In this paper, the object detection technology based on deep learning is applied to the assembly process of space power station simulation, which can provide assistance for the attitude adjustment and navigation of th...
详细信息
In this paper, the object detection technology based on deep learning is applied to the assembly process of space power station simulation, which can provide assistance for the attitude adjustment and navigation of the aircraft through the detection of some components. Firstly, the 3 D modeling and rendering of the space power station are carried out, on which the image dataset is collected and established. Then, based on the YOLOv3 network, we improve the structure of feature *** fusing the information of shallow and deep features, we can improve the detection ability of the network for different scale *** and quantitative experimental results show that the improved YOLOv3 network can accurately and effectively detect the key components of the Space solar power station.
This paper is concerned with the stability analysis of discrete time-delay system. Firstly, an improved augmented functional form is proposed and the positive definite condition of functional is derived. Then, the for...
详细信息
This paper is concerned with the stability analysis of discrete time-delay system. Firstly, an improved augmented functional form is proposed and the positive definite condition of functional is derived. Then, the forward difference of functional is estimated by applying summation inequalities and a state-connecting-based zero-value equation. As a result, an improved stability criterion is established. Finally, a numerical example is given to show the efficiency and merit of the proposed method.
This paper is concerned with the dynamic event-triggered distributed filtering problem for a class of time-varying stochastic systems with switching nonlinearities and redundant channels. A random variable that obeys ...
详细信息
This paper is concerned with the dynamic event-triggered distributed filtering problem for a class of time-varying stochastic systems with switching nonlinearities and redundant channels. A random variable that obeys Bernoulli distribution is used to characterize the switching nonlinearities, and moreover, a set of random variables are used to described redundant channels, which are introduced to increase the probability of successful deliver of the data packets. A dynamic event-triggered scheme is introduced to further reduce the number of excessive executions of the signal transmissions. The aim of this paper is to design a locally optimal time-varying filter such that, for switching nonlinearities and redundant channels, an upper bound on the filtering error covariance is derived and such an upper bound is minimized by properly designing the filter gain based on the solution of a Riccati-like difference equation. In addition, the performance analysis of the proposed filtering algorithm is conducted and a sufficient condition is given to verify the boundedness of the filtering error. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed filter design scheme.
Compared with conventional object detection, remote sensing images are taken from the air. The angle of view is not fixed and the object direction, scale which compared with conventional object detection algorithm are...
详细信息
Compared with conventional object detection, remote sensing images are taken from the air. The angle of view is not fixed and the object direction, scale which compared with conventional object detection algorithm are quite different. These factors lead to the object detection in remote sensing images difficult. To solve the above problems, this paper proposes an improved remote sensing object detection method based on Faster-RCNN algorithm. Using online difficult example mining technology,feature pyramid structure, Soft-NMS technology, and RoI-Align technology to enhance the capabilities of Faster-RCNN in small object detection task in remote sensing images. The algorithm in this paper was evaluated on the RSOD-Dataset, compared with the original Faster-RCNN algorithm, the proposed algorithm improves the detection accuracy and training convergence speed,which shows that these improvements are of great significance to the object detection algorithm of remote sensing images.
The research area of industrial alarm monitoring and management has been attracting increasing studies in the past decade. A variety of advanced alarm management techniques have been proposed. However, the validation ...
详细信息
The research area of industrial alarm monitoring and management has been attracting increasing studies in the past decade. A variety of advanced alarm management techniques have been proposed. However, the validation of the results were mostly based on real industrial data while such data was not always accessible to all researchers. Even if obtained, the privacy policies of industrial corporations may lead to difficulty in publishing new results. Thus, there is a great demand to construct a large scale simulated alarm system and create standard alarm & event data for the test of new methods. This paper proposes the design of a simulated alarm system by extending the public model of a Vinyl Acetate Monomer(VAM) process and collects the alarm & event data through a long term alarm monitoring process. An example alarm & event dataset is created and analyzed to illustrate the usability of the simulated alarm system.
An improved method for spectral reflectance reconstruction from digital camera raw RGB responses of pixels is proposed by adaptively weighting training samples considering colorimetric and lightness similarities. The ...
详细信息
An improved method for spectral reflectance reconstruction from digital camera raw RGB responses of pixels is proposed by adaptively weighting training samples considering colorimetric and lightness similarities. The proposed method was based on an adaptive local weighted linear regression model by using a Gaussian function in weighting matrix *** novelty of our method is designing the weighting matrix combining colorimetric and lightness similarities. The proposed method was tested using two different standard color charts, with a simulated digital camera based on the camera spectral sensitivity. Experimental results indicate that the proposed method exhibits considerable improvements in terms of the spectral reflectance and the colorimetric values in comparison with existing methods.
This paper is concerned with the problem of asymptotical synchronization of chaotic Lur’e systemscontrolled via PD controller with time-varying delay. Firstly, a new Lyapunov-Krasovskii functional(LKF) with more i...
详细信息
This paper is concerned with the problem of asymptotical synchronization of chaotic Lur’e systemscontrolled via PD controller with time-varying delay. Firstly, a new Lyapunov-Krasovskii functional(LKF) with more information of time-varying delay is constructed. Then, by applying the Wirtinger-based integral inequality and the extended reciprocally convex combination lemma(RCCL), a new synchronization criterion for time-varying delay is obtained, and a less conservatism corollary for the constant delay is established by weakening some terms of LKF. Finally, a numerical example is given to show the better performance of the proposed criteria.
This paper studies the dissipative problem of neural networks with time-varying delay and external disturbance. A suitable augmented Lyapunov-Krasovskii functional(LKF) is constructed by taking full advantage of the d...
详细信息
This paper studies the dissipative problem of neural networks with time-varying delay and external disturbance. A suitable augmented Lyapunov-Krasovskii functional(LKF) is constructed by taking full advantage of the delay information of the system and the conditions of the excitation function. Then by employing auxiliary function inequalities, the reciprocally convex combination and a vector zero-value method to deal with the derivative of the LKF, a less conservative delay-dependent dissipative criterion is obtained. Finally, a numerical example is given to show the effectiveness of this criterion.
In the industrial field, compound faults often occur on rolling bearings and it's difficult to diagnose them correctly. To solve this problem, this article proposes a CNN-ELM compound fault diagnosis method based ...
详细信息
ISBN:
(数字)9781728162461
ISBN:
(纸本)9781665419352
In the industrial field, compound faults often occur on rolling bearings and it's difficult to diagnose them correctly. To solve this problem, this article proposes a CNN-ELM compound fault diagnosis method based on joint distribution modification. Firstly, considering the complementarity and coupling of data from multiple sensors, a data input trick of multi-sensor data connected in parallel is designed. Secondly, due to the discrepancy of distribution between the compound fault data features and the single fault data features, the marginal distribution matrix and the posterior distribution matrix are used to modify the CNN-ELM network, so that the network can extract more reliable data features for fault diagnosis. Finally, referring to the categories and criteria of bearing damage proposed by Paderborn University, the label code is defined. The corresponding data set is used to verify the proposed algorithm. Experimental results show that the algorithm can accurately obtain detailed fault information such as fault location, fault type, and fault severity.
Feature extraction and matching of images is a key step in 3D reconstruction, and its accuracy directly affects the accuracy of 3D reconstruction. In this paper, aiming at the mismatch caused by the high similarity be...
详细信息
Feature extraction and matching of images is a key step in 3D reconstruction, and its accuracy directly affects the accuracy of 3D reconstruction. In this paper, aiming at the mismatch caused by the high similarity between screws, proposes a feature matching algorithm based on median filtering, Lowes algorithm and scale-invariant feature transform(SURF), called M-L-SURF algorithm. First, the median filtering is performed on the screw image to remove noise, then the SURF algorithm is used for feature extraction and matching, and finally, the Lowe's algorithm is used to filter the matching results. The results of experiments show that the M-L-SURF algorithm can achieve a 97.4% correct rate of screw image matching. The matching results obtained in this paper can be better applied to the subsequent work of 3D reconstruction.
暂无评论