3results about How to "Accurate classification effect" patented technology

Embodiments of the present application disclose a decision tree model generation method and a data recommendation method based on the decision tree model. The method comprises: obtaining a training data set formed by feature information of a plurality of training samples, the training samples having known category attributes; in a process of generating a decision tree model according to the training data set, iteratively calculating information gain of each feature attribute under each node, and dividing a data set contained by a current node according to a feature attribute corresponding to maximum information gain until a category attribute can be determined according to the data set contained by the node; if information gains of a plurality of feature attributes under the current node are equal and are maximum information gain, then calculating respective correction information gains of the plurality of feature attributes, and determining a feature attribute for dividing the data set contained by the current node according to the calculated correction information gains; and outputting the decision tree model formed according to the training data set. The decision tree model generated by the present application has more accurate classification effect.

The application discloses a bearing fault classification method and system based on an intelligent inspection robot, and belongs to the technical field of sensing technology and digital signal processing technology. The technical problem to be solved by the application is how to use an intelligent inspection robot to classify bearing faults according to sound, and then accurately know the bearing fault position. The technical scheme adopted is as follows: S1, collecting acoustic signals: collecting the fault sound of a bearing inner ring raceway, a bearing outer ring raceway, a bearing rolling element and a bearing assembly based on an intelligent inspection robot's collection card and microphone, and simultaneously collecting the sound information of a normal bearing working; S2, constructing a time-frequency signal: constructing a time-frequency signal to express a data-increased signal feature; S3, feature extraction: extracting features through a self-encoding network; S4, feature classification: classifying features through a convolutional neural network; and S5, optimizing classification: training and testing by using an Adam optimization algorithm, continuously adjusting the parameter settings in the network, and then obtaining more accurate classification results.

The invention aims to provide the cross-linked polyethylene cable insulation aging feature extraction and service life evaluation method, which not only can fully solve the problem of power distribution cable defect operation and maintenance in the prior art, but also can prolong the service life cycle of the power distribution cable and further reduce the intelligent degree and the operation and maintenance cost of intelligent routing inspection of the power distribution cable.