124 results about "Affinity propagation" patented technology

The invention discloses a clustering analysis-based intelligent fault diagnosis method for an antifriction bearing of a mechanical system. A diagnosis model is trained firstly, comprising the following steps: collecting standard vibration signal samples of five fault and normal bearing states of an outer ring, an inner ring, a rolling body and a holding frame; decomposing signals, extracting original vibration signals as well as time domain and frequency domain characteristics of decomposed components to obtain an original characteristic set; removing redundancy by means of a self-weight algorithm and an AP (Affinity Propagation) clustering algorithm to obtain Z optimal characteristics; classifying sample statuses by means of the AP clustering algorithm to obtain a well-trained diagnosis model. A fault diagnosis is performed by the following steps: collecting real-time vibration information of a bearing, decomposing the signals, extracting the optimal characteristics determined by the model, importing the AP clustering algorithm to cluster parameters based on the diagnosis model, comparing with the Z characteristics known in the model to obtain a category of a current unknown signal, so as to complete the fault diagnosis. According to the clustering analysis-based intelligent fault diagnosis method disclosed by the invention, both EEMD (Ensemble Empirical Mode Decomposition) and WPT are utilized to decompose the vibration signals, more refined bearing status information can be acquired, the self-weight algorithm and the AP clustering algorithm increase intelligence of the diagnosis, and therefore accurate diagnosis is ensured.

Adaptive applications of affinity propagation are described to facilitate effective and computationally efficient means of clustering computer-based objects such as items of content, and / or to determine exemplars associated with a set of objects. Affinity propagation is also applied by the present invention to define system user affinity groups and / or exemplar users. The present invention applies usage behaviors as a basis for influencing clustering through methods such as initializing exemplar attractor values based on usage behaviors and / or basing similarity values between pairs of objects or users on usage behaviors associated with system objects, or usage behaviors that are associated with, directly or indirectly, specific system users.

The invention discloses a Wi-Fi-based indoor positioning navigation method. The Wi-Fi-based indoor positioning navigation method includes an acquisition stage, an online positioning stage and a navigation stage. According to the acquisition stage, RSS fingerprint information which is acquired from reference points in the same direction is clustered through an affinity propagation clustering algorithm, so that different classes and class leaders can be formed, and a fingerprint database can be established and is stored in a server. According to the online positioning stage, a handheld terminal receives the RSS fingerprint information and sends the same to the server; the server performs class matching on the received RSS fingerprint information and fingerprint information of the server; a fingerprint graph matrix is formed according to a matched class leader set and is transmitted to the handheld terminal for precise positioning; norm minimization processing and corresponding weighing are performed on rough positioning information through using an improved compressed sensing model; and the positioning of coordinates can be completed. According to the navigation stage, a shortest path is searched through utilizing a quantum cellular ant algorithm; and a position is tracked and navigated in real time through using Kalman filtering system. The Wi-Fi-based indoor positioning navigation method of the invention has the advantages of simple algorithms, small workload of affine clustering and matching, short response time and small positioning error.

The invention discloses a multi-target collaborative salient-region detection method based on similarity propagation and relates to the field of multimedia information processing and computer vision. The method includes the following steps: with respect to a plurality of image files which are input, segmenting each image into superpixels and performing pairwise measurement on inter-superpixel similarities and establishing a superpixel similarity graph model; realizing inter-image superpixel similarity matrix bipartite matching through the superpixel similarity graph model; performing superpixel graph model similarity diffusion so as to obtain a similarity graph model; and calculating a saliency map through the similarity graph model. The method performs collaborative salience detection on a plurality of targets in a plurality of images which are input so that detection precision is improved; through a parallelization similarity propagation algorithm, the operation speed is reduced and needs in practical application are met; and experiment results show that the method obtains a more accurate detection result during a shorter calculation time.

The invention discloses a tracking measurement set partitioning method for multiple extended targets based on density analysis and spectrum clustering. The method is mainly used for solving the problems that in noisy environments, the number of the multiple extended targets is unknown, a changing measurement set is difficult to partition and the calculating cost is high. The method comprises the steps of constructing a density distribution function for the measurement set by adopting a Gaussian kernel, then, selecting a density threshold according to a density histogram technology, filtering noise wave measurements out of the measurement set, constructing a noise wave measurement data set removed similarity matrix by introducing an affinity propagation technology, finally, carrying out Laplace spectrum transform on the similarity matrix, and clustering by adopting a K-mean algorithm. The method has the advantages that the measurement set of the multiple extended targets can be accurately partitioned, and the calculating cost is reduced, so that the tracking performance for the multiple extended targets is improved, and the design requirements of actual engineering systems are met.