Beijing Institute of Technology

Fang Deng

Jie Chen

Yeyun Cai

Xinyu Fan

Ning Ding

Chengwei Mi

Bin Zhang

Chen Chen

Feng Gao

Qing Bo Wang

Xin Gao

Jia Zhang

Jiwei He

Wenjie Chen

Sai Lu

Bin Xin

Jiachen Zhao

Lihua Dou

Yanxin Ji

Zelang Liang

Mengjie Jing

Yingmei He

Xianghu Yue

Disclosed is a large-scale dynamic double-effect scheduling method for a flexible job shop based on genetic programming (GP). In a GP implementation process of the present disclosure, in addition to features related to workpieces, processing robots and automated guided vehicles (AGVs), such as processing time of working procedures and buffer area waiting time, features of a ratio of processing time to transfer time and a ratio of processing energy consumption to transfer energy consumption are also added in a terminal set to cause job shop environment features to be more comprehensively applied to a scheduling rule design, thereby automatically designing a more consistent and accurate scheduling rule. A double-effect scheduling rule of the present disclosure overcomes the shortcomings of slow convergence speed, difficulty in rapid corresponding changes and unfit scheduling rules, and can quickly produce a more efficient and energy-saving production scheduling scheme.

Large-scale dynamic double-effect scheduling method for flexible job shop based on genetic programming

A photovoltaic array fault diagnosis method based on composite information is provided. The method includes: collecting and preprocessing composite information data of photovoltaic array working state, including image data and text data; using the image data of photovoltaic array working state to train a pre-established fault classification model of deep convolutional neural network, to thereby obtain an image fault classification model; using the text data of photovoltaic array working state to train a pre-established fault classification model based on a support vector machine, to thereby obtain a text fault classification model; fusing the image fault classification model and the text fault classification model by logistic regression algorithm to obtain a fusion model, and training the fusion model using the composite information data of photovoltaic array working state to thereby obtain the photovoltaic array fault diagnosis model.

Photovoltaic array fault diagnosis method based on composite information

A self-powered wireless keyboard by modifying the structure of a traditional membrane keyboard having a volcanic crater structure. Not damaging the original membrane keyboard structure, a micro magnet core is installed inside a cylindrical protrusion block under the key cap as a mover of the induction power generation device, and an induction coil is wound in a key slot of the keyboard base as the stator of the induction power generation device. In this way, when each key is pressed, it will produce induction current. A layer of flexible solar cell can be laid on the upper surface of the key, which can generate electricity by collecting the light energy in the surrounding environment during the time of daily illumination.

Self-powered wireless keyboard

A mechanical energy-based self-powering counting system is provided. The system includes an electromagnetic power generator, a count measuring circuit, a count energy supply circuit, a controller and a wireless transmission module. The electromagnetic power generator is driven by an external device and produces an electric signal and outputs the electric signal to the controller after passing it through the count measuring circuit. The controller processes the received signal, updates a count according to certain programming rules and sends data to the wireless transmission module. The energy from the electromagnetic power generator flowing through the count measuring circuit can supply power to the controller. An energy storage module in the count energy supply circuit performs voltage feedback on the controller. The controller monitors the voltage of the energy storage module to control whether it enters a charging state.

Mechanical energy-based self-powering counting system

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Beijing, China

Fang Deng