification. 展开更多
关键词 Power Quality DISTURBANCE Classification wavelet transform SVM MULTI-CLASS algorithmS
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Biomedical Image Processing Using FCM Algorithm Based on the Wavelet Transform
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作者 闫玉华 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2004年第3期18-20,共3页
An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decompo... An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced. 展开更多
关键词 biomedical image processing FCM algorithm wavelet transform texture feature
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Audio Watermarking Using Wavelet Transform and Genetic Algorithm for Realizing High Tolerance to MP3 Compression
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作者 Shinichi Murata Yasunari Yoshitomi Hiroaki Ishii 《Journal of Information Security》 2011年第3期99-112,共14页
Recently, several digital watermarking techniques have been proposed for hiding data in the frequency domain of audio signals to protect the copyrights. However, little attention has been given to the optimal position... Recently, several digital watermarking techniques have been proposed for hiding data in the frequency domain of audio signals to protect the copyrights. However, little attention has been given to the optimal position in the frequency domain for embedding watermarks. In general, there is a tradeoff between the quality of the watermarked audio and the tolerance of watermarks to signal processing methods, such as compression. In the present study, a watermarking method developed for a visual image by using a wavelet transform was applied to an audio clip. We also improved the performance of both the quality of the watermarked audio and the extraction of watermarks after compression by the MP3 technique. To accomplish this, we created a multipurpose optimization problem for deciding the positions of watermarks in the frequency domain and obtaining a near-optimum solution. The near-optimum solution is obtained by using a genetic algorithm. The experimental results show that the proposed method generates watermarked audios of good quality and high tolerance to MP3 compression. In addition, the security was improved by using the characteristic secret key to embed and extract the watermark information. 展开更多
关键词 AUDIO WATERMARKING GENETIC algorithm Optimization wavelet transforms SECRET Key
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An Orthogonal Wavelet Transform Fractionally Spaced Blind Equalization Algorithm Based on the Optimization of Genetic Algorithm
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作者 廖娟 郭业才 季童莹 《Defence Technology(防务技术)》 SCIE EI CAS 2011年第2期65-71,共7页
An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square er... An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels. 展开更多
关键词 information processing technique genetic algorithm orthogonal wavelet transform fractionally spaced equalizer blind equalization underwater acoustic channel
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A New Image Watermarking Scheme Using Genetic Algorithm and Residual Numbers with Discrete Wavelet Transform
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作者 Peter Awonnatemi Agbedemnab Mohammed Akolgo Moses Apambila Agebure 《Journal of Information Security》 2023年第4期422-436,共15页
Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presen... Transmission of data over the internet has become a critical issue as a result of the advancement in technology, since it is possible for pirates to steal the intellectual property of content owners. This paper presents a new digital watermarking scheme that combines some operators of the Genetic Algorithm (GA) and the Residue Number (RN) System (RNS) to perform encryption on an image, which is embedded into a cover image for the purposes of watermarking. Thus, an image watermarking scheme uses an encrypted image. The secret image is embedded in decomposed frames of the cover image achieved by applying a three-level Discrete Wavelet Transform (DWT). This is to ensure that the secret information is not exposed even when there is a successful attack on the cover information. Content creators can prove ownership of the multimedia content by unveiling the secret information in a court of law. The proposed scheme was tested with sample data using MATLAB2022 and the results of the simulation show a great deal of imperceptibility and robustness as compared to similar existing schemes. 展开更多
关键词 Discrete wavelet transform (DWT) Digital Watermarking Encryption Genetic algorithm (GA) Residue Number System (RNS) GARN
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PARAMETERS OPTIMIZATION OF CONTINUOUS WAVELET TRANSFORM AND ITS APPLICATION IN ACOUSTIC EMISSION SIGNAL ANALYSIS OF ROLLING BEARING 被引量:8
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作者 ZHANG Xinming HE Yongyong HAO Rujiang CHU Fulei 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2007年第2期104-108,共5页
Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform (CWT) has been successfully used in the field of fault diagnosis. The principle of ... Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform (CWT) has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission (AE) signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT. 展开更多
关键词 Rolling bearing Fault diagnosis Acoustic emission (AE) Continuous wavelet transform (CWT) Genetic algorithm
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Developing an Evolutionary Algorithm to Search for an Optimal Multi-Mother Wavelet Packets Combination
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作者 Ohad Bar Siman Tov J. David Schaffer Kenneth J. McLeod 《Journal of Biomedical Science and Engineering》 2015年第7期458-470,共13页
The wavelet transform is a popular analysis tool for non-stationary data, but in many cases, the choice of the mother wavelet and basis set remains uncertain, particularly when dealing with physiological data. Further... The wavelet transform is a popular analysis tool for non-stationary data, but in many cases, the choice of the mother wavelet and basis set remains uncertain, particularly when dealing with physiological data. Furthermore, the possibility exists for combining information from numerous mother wavelets so as to exploit different features from the data. However, the combinatorics become daunting given the large number of basis sets that can be utilized. Recent work in evolutionary computation has produced a subset selection genetic algorithm specifically aimed at the discovery of small, high-performance, subsets from among a large pool of candidates. Our aim was to apply this algorithm to the task of locating subsets of packets from multiple mother wavelet decompositions to estimate cardiac output from chest wall motions while avoiding the computational cost of full signal reconstruction. We present experiments which show how a continuous assessment metric can be extracted from the wavelets coefficients, but the dual-objective nature of the algorithm (high accuracy with small feature sets) imposes a need to restrict the sensitivity of the continuous accuracy metric in order to achieve the small subset size desired. A possibly subtle tradeoff seems to be needed to meet the dual objectives. 展开更多
关键词 wavelet transform Data Mining GENETIC algorithm
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Impulse Response Identification Based on Varying Scale Orthogonal Wavelet Packet Transform
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作者 LIHe-Sheng MAOJian-Qin ZHAOMing-Sheng 《自动化学报》 EI CSCD 北大核心 2005年第4期567-577,共11页
In this paper, by applying a group of specific orthogonal wavelet packet to Eykho?algorithm, a new impulse response identification algorithm based on varying scale orthogonal WPTis provided. In comparison to Eykho? al... In this paper, by applying a group of specific orthogonal wavelet packet to Eykho?algorithm, a new impulse response identification algorithm based on varying scale orthogonal WPTis provided. In comparison to Eykho? algorithm, the new algorithm has better practicability andwider application range. Simulation results show that the proposed impulse response identificationalgorithm can be applied to both deterministic and random systems, and is of higher identificationprecision, stronger anti-noise interference ability and better system dynamic tracking property. 展开更多
关键词 微波转换 WPT 时间频率分析 Eykhoff算法 脉冲响应
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一种融合小波变化和精简USAN的SUSAN角点检测方法
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作者 滕敏 王长庚 《振动.测试与诊断》 北大核心 2026年第1期172-178,223,共8页
针对传统的小吸收同值核区(small univalue segment assimilating nucleus,简称SUSAN)算法对建筑物进行形变检测,存在计算量大、实时性较差和角点准确性低等问题,提出了一种SUSAN改进算法。首先,引入小波变化以及均值阈值计算,提高算法... 针对传统的小吸收同值核区(small univalue segment assimilating nucleus,简称SUSAN)算法对建筑物进行形变检测,存在计算量大、实时性较差和角点准确性低等问题,提出了一种SUSAN改进算法。首先,引入小波变化以及均值阈值计算,提高算法的检测速度;其次,通过精简像素点集的筛选,减少了检测时间;最后,对大楼建筑物进行了对比实验。结果表明,所提出的改进算法在检测白化严重的照片时,角点检测的正确率和检测率相比SUSAN算法提高了21.24%和11.70%,提升效果显著,同时对其他类型建筑物的角点检测效果也有一定提升。 展开更多
关键词 小吸收同值核区算法 小波变化 吸收同值核区 均值阈值计算
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无人机信号时差估计算法研究分析
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作者 孙大洋 尹铎城 +2 位作者 徐睿阳 周昊燃 范宇哲 《无人系统技术》 2026年第1期90-101,共12页
随着无人机“黑飞”问题日益凸显,无人机检测与定位技术受到了广泛关注。由于时差估计是到达时差(TDOA)定位的核心,为确定适用于无人机信号的最优时差估计算法,对广义互相关(GCC)、多重信号分类(MUSIC)算法以及小波变换分析三种算法进... 随着无人机“黑飞”问题日益凸显,无人机检测与定位技术受到了广泛关注。由于时差估计是到达时差(TDOA)定位的核心,为确定适用于无人机信号的最优时差估计算法,对广义互相关(GCC)、多重信号分类(MUSIC)算法以及小波变换分析三种算法进行综合评析与仿真实验。首先,对上述算法的国内外研究进行梳理,并从抗干扰能力、计算量和适用范围等角度对上述时差估计算法进行对比分析。其次,通过基于正交频分复用(OFDM)信号的时差估计仿真实验,得出在高斯噪声环境下,GCC呈现最高的估计精度,在30 dB下达到0.398%的相对误差;同时,还设置了各算法的运行时间以及对不同噪声的鲁棒性测试实验,并进行结果分析与原因探究。最后,总结各实验表现,得出GCC为无人机信号时差估计最优算法,并探讨了时差估计的后续研究方向和前景。 展开更多
关键词 无人机定位 时差估计 广义互相关 MUSIC算法 小波变换 OFDM信号
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基于变分贝叶斯优化宽度学习的轴承故障诊断
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作者 时培明 靳诺 +1 位作者 张玉皓 许学方 《燕山大学学报》 北大核心 2026年第1期9-15,共7页
针对宽度学习进行故障诊断容易使模型出现过拟合的问题,本文提出了一种变分贝叶斯优化宽度学习的故障诊断模型。首先利用小波包变换与快速傅里叶变换结合的方法,分解原始振动信号,重构其基本波形,提取出故障敏感特征。随后,利用宽度学... 针对宽度学习进行故障诊断容易使模型出现过拟合的问题,本文提出了一种变分贝叶斯优化宽度学习的故障诊断模型。首先利用小波包变换与快速傅里叶变换结合的方法,分解原始振动信号,重构其基本波形,提取出故障敏感特征。随后,利用宽度学习系统构建故障诊断模型,并通过变分贝叶斯对权值矩阵优化处理,更新变分分布参数,估计其权值矩阵的后验分布,之后进行故障诊断,有效解决了过拟合的问题。实验结果显示,该方法在准确率、精确率、召回率上分别提高了9.34%、5.64%、7.65%,具有更好的稳定性。 展开更多
关键词 滚动轴承 小波包变换 宽度学习 故障诊断 变分贝叶斯优化算法
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基于小波变换与GA优化模糊控制的复合电源能量管理策略
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作者 张奥 龚国庆 《北京信息科技大学学报(自然科学版)》 2026年第1期80-91,共12页
针对电动汽车单一电源电流冲击大的问题,构建了电容半主动拓扑的复合电源,并提出一种基于小波变换与遗传算法(genetic algorithm,GA)优化模糊控制的能量管理策略。利用Haar小波分解需求功率,以高频分量及储能元件荷电状态(state of char... 针对电动汽车单一电源电流冲击大的问题,构建了电容半主动拓扑的复合电源,并提出一种基于小波变换与遗传算法(genetic algorithm,GA)优化模糊控制的能量管理策略。利用Haar小波分解需求功率,以高频分量及储能元件荷电状态(state of charge,SOC)为输入,通过GA优化隶属度函数参数实现功率精准分配。在新欧洲驾驶循环(new European driving cycle,NEDC)及中国轻型汽车行驶工况-乘用车(China light-duty vehicle test cycle-passenger car,CLTC-P)等工况下的仿真表明,相比单一电源策略,所提策略峰值电流平均降低约28.0%,均方根(root mean square,RMS)电流平均降低约21.0%,并将高电流区间占比压缩至6%以内,电池温升幅度降低34.8%和37.8%;在不同SOC条件下均表现出鲁棒性,对电流指标的优化幅度稳定保持在20%~28%区间,有效延长了电池循环寿命。 展开更多
关键词 复合电源 小波变换 模糊控制 遗传算法
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结合先验知识的退化条码复原算法研究
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作者 袁斌 王道芳 李晨 《机械设计与制造》 北大核心 2026年第3期110-114,119,共6页
针对商品分拣装置入库过程中条码识别效果不佳的问题,提出了一种结合先验知识的条码复原算法。通过快速小波变换算法对透视映射后的校正图像进行预增强,并设计了一种自适应阈值的条码重构方法,首先通过垂直投影曲线的波峰波谷对边界初... 针对商品分拣装置入库过程中条码识别效果不佳的问题,提出了一种结合先验知识的条码复原算法。通过快速小波变换算法对透视映射后的校正图像进行预增强,并设计了一种自适应阈值的条码重构方法,首先通过垂直投影曲线的波峰波谷对边界初步确定,然后通过局部阈值和差分运算构建的隶属度函数对边界精确定位;最后以公开条码数据集和实际采集图像进行试验验证。结果表明,所提方法能够有效解决退化条码的解码问题,在识别率提升了7%以上,更易对外界因素造成的模糊条码进行复原。 展开更多
关键词 条码 复原算法 小波变换 隶属度函数 自适应局部阈值 差分运算
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基于WT-SSA-LSTM的羊舍PM_(2.5)浓度预测模型研究
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作者 周冰 董佳琦 +3 位作者 邢赫 陈苑冰 王裕莞 刘双印 《农业机械学报》 北大核心 2026年第5期417-426,共10页
集约化羊养殖中,环境管理技术落后和缺失是导致羊舍环境恶化的关键因素,准确预测羊舍的环境参数变化对于确保羊的健康成长和提高羊养殖业的经济收益至关重要。PM_(2.5)颗粒物是威胁羊健康成长和繁殖的重要因素,为了精准把握羊舍内PM_(2... 集约化羊养殖中,环境管理技术落后和缺失是导致羊舍环境恶化的关键因素,准确预测羊舍的环境参数变化对于确保羊的健康成长和提高羊养殖业的经济收益至关重要。PM_(2.5)颗粒物是威胁羊健康成长和繁殖的重要因素,为了精准把握羊舍内PM_(2.5)的浓度规律,本文提出WT-SSA-LSTM模型,使用小波变换(Wavelet transform,WT)对羊舍环境参数数据进行分解重构,消除数据噪声,结合麻雀搜索算法(Sparrow search algorithm,SSA)对长短时记忆网络(Long short-term memory network,LSTM)模型的隐藏层神经元数、学习率和batch_size进行优化,调整输入模型的参数,避免参数选取的随机性,进一步提高模型性能。实验结果表明,WT-SSA-LSTM模型的各项指标均优于其他预测模型,其MAE、RMSE、MSE、NRMSE、R^(2)分别达到0.3497μg/m^(3)、0.6004μg/m^(3)、0.3605μg^(2)/m^(6)、0.0057和0.9981,证明本文提出的WT-SSA-LSTM预测模型具有较高的精度和较好的稳定性,为集约化羊群养殖羊舍的PM_(2.5)浓度变化监测和调控提供指导性建议。 展开更多
关键词 羊舍 PM_(2.5)浓度预测 小波变换降噪 麻雀搜索算法 长短时记忆网络
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判决门限辅助的多媒体网络信息入侵检测
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作者 赵奕祺 巫立峰 +1 位作者 郑浩 孙硕 《计算机仿真》 2026年第2期373-377,共5页
多媒体网络数据包括海量的视频、音频及图像等数据。这些数据不仅体量大,还具有复杂的时空特性。为了解决上述特性导致入侵检测精度降低的问题,提出一种判决门限辅助的多媒体网络信息入侵检测方法。根据多媒体网络运行数据的时间序列,... 多媒体网络数据包括海量的视频、音频及图像等数据。这些数据不仅体量大,还具有复杂的时空特性。为了解决上述特性导致入侵检测精度降低的问题,提出一种判决门限辅助的多媒体网络信息入侵检测方法。根据多媒体网络运行数据的时间序列,采用离散小波变换算法将多媒体网络数据划分为细节信号与近似信号,有效地提取出与入侵行为紧密相关的数据。根据数据的划分结果,利用信息熵进一步提取入侵行为数据的特征,获得特征熵并划分出入侵等级。结合特征熵结果构建高斯混合模型,设置判决门限,从而精准判断出入侵行为,完成多媒体网络信息入侵检测算法设计。仿真结果表明:所提方法可以准确检测出入侵后的多媒体网络运行信息流量状态为连接密度没有规律,杂乱无章;入侵检测精度显著提高至0.97,且能够在最短时间内检测出网络是否遭受入侵。 展开更多
关键词 判决门限 多媒体网络 信息入侵检测 离散小波变换算法 时间序列
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基于IBKA-VMD-WTC-TSLANeT的短期电力负荷预测
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作者 彭彪 于惠钧 谢雄峰 《科学技术与工程》 北大核心 2026年第5期2009-2017,共9页
短期电力负荷预测是电力系统运行和管理的重要组成部分,对优化电力调度、提高电力系统可靠性具有重要作用。针对现有预测模型对高随机性的电力负荷特征提取能力不足问题提出一种短期电力负荷预测模型。它包括使用改进黑翅鸢算法(improve... 短期电力负荷预测是电力系统运行和管理的重要组成部分,对优化电力调度、提高电力系统可靠性具有重要作用。针对现有预测模型对高随机性的电力负荷特征提取能力不足问题提出一种短期电力负荷预测模型。它包括使用改进黑翅鸢算法(improved black kite algorithm, IBKA)优化参数的变分模态分解(variational mode decomposition, VMD)的数据分解部分,以及由小波变换卷积(wavelet transform convolution, WTC)和时间序列轻量自适应网络(time series lightweight adaptive network, TSLANet)组成的预测部分。首先使用VMD将原始数据分解为多个平稳的子序列,在分解中引入使用拉丁超立方抽样、Gompertz模型步长调整策略、北方苍鹰优化算法(northern goshawk optimization, NGO)随机整数因子改进的BKA算法对分解层数和惩罚因子进行寻优,提高其分解精度。接着将分解的各个分量分别与气温和湿度数据输入WTC-TSLANeT组合模型进行预测,其中WTC通过小波变换对时间序列进行多尺度分解以增强模型对复杂时间序列的表征能力,TSLANet通过局部特征提取和频域特征增强,进一步提升模型对时间依赖关系的建模能力。最终将各个分量的预测值叠加重构得到最终预测值。对比实验结果表明,所提模型有更强的电力负荷特征提取能力和更高的预测精准度。 展开更多
关键词 短期负荷预测 改进黑翅鸢算法 变分模态分解 小波变换卷积 时间序列轻量自适应网络
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小波包能量熵下电力调度设备状态辨识算法
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作者 刘嗣萃 周迎伟 +3 位作者 魏志峥 翟元 马超 王佐民 《信息技术》 2026年第3期203-208,共6页
电力系统设备间存在的多种相互作用和耦合效应,导致了系统的非线性特性。单纯依靠高斯核函数来建立的状态辨识模型无法完全捕捉这些非线性关系,对此,研究小波包能量熵下电力调度设备状态辨识算法。构建电力调度设备状态辨识模型,并以该... 电力系统设备间存在的多种相互作用和耦合效应,导致了系统的非线性特性。单纯依靠高斯核函数来建立的状态辨识模型无法完全捕捉这些非线性关系,对此,研究小波包能量熵下电力调度设备状态辨识算法。构建电力调度设备状态辨识模型,并以该模型为基础,采用小波包算法对其进行优化。通过计算小波包能量熵,将复杂的非线性关系转化为可量化的特征值;将该特征值作为设备状态的特征信息,得出首次辨识结果并建立样本集,并与辨识模型相结合,完成电力调度设备状态辨识。实验结果表明,此算法能够准确辨识电力调度设备的多类别状态。 展开更多
关键词 电力调度设备 小波包变换算法 小波包能量熵 高斯核函数
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基于连续小波变换的土壤有机质含量估测
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作者 吴斗庆 郭辉 《黑龙江工程学院学报》 2026年第2期43-51,共9页
采煤活动导致采煤区土壤结构破坏及有机质分布发生变化,因此,对采煤拉张裂隙区土壤有机质含量的精准估测具有重要意义。以安徽省淮北市朱庄煤矿3522工作面拉张裂隙区为对象,采集90份土壤样本,测定其光谱反射率与有机质含量数据。首先对... 采煤活动导致采煤区土壤结构破坏及有机质分布发生变化,因此,对采煤拉张裂隙区土壤有机质含量的精准估测具有重要意义。以安徽省淮北市朱庄煤矿3522工作面拉张裂隙区为对象,采集90份土壤样本,测定其光谱反射率与有机质含量数据。首先对原始光谱信号进行Savitzky-Golay平滑和一阶导数处理,然后通过小波熵选取Gaussian4(Gaus4)、Morlet和Mexican hat(Mexh)3种小波基函数,对光谱数据进行多尺度连续小波变换,结合皮尔逊相关分析与遗传算法筛选特征波段。最后,采用偏最小二乘回归、Lasso回归与随机森林回归构建土壤有机质含量估测模型。结果表明:经过连续小波变换处理后土壤光谱与有机质之间的相关性有所增强,其中,Morlet小波提取的特征波段数最多;经遗传算法优化后,未使用连续小波变换特征波段数量为901个,而Morlet、Mexh和Gaus4的特征波段数分别减至301个、162个和179个,有效降低数据维度;Morlet-GA-Lasso模型在训练集和验证集的决定系数均为0.76,均方根误差分别为0.49 g·kg^(-1)和0.42 g·kg^(-1),测试集相对分析误差为2.06,表明该模型在采煤裂隙区具有较强的适应性和估测能力。 展开更多
关键词 连续小波变换 土壤有机质 遗传算法 随机森林回归 偏最小二乘回归
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基于图像融合的输电线路覆冰重量估计研究
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作者 周子涵 舒征宇 +3 位作者 雷明 毛洪彬 任冠臣 李建斌 《计算机测量与控制》 2026年第3期216-222,共7页
输电线路覆冰是电力系统运行中常见且危害性极大的气象灾害,其附加荷载会导致导线弧垂增加、绝缘性能下降甚至杆塔损毁;基于此,对输电线路覆冰重量估计问题进行了研究;针对无人机巡检图像因拍摄角度差异导致的几何畸变以及低能见度条件... 输电线路覆冰是电力系统运行中常见且危害性极大的气象灾害,其附加荷载会导致导线弧垂增加、绝缘性能下降甚至杆塔损毁;基于此,对输电线路覆冰重量估计问题进行了研究;针对无人机巡检图像因拍摄角度差异导致的几何畸变以及低能见度条件下图像质量下降的情况,采用透视变换进行视角校正,并利用改进小波变换融合可见光与红外图像,以提升图像清晰度、对比度和细节表现;结合SURF特征点检测、FLANN匹配与加权平均策略,实现了输电线路全景图像的无缝拼接;在拼接图像中提取导线弧垂参数,并结合抛物线力学模型与导线设计参数,反演计算线路覆冰重量;经实验测试,该方法在多日实测数据中与拉力传感器测值的平均误差小于6%,在准确性、鲁棒性和计算效率方面均优于传统方法,能够满足电力系统覆冰监测与防灾减灾的工程应用需求。 展开更多
关键词 覆冰重量 透视变换 小波变换 SURF算法 图像拼接
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