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公开(公告)号：US12174715B2
公开(公告)日：2024-12-24
申请号：US17797133
申请日：2021-10-27
Applicant: Hefei University of Technology
Inventor： Qiang Zhang , Ting Huang , Shanlin Yang , Xianghong Hu , Chunhui Wang , Yuanhang Wang , Xiaojian Ding
IPC: G06F11/22
Abstract: A deep learning fault diagnosis method includes the following steps: a fault diagnosis data set X is processed based on sliding window processing, to obtain a picture-like sample data set {tilde over (X)}, and obtain an attention matrix A of the picture-like sample data set {tilde over (X)}; and a 2D-CNN model is constructed to process the picture-like sample data set {tilde over (X)} to obtain a corresponding feature map F, and in the meantime, the feature map F is processed based on channel-oriented average pooling and channel-oriented maximum pooling to obtain an output P1 of the average pooling and an output P2 of the maximum pooling, and a weight matrix W is obtained based on the attention matrix A, the output P1 of the average pooling, and the output P2 of the maximum pooling, so that an output of the model is a feature map {tilde over (F)} based on an attention mechanism, where {tilde over (F)}=WF.
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Patent Agency Ranking
公开(公告)号：US10571871B2
公开(公告)日：2020-02-25
申请号：US16056045
申请日：2018-08-06
Applicant: Hefei University of Technology
Inventor： Qiang Zhang , Shanlin Yang , Zhanglin Peng , Jun Pei , Xiaonong Lu
Abstract: The present invention discloses an automatic loading system and method for service functions of a hydraulic machine. The loading system includes an acquiring portion for acquiring i service function component chains of a hydraulic machine, a determining portion for determining a demand sequence of the service function component chains used by a user within each preset time period in a measuring cycle based on the acquired service function component chains and a deciding portion for automatically loading a service function of the hydraulic machine in a next moment according to the demand sequence based on a current input operation command of the user. By adopting the automatic loading system or method provided by the present invention, response speed of intelligent services of the hydraulic machine can be improved.
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3.发明授权公开(公告)号：US10124675B2
公开(公告)日：2018-11-13
申请号：US15794989
申请日：2017-10-26
Applicant: Hefei University of Technology
Inventor： Xiaonong Lu , Qiang Zhang , Wanying Wang , Anning Wang , Shanlin Yang , Minglun Ren , Zhanglin Peng
Abstract: The present invention relates to a method and device for on-line prediction of remaining driving mileage of an electric vehicle. The method comprises: acquiring in-transit data and driving environment data of the electric vehicle which is driving; calculating the power consumption per mileage of the electric vehicle in the current case by using the in-transit data and the driving environment data in combination with a power consumption rate data model; predicting the remaining driving mileage of the electric vehicle based on the power consumption per mileage. The device provided by the present invention is implemented on the basis of the method above. The prediction result of the present invention is more accurate, to avoid the problem that the power is exhausted due to exceeding the mileage expected by a user so that the electric vehicle cannot continue to drive, thereby improving the driving experience of the user.
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公开(公告)号：US20240184678A1
公开(公告)日：2024-06-06
申请号：US17797133
申请日：2021-10-27
Applicant: Hefei University of Technology
Inventor： Qiang Zhang , Ting Huang , Shanlin Yang , Xianghong Hu , Chunhui Wang , Yuanhang Wang , Xiaojian Ding
IPC: G06F11/22
CPC classification number: G06F11/2263
Abstract: A deep learning fault diagnosis method includes the following steps: a fault diagnosis data set X is processed based on sliding window processing, to obtain a picture-like sample data set {tilde over (X)}, and obtain an attention matrix A of the picture-like sample data set {tilde over (X)}; and a 2D-CNN model is constructed to process the picture-like sample data set {tilde over (X)} to obtain a corresponding feature map F, and in the meantime, the feature map F is processed based on channel-oriented average pooling and channel-oriented maximum pooling to obtain an output P1 of the average pooling and an output P2 of the maximum pooling, and a weight matrix W is obtained based on the attention matrix A, the output P1 of the average pooling, and the output P2 of the maximum pooling, so that an output of the model is a feature map {tilde over (F)} based on an attention mechanism, where {tilde over (F)}=WF.
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公开(公告)号：US10402404B2
公开(公告)日：2019-09-03
申请号：US16127337
申请日：2018-09-11
Applicant: Hefei University of Technology
Inventor： Jun Pei , Wenjuan Fan , Xinbao Liu , Qiang Zhang , Min Kong , Shaojun Lu
IPC: G06F17/30 , G06F16/2453 , G06F9/48
Abstract: The present invention discloses a scheduling method and system based on a hybrid variable neighborhood search and gravitational search algorithm. The method includes: 1 setting parameters of the algorithm; 2 initializing an initial solution of the algorithm; 3 performing local search based on a gravitational search algorithm (GSA); 4 updating the initial solution; 5 determining whether an algorithm termination condition is satisfied; if yes, outputting the global optimal solution searched for by the algorithm, otherwise, returning to the step 3. According to the present invention, a near-optimal solution for the continuous batch processing problem based on position learning effect and linear starting time can be obtained, so that an enterprise can make full use of production resources thereof to the utmost extent, and thus reduce production costs and improve the enterprise service level and the customer satisfaction level.
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公开(公告)号：US10318931B2
公开(公告)日：2019-06-11
申请号：US16137558
申请日：2018-09-21
Applicant: Hefei University of Technology
Inventor： Qiang Zhang , Wanying Wang , Zhanglin Peng , Xiaonong Lu , Jun Pei , Yu Fan , Jianwen Yan
Abstract: The present invention discloses a method and system for determining a maintenance policy of a complex forming device. The method and system include: establishing a performance judgement standard; obtaining actual operation data; and determining a performance stage of the complex forming device, and determining the maintenance policy of the complex forming device. The establishing a performance judgement standard includes allocating data located at different performance stages to corresponding working condition units; setting data located at a normal performance stage to normal reference data, and calculating, by using a shortest path algorithm, distances between operation data of different working condition units in different functional modules and the normal reference data, to obtain performance statuses of the different functional modules. In view of this, by using the method and system provided in the present invention, a suitable maintenance policy can be selected for the complex forming device, thereby reducing maintenance costs.
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