Shandong University

Qi Zhang

Chenghui Zhang

Bin Duan

Yunlong Shang

Weimin Cheng

Gang Zhou

Wen Nie

Naxin Cui

Zhongkai Zhou

Mao Xu

Chunjin Zhang

Yanzhao Ren

Da Li

Tao Fan

Luyu Dong

Cong Chen

Ruonan Bai

Jiao Xue

Shujuan Ji

Han Qiu

A multi-fault diagnosis method has the following steps: measuring cell voltages of a battery pack to be diagnosed; constructing a cell voltage sequence according to measured cell voltages of the battery pack to be diagnosed, and calculating a sample entropy value of the cell voltage sequence; setting a correction coefficient for representing voltage fluctuation information, and correcting the sample entropy value through the correction coefficient to obtain a corrected sample entropy value; and judging and outputting a fault type of the battery pack to be diagnosed according to a numerical value change of the corrected sample entropy value. Faults of cells can be accurately diagnosed without a model, sample entropy values under different faults can be distinguished by setting the correction coefficient, the intuitiveness and efficiency of fault detection are improved, and the fault type and time of the lithium-ion cells can be quickly, accurately and stably diagnosed and predicted.

Multi-fault diagnosis method and system for battery packs based on corrected sample entropy

A fractional-order KiBaM battery model considering nonlinear capacity characteristics and a parameter identification method includes a temporary capacity portion and an available capacity portion for describing nonlinear capacity characteristics of a battery, wherein the temporary capacity portion represents the power that can be directly obtained during the discharge, indicating the state of charge (SOC) of the battery; the available capacity portion represents the power that cannot be directly obtained, and such two portions are connected; when the battery is discharged, the load current i flows out from the temporary capacity portion, and a power passing rate coefficient of such capacity portions is obtained; and the nonlinear capacity effect and recovery effect of the battery are denoted by the height ratio of the temporary capacity and available capacity portions in view of the magnitude of the fractional order of battery capacity characteristics.

Fractional-order KiBaM battery model considering nonlinear capacity characteristics and parameter identification method

An on-line quantitative evaluation method for the stability of a welding process includes the steps of monitoring and acquiring the arc voltage U and the welding current I during the welding process, and drawing a phase diagram of each U-I cycle; converting the phase diagram of each U-I cycle into a binary image K; obtaining an area Jthrough which a dynamic working curve passes in the binary image K; obtaining a welding process stability evaluation index P according to the formula (1), where Jis the area of a U-I curve, N is the number of cycles passed, L is the total number of samples in N cycles, and P is the repetition rate of the i-th U-I cycle and other cycles (i=1 . . . N); and evaluating the stability of the welding process according to the obtained welding stability evaluation index P.

On-line quantitative evaluation method for stability of welding process

Provided is a method for detecting deceptive e-commerce reviews based on a sentiment-topic joint probability, which belongs to the fields of natural language processing, data mining and machine learning. In the data of different fields, a STM model is superior to other reference models; compared with other models, the STM model belongs to a completely un-supervised (no label information) statistic learning method and shows great advantages in processing unbalanced large sample dataset. Thus, the STM model is more suitable for application in a real e-commerce environment.

Method for detecting deceptive e-commerce reviews based on sentiment-topic joint probability

A multi-nozzle combined atomizing dust suppression experimental equipment under the effect of airflow disturbance includes a simulated roadway device, water spray based dust suppression device and nozzle position adjustor. The simulated roadway device includes an inlet portion, front divergent portion, simulated roadway body, rear convergent portion and outlet portion. The water spray based dust suppression device includes a dust generation and extraction system and spraying system. The dust generation and extraction system includes a dust generation device, exhaust air duct, exhaust fan and outlet air duct while the spraying system includes a water tank, high pressure water pump, confined water pipe, pressure water flow converter and multiple nozzles. The nozzle position adjustor includes a nozzle slide, slide fixing rod, nozzle sliding rack and electrically-controlled drive system which controls the change of horizontal position and vertical position of the nozzles.

Type of multi-nozzle combined atomizing dust suppression experimental equipment under the effect of airflow disturbance

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Jinan, China

Qi Zhang