Beijing University of Chemical Tehcnology

Baidu Online Network Technology (beijing) Co., Ltd.

Jinjie Zhang

Zhiwei Mao

Zhinong Jiang

Xudong Zhang

Yao M Wang

Kun Chang

Haipeng Zhao

The present disclosure relates to a fault diagnosis method of a reciprocating machinery based on a keyphasor-free complete-cycle signal. The method includes the following steps: 1) building a complete-cycle vibration signal image library; 2) training an image recognition model; 3) acquiring a complete-cycle data on a keyphasor-free basis; 4) building an automatic feature extraction model; and 5) inputting a hidden layer feature of an autoencoder into a support vector machine (SVM) classifier to obtain a diagnosis result. By using a deep cascade convolutional neural network (CNN), the present disclosure achieves the goal of complete-cycle data acquisition on a keyphasor-free basis, solves the problems that traditional intelligent fault diagnosis relies on a keyphasor signal and real-time diagnosis fails due to insufficient installation space. In addition, by using an autoencoder for automatic feature extraction, the present disclosure avoids manual feature selection, reduces labor costs.

Fault diagnosis method of reciprocating machinery based on keyphasor-free complete-cycle signal

A load identification method for reciprocating machinery based on information entropy and envelope features of an axis trajectory of a piston rod. According to the present disclosure, firstly, the position of an axial center is calculated according to a triangle similarity theorem to obtain an axial center distribution; secondly, features are extracted from the axial center distribution of the piston rod by means of an improved envelope method for discrete points as well as an information entropy evaluation method; thirdly, a dimensionality reduction is carried out on the features by means of manifold learning to form a set of sensitive features of the load; and finally, a neural network is trained to obtain a load identification classifier to fulfill automatic identification on the operating load of the reciprocating machinery. The advantages of the present disclosure are verified by means of actual data of a piston rod of a reciprocating compressor.

Load identification method for reciprocating machinery based on information entropy and envelope features of axis trajectory of piston rod

The embodiments of the present invention provide a method for pushing point of interest information, comprising: displaying an electronic map; determining a target point of interest on the electronic map; acquiring an access identification of at least one piece of description information about the target point of interest; and displaying the access identification of the at least one piece of description information about the target point of interest. The embodiments of the present invention also provide a system for pushing point of interest information. According to the technical solutions provided in the embodiments of the present invention, the efficiency of pushing point of interest information can be improved.

Method and system for pushing point of interest information

Growing community of inventors

Beijing, China

Jinjie Zhang