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Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

《能源前沿（英文）》 2020年 第14卷 第4期   页码 817-835 doi: 10.1007/s11708-020-0709-9

摘要： Since gas turbine plays a key role in electricity power generating, the requirements on the safety and reliability of this classical thermal system are becoming gradually strict. With a large amount of renewable energy being integrated into the power grid, the request of deep peak load regulation for satisfying the varying demand of users and maintaining the stability of the whole power grid leads to more unstable working conditions of gas turbines. The startup, shutdown, and load fluctuation are dominating the operating condition of gas turbines. Hence simulating and analyzing the dynamic behavior of the engines under such instable working conditions are important in improving their design, operation, and maintenance. However, conventional dynamic simulation methods based on the physic differential equations is unable to tackle the uncertainty and noise when faced with variant real-world operations. Although data-driven simulating methods, to some extent, can mitigate the problem, it is impossible to perform simulations with insufficient data. To tackle the issue, a novel transfer learning framework is proposed to transfer the knowledge from the physics equation domain to the real-world application domain to compensate for the lack of data. A strong dynamic operating data set with steep slope signals is created based on physics equations and then a feature similarity-based learning model with an encoder and a decoder is built and trained to achieve feature adaptive knowledge transferring. The simulation accuracy is significantly increased by 24.6% and the predicting error reduced by 63.6% compared with the baseline model. Moreover, compared with the other classical transfer learning modes, the method proposed has the best simulating performance on field testing data set. Furthermore, the effect study on the hyper parameters indicates that the method proposed is able to adaptively balance the weight of learning knowledge from the physical theory domain or from the real-world operation domain.

关键词： gas turbine     dynamic simulation     data-driven     transfer learning     feature similarity    

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一种面向软件缺陷预测的相似性度量特征选择方法 Article

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

《信息与电子工程前沿（英文）》 2017年 第18卷 第11期   页码 1744-1753 doi: 10.1631/FITEE.1601322

摘要： 针对软件缺陷预测中不同特征与类别的相关性差异，本文提出一种基于相似性度量（similarity measure, SM）的特征选择方法。

关键词： 软件缺陷预测；特征选择；相似性度量；特征权重；特征排序列表    

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New approach for distinguishing the similarity of links

XIANG Jianyun, GE Maozhong, WANG Zhiping

《机械工程前沿（英文）》 2008年 第3卷 第1期   页码 55-58 doi: 10.1007/s11465-008-0004-7

摘要： Based on the problem of distinguishing the similarity of links in the regenerative innovation design of a kinematic chain, a new approach using the standard power matrix of the adjacent matrix is presented in this paper. The implementation of the approach is illustrated with an example. This method solves the technically baffling problem in mechanism type synthesis and reduced redundant design scheme, and raises the reliability and the efficiency of the regenerative innovation design of the kinematic chain.

关键词： kinematic     similarity     implementation     mechanism     standard    

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Case modifying of high-speed cutting database based on CSP and similarity theory

Kejun XIANG, Zhanqiang LIU, Xing AI

《机械工程前沿（英文）》 2009年 第4卷 第1期   页码 83-87 doi: 10.1007/s11465-009-0014-0

摘要： By analyzing the reasoning of a high-speed cutting database system, a case modifying method is put forward. According to the variables’ difference of the solution part in a case, a constraint satisfaction problem (CSP) and similarity calculation are used to modify a case. The constraint relationship of discrete variables is described by establishing a rule knowledge base. The algorithm of CSP is used to solve the discrete variable constraint problem. On the basis of the high-speed cutting theory, a similarity calculation formula is deduced to calculate the consecutive variables. The CSP and similarity calculation are applied to case modifying, which is possible to automatically modify cases in the high-speed cutting database system.

关键词： high-speed cutting database     case modifying     CSP     similarity calculation    

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Subspace transform induced robust similarity measure for facial images

Jian Zhang, Heng Zhang, Li-ling Bo, Hong-ran Li, Shuai Xu, Dong-qing Yuan,zhangjian@jou.edu.cn,zhangheng@jou.edu.cn

《信息与电子工程前沿（英文）》 2020年 第21卷 第9期   页码 1267-1412 doi: 10.1631/FITEE.1900552

摘要： Similarity measure has long played a critical role and attracted great interest in various areas such as and machine perception. Nevertheless, there remains the issue of developing an efficient two-dimensional (2D) robust similarity measure method for images. Inspired by the properties of subspace, we develop an effective 2D technique, named transformation similarity measure (TSM), for robust . Specifically, the TSM method robustly determines the similarity between two well-aligned frontal facial images while weakening interference in the by linear transformation and singular value decomposition. We present the mathematical features and some odds to reveal the feasible and robust measure mechanism of TSM. The performance of the TSM method, combined with the nearest neighbor rule, is evaluated in under different challenges. Experimental results clearly show the advantages of the TSM method in terms of accuracy and robustness.
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Modeling of oil near-infrared spectroscopy based on similarity and transfer learning algorithm

Yifei Wang, Kai Wang, Zhao Zhou, Wenli Du

《化学科学与工程前沿（英文）》 2019年 第13卷 第3期   页码 599-607 doi: 10.1007/s11705-019-1807-2

摘要： Near-infrared spectroscopy mainly reflects the frequency-doubled and total-frequency absorption information of hydrogen-containing groups (O‒H, C‒H, N‒H, S‒H) in organic molecules for near-infrared lights with different wavelengths, so it is applicable to testing of most raw materials and products in the field of petrochemicals. However, the modeling process needs to collect a large number of laboratory analysis data. There are many oil sources in China, and oil properties change frequently. Modeling of each raw material is not only unfeasible but also will affect its engineering application efficiency. In order to achieve rapid modeling of near-infrared spectroscopy and based on historical data of different crude oils under different detection conditions, this paper discusses about the feasibility of the application of transfer learning algorithm and makes it possible that transfer learning can assist in rapid modeling using certain historical data under similar distributions under a small quantity of new data. In consideration of the requirement of transfer learning for certain similarity of different datasets, a transfer learning method based on local similarity feature selection is proposed. The simulation verification of spectral data of 13 crude oils measured by three different probe detection methods is performed. The effectiveness and application scope of the transfer modeling method under different similarity conditions are analyzed.

关键词： near-infrared spectroscopy     transfer learning     similarity     modeling    

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Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

《机械工程前沿（英文）》 2021年 第16卷 第4期   页码 829-839 doi: 10.1007/s11465-021-0652-4

摘要： Existing fault diagnosis methods usually assume that there are balanced training data for every machine health state. However, the collection of fault signals is very difficult and expensive, resulting in the problem of imbalanced training dataset. It will degrade the performance of fault diagnosis methods significantly. To address this problem, an imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning is proposed in this paper. Unsupervised autoencoder is firstly used to compress every monitoring signal into a low-dimensional vector as the node attribute in the SuperGraph. And the edge connections in the graph depend on the relationship between signals. On the basis, graph convolution is performed on the constructed SuperGraph to achieve imbalanced training dataset fault diagnosis for rotating machinery. Comprehensive experiments are conducted on a benchmarking publicized dataset and a practical experimental platform, and the results show that the proposed method can effectively achieve rotating machinery fault diagnosis towards imbalanced training dataset through graph feature learning.

关键词： imbalanced fault diagnosis     graph feature learning     rotating machinery     autoencoder    

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Chemically reactive solute transfer in a boundary layer slip flow along a stretching cylinder

Swati Mukhopadhyay

《化学科学与工程前沿（英文）》 2011年 第5卷 第3期   页码 385-391 doi: 10.1007/s11705-011-1101-4

摘要： This paper presents the distribution of a solute undergoing a first order chemical reaction in an axisymmetric laminar boundary layer flow along a stretching cylinder. Velocity slip condition at the boundary is used instead of no-slip condition. Similarity transformations are used to convert the partial differential equations corresponding to momentum and concentration into highly nonlinear ordinary differential equations. Numerical solutions of these equations are obtained by the shooting method. The velocity decreases with increasing slip parameter. The skin friction as well as the mass transfer rate at the surface is larger for a cylinder than for a flat plate.

关键词： boundary layer     stretching cylinder     partial slip     mass transfer     similarity solution    

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Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective

《机械工程前沿（英文）》 2023年 第18卷 第2期 doi: 10.1007/s11465-022-0737-8

摘要： Selective laser melting (SLM) is a unique additive manufacturing (AM) category that can be used to manufacture mechanical parts. It has been widely used in aerospace and automotive using metal or alloy powder. The build orientation is crucial in AM because it affects the as-built part, including its part accuracy, surface roughness, support structure, and build time and cost. A mechanical part is usually composed of multiple surface features. The surface features carry the production and design knowledge, which can be utilized in SLM fabrication. This study proposes a method to determine the build orientation of multi-feature mechanical parts (MFMPs) in SLM. First, the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives. Second, the estimation models of involved optimization objectives are established, and a set of alternative build orientations (ABOs) is further obtained by many-objective optimization. Lastly, a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs. The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process. Two case studies are reported to validate the proposed method with numerical results, and the effectiveness comparison is presented. Physical manufacturing is conducted to prove the performance of the proposed method. The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82, 10.84, and 10.62 μm, respectively. The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.

关键词： selective laser melting (SLM)     build orientation determination     multi-feature mechanical part (MFMP)     fuzzy analytical hierarchy process     multi-objective decision making (MODM)    

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A dynamic procedure based on the scale-similarity hypotheses for large-eddy simulation

ZHOU Bing, CUI Guixiang, CHEN Naixiang

《能源前沿（英文）》 2007年 第1卷 第4期   页码 468-472 doi: 10.1007/s11708-007-0069-z

摘要： Current dynamic procedures in large-eddy simulation treat the two subgrid-scale stresses in the Germano identity with the same subgrid base model. Thus to get the base model coefficient, the coefficient must be assumed to be consta

关键词： large-eddy simulation     Germano identity     coefficient     subgrid-scale    

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提升KPCA方法特征抽取效率的算法设计

徐勇,杨静宇,陆建峰

《中国工程科学》 2005年 第7卷 第10期   页码 38-42

摘要：

在PCA基础上发展出的KPCA方法能抽取样本的非线性特征分量。然而, 基于KPCA的特征抽取需计算所有训练样本与待抽取特征的样本间的核函数, 因此, 训练集的大小制约着特征抽取的效率。为了提高效率，假设特征空间中变换轴可由一部分训练样本(节点)线性表出，并设计了改进的KPCA算法(IKPCA)。该算法抽取某样本特征时，只需计算该样本与节点间的核函数即可。实验结果显示，IKPCA在对应较好性能的同时，具有明显的效率上的优势。

关键词： KPCA     IKPCA     特征抽取     特征空间    

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composition differences between processed protein from different animal species by self-organizing feature

Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN

《农业科学与工程前沿（英文）》 2016年 第3卷 第2期   页码 171-179 doi: 10.15302/J-FASE-2016095

摘要： Amino acids are the dominant organic components of processed animal proteins, however there has been limited investigation of differences in their composition between various protein sources. Information on these differences will not only be helpful for their further utilization but also provide fundamental information for developing species-specific identification methods. In this study, self-organizing feature maps (SOFM) were used to visualize amino acid composition of fish meal, and meat and bone meal (MBM) produced from poultry, ruminants and swine. SOFM display the similarities and differences in amino acid composition between protein sources and effectively improve data transparency. Amino acid composition was shown to be useful for distinguishing fish meal from MBM due to their large concentration differences between glycine, lysine and proline. However, the amino acid composition of the three MBMs was quite similar. The SOFM results were consistent with those obtained by analysis of variance and principal component analysis but more straightforward. SOFM was shown to have a robust sample linkage capacity and to be able to act as a powerful means to link different sample for further data mining.

关键词： self-organizing feature maps     visualization     processed animal proteins (PAPs)     amino acid    

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Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

《机械工程前沿（英文）》 2017年 第12卷 第3期   页码 406-419 doi: 10.1007/s11465-017-0419-0

摘要：

Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.

关键词： wind turbine     planet gear fault     feature extraction     spectral kurtosis     time wavelet energy spectrum    

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Speech emotion recognitionwith unsupervised feature learning

Zheng-wei HUANG,Wen-tao XUE,Qi-rong MAO

《信息与电子工程前沿（英文）》 2015年 第16卷 第5期   页码 358-366 doi: 10.1631/FITEE.1400323

摘要： Emotion-based features are critical for achieving high performance in a speech emotion recognition (SER) system. In general, it is difficult to develop these features due to the ambiguity of the ground-truth. In this paper, we apply several unsupervised feature learning algorithms (including -means clustering, the sparse auto-encoder, and sparse restricted Boltzmann machines), which have promise for learning task-related features by using unlabeled data, to speech emotion recognition. We then evaluate the performance of the proposed approach and present a detailed analysis of the effect of two important factors in the model setup, the content window size and the number of hidden layer nodes. Experimental results show that larger content windows and more hidden nodes contribute to higher performance. We also show that the two-layer network cannot explicitly improve performance compared to a single-layer network.

关键词： Speech emotion recognition     Unsupervised feature learning     Neural network     Affect computing    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

《能源前沿（英文）》 2023年 第17卷 第4期   页码 527-544 doi: 10.1007/s11708-023-0880-x

摘要： Intelligent power systems can improve operational efficiency by installing a large number of sensors. Data-based methods of supervised learning have gained popularity because of available Big Data and computing resources. However, the common paradigm of the loss function in supervised learning requires large amounts of labeled data and cannot process unlabeled data. The scarcity of fault data and a large amount of normal data in practical use pose great challenges to fault detection algorithms. Moreover, sensor data faults in power systems are dynamically changing and pose another challenge. Therefore, a fault detection method based on self-supervised feature learning was proposed to address the above two challenges. First, self-supervised learning was employed to extract features under various working conditions only using large amounts of normal data. The self-supervised representation learning uses a sequence-based Triplet Loss. The extracted features of large amounts of normal data are then fed into a unary classifier. The proposed method is validated on exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faults. A comprehensive comparison study was also conducted with various feature extractors and unary classifiers. The results show that the proposed method can achieve a relatively high recall for all kinds of typical faults. The model can detect progressive faults very quickly and achieve improved results for comparison without feature extractors in terms of F1 score.

关键词： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear time series    

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标题 作者 时间 类型 操作

Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

期刊论文

一种面向软件缺陷预测的相似性度量特征选择方法

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

期刊论文

New approach for distinguishing the similarity of links

XIANG Jianyun, GE Maozhong, WANG Zhiping

期刊论文

Case modifying of high-speed cutting database based on CSP and similarity theory

Kejun XIANG, Zhanqiang LIU, Xing AI

期刊论文

Subspace transform induced robust similarity measure for facial images

Jian Zhang, Heng Zhang, Li-ling Bo, Hong-ran Li, Shuai Xu, Dong-qing Yuan,zhangjian@jou.edu.cn,zhangheng@jou.edu.cn

期刊论文

Modeling of oil near-infrared spectroscopy based on similarity and transfer learning algorithm

Yifei Wang, Kai Wang, Zhao Zhou, Wenli Du

期刊论文

Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

期刊论文

Chemically reactive solute transfer in a boundary layer slip flow along a stretching cylinder

Swati Mukhopadhyay

期刊论文

Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective

期刊论文

A dynamic procedure based on the scale-similarity hypotheses for large-eddy simulation

ZHOU Bing, CUI Guixiang, CHEN Naixiang

期刊论文

提升KPCA方法特征抽取效率的算法设计

徐勇,杨静宇,陆建峰

期刊论文

composition differences between processed protein from different animal species by self-organizing feature

Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN

期刊论文

Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

期刊论文

Speech emotion recognitionwith unsupervised feature learning

Zheng-wei HUANG,Wen-tao XUE,Qi-rong MAO

期刊论文

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

期刊论文