Journal of Northeastern University(Natural Science)

YOLOv3-ADS:A Compression Model for Deep Learning Object Detection Based on YOLOv3

SONG Xin， LI Qi， XIE Wan-jun， LI Ning

2021, 42 (5): 609-615. DOI: 10.12068/j.issn.1005-3026.2021.05.001

Abstract ( 1111 )

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Since the original YOLOv3 model takes up a large amount of storage space， more initialization dataset samples and parameters are required. A deep learning object detection compression model YOLOv3-ADS was proposed based on YOLOv3. The proposed model uses the methods of splicing and stacking for data enhancement of the fewer representative initial datasets. It introduces the DIoU loss function， and improves the accuracy of object detection. Finally， YOLOv3-ADS model was compressed by sparse training and pruning rate threshold setting， which reduces the number of redundant nodes， parameters and the required storage space. The experimental results show that， compared with the existing YOLOv3 model， the average accuracy of the proposed YOLOv3-ADS compression model is increased by about 30%， from 0.6418 to 0.8368， and the number of parameters is reduced by 96.6%， from the original 63.0MB to 2.2MB. At the same time， the storage space required by YOLOv3-ADS model is reduced by 96.5%， from 252MB to only 8.81MB.

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3D U-Net Infant Brain Tissue MR Image Segmentation Based on Attention Mechanism

WEI Ying， LEI Zhi-hao， QI Lin

2021, 42 (5): 616-623. DOI: 10.12068/j.issn.1005-3026.2021.05.002

Abstract ( 1085 )

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In the field of infant brain tissue segmentation， infant brain tissue has problems such as low contrast and uneven gray scale. These problems lead to the unsatisfied accuracy of the existing methods. A brain MRI image tissue segmentation method was proposed based on a three-dimensional U-Net network(3D U-Net)， which combines the attention mechanism module and the pyramid structure module， to better provide model information at different levels and positions. The contextual information of the image is fully applied to reduce the loss of image information. It can also mine the interdependence and feature mapping between channel mappings to improve the feature representation of specific semantics.The DICE index results of WM (white matter) and GM (gray matter) of the algorithm proposed in the Iseg2017 dataset have increased by 0.7% compared with the previous optimal results， and the CSF (cerebrospinal fluid) index is with comparability. In the evaluation of the Iseg2019 cross-dataset challenge， the segmentation results of WM， GM in DICE ratio and ASD achieved first place，while the CSF index won the second place.

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A Convolutional Neural Network Based Local Dimming Technology

ZHANG Tao， LIU Tian-wei， DU Wen-li

2021, 42 (5): 624-632. DOI: 10.12068/j.issn.1005-3026.2021.05.003

Abstract ( 728 )

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Due to the light spreading problem， pixel compensation algorithms are difficult to accurately compensate brightness according to the extracted backlight information. Besides， a single compensation curve is difficult to adapt to the complex image content， resulting in unsatisfactory image quality. In order to improve the adaptability of pixel compensation， the idea of encoding and decoding in neural network was introduced. The deep feature of image was extracted by encoding network， and it was decoded by using the information of shallow feature in decoding network. A kind of classification-regression compensation neural network (CRCNN) was proposed. The experimental results show that the pixel compensation image obtained by this network can not only improve the subjective quality of the image， but also achieve good results in contrast， peak signal-to-noise ratio and other objective indicators.

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Vacuum Rolling Cladding Technology for Heavy Thick High-Strength Al Alloy Plate

XIE Guang-ming， ZHOU Li-cheng， LUO Zong-an， WANG Guo-dong

2021, 42 (5): 633-639. DOI: 10.12068/j.issn.1005-3026.2021.05.004

Abstract ( 639 )

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In order to improve the segregation， loose， and porosity in the center region of heavy thick high-strength Al alloy plate， a rolling cladding technique was developed based on vacuum friction stir welding (FSW). The process included the surface treatment， vacuum FSW， hot-roll cladding， and heat treatment. The 7050-Al alloy blanks were welded by FSW at 0.01Pa， and then were cladding by hot rolling at 450℃ with the total reduction ratio of 75%. Subsequently， the cladding plate was subjected to the solid-solution and aging heat treatments. No any crack or porosity was observed at the cladding interface， and the original cladding interface disappeared， only remaining a few of fine and dispersed MgO particles on it. The shear strength of the cladding interface is up to 266MPa， which reaches 99% of the substrate strength， so that an excellent metallurgical bonded interface is obtained.

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Effect of Nano-Sized SiC Powder Filler on Additive Manufactured Properties of Precursor-Derived Ceramics

WANG Zhi-yong， ZHAO Yu-hui， ZHAO Ji-bin， GE Chun-hua5

2021, 42 (5): 639-645. DOI: 10.12068/j.issn.1005-3026.2021.05.005

Abstract ( 437 )

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In order to reduce the generation of cracks and pores during the pyrolysis process of precursor-derived ceramics， the effects of the inert filler of nano-sized SiC powders on the precursor polymer， precursor-derived ceramics volume shrinkage， ceramic yield were studied. The features of precursor-derived ceramics with different mass fractions of SiC filler were examined by TGA， FT-IR and XRD technologies， and the volume shrinkage of the ceramics was measured by drainage method. The results showed that with the increasing mass fraction of SiC powders， the volume shrinkage of the precursor-derived ceramics decreased， while the yield of the ceramics increased. When the mass fraction was 3%， the volume shrinkage rate of the ceramics was down to the minimum value of 73.47% and the yield was up to the maximum one of 26.42%. During the pyrolysis process， when the heating rate was 4℃/min， the surface of the precursor-derived ceramics was flat and smooth without evident cracks. Therefore， the inert filler of the nano-sized SiC powders has great effects on reducing the volume shrinkage of precursor-derived ceramics and increasing the ceramic yield.

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Microstructure Behaviors of Phosphorus in Converter Slag

ZHANG Rui， JIA Ji-xiang， LIU Cheng-jun， MIN Yi

2021, 42 (5): 646-651. DOI: 10.12068/j.issn.1005-3026.2021.05.006

Abstract ( 592 )

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To design a reasonal composition of converter slag and achieve a satisfactory dephosphorization ratio， the structures of CaO-SiO₂-Fe_○xO-P₂O₅ molten slags were examined by Raman spectroscopy， and the existence form and transformation behavior of phosphorus were further analyzed in terms of the variation of slag composition during the process of basic oxygen steelmaking. The results show that phosphorus in molten slags mainly exists in the forms of Q⁰(P)， Q¹(P) and Q²(P). Meanwhile， phosphorus can enter the silica tetrahedron and ferrite tetrahedron， and occupy the locations of silicon and iron to form the Si—O—P and Fe—O—P bonds， respectively. With the increasing total content of CaO and FeO， the molar fractions of the Q⁰(P)， Q¹(P)， Q⁰(Si) and Q¹(Si) with lower-degree polymerization increase， while the molar fractions of Q²(P)， Q²(Si) and Q³(Si) with higher-degree one decrease. In addition， Si—O—P and Fe—O—P bonds also gradually decrease. The Si—O—P and Fe—O—P bonds disappear， when the basicity of molten slag was 2.83.

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Prediction Model of Al₂O₃ Activity in CaO-SiO₂-Al₂O₃-MgO Quaternary Slag System

GUO Yong-chun， ZHENG Hai-yan， HU Xin-guang， SHENG Feng-man

2021, 42 (5): 652-657. DOI: 10.12068/j.issn.1005-3026.2021.05.007

Abstract ( 531 )

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Since the activity of each component of the blast furnace slag has great effects on blast furnace smelting and product quality， a model was built to predict Al₂O₃ activity in CaO-SiO₂-Al₂O₃-MgO quaternary slag system， based on the molecule and ion coexistence theory. After the prediction model was validated by the experimental results， the effects of the R(w(CaO)/w(SiO₂))，w(MgO)/w(Al₂O₃) and w(Al₂O₃) on Al₂O₃ activity were explored. The results indicate that the model can predict the Al₂O₃ activity of molten slag accurately. When the w(Al₂O₃) was 20% and w(MgO)/w(Al₂O₃) was 0.40， the Al₂O₃ activity decreased with the increasing R. When the w(Al₂O₃) was 20% and R was 1.25， the Al₂O₃ activity decreased with the increasing w(MgO)/w(Al₂O₃). With the R=1.25 and w(MgO)/w(Al₂O₃) =0.40， the Al₂O₃ activity increased with the increasing w(Al₂O₃).

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Time-Dependent Reliability Algorithm Based on Kriging and Monte Carlo

CAO Ru-nan， SUN Zhi-li， GUO Fan-yi， WANG Jian

2021, 42 (5): 658-664. DOI: 10.12068/j.issn.1005-3026.2021.05.008

Abstract ( 521 )

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The first outcrossing method can get the change of failure probability with time， but the calculation is complex and may call for more cost. The quasi-static method requires a smaller amount of calculation， but it can only get the failure probability value corresponding to a given period of time， and cannot obtain its change trend.In view of the above problems， AK-MCS-T， a time-dependent reliability analysis method is proposed by combining the Kriging model and the Monte Carlo method. It not only has the advantage of small calculation amount of the quasi-static method， but also can give the change of failure probability with time. AK-MCS-T proposes a new selection criterion for the Kriging model which not only considers the probability of wrong judgment of response evaluation value based on the Kriging model at a sample point， but also considers the probability density corresponding to this sample point. At the same time， a new learning stopping condition is proposed to ensure the accuracy of AK-MCS-T. Finally， the effectiveness and accuracy of the new method are proved by two examples: acorroded beam structure and a cantilever tube structure.

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Bearing Remaining Useful Life Prediction Method Based on Transfer Learning

WANG Xin-gang， HAN Kai-zhong， WANG Chao， LI Lin

2021, 42 (5): 665-672. DOI: 10.12068/j.issn.1005-3026.2021.05.009

Abstract ( 1273 )

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To address the problem that most bearing remaining useful life (RUL) prediction methods based on artificial intelligence cannot well predict bearing RUL under different working conditions， a transfer learning method was proposed to predict bearing RUL under different working conditions. Fourier transform was applied to the raw vibration signals of the bearing to obtain the frequency-domain signals， and convolutional neural network (CNN) and long short-term memory network(LSTM) were used to extract the features between data of the bearing′s frequency-domain signals and mine temporal information. The method of combining global and local domain adaption was adopted to reduce the distribution differences of the bearing data under different working conditions. The effectiveness of the method was verified by the existing bearing data. Compared with the traditional deep learning models， the proposed method improves the accuracy of bearing RUL prediction under different working conditions.

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Bearing Fault Detection Based on Improved CYCBD Method

LUO Zhong， XU Di， LI Lei， MA Hui

2021, 42 (5): 673-678. DOI: 10.12068/j.issn.1005-3026.2021.05.010

Abstract ( 635 )

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Aiming at the problem that it is difficult to extract the fault features of the main shaft bearing of turboshaft engines， and that the background noise has a large interference， an improved second-order cyclostationary blind deconvolution (CYCBD) method is proposed to extract the fault feature frequency under strong noise background. In this method， particle swarm optimization (PSO) is used to optimize the filter length parameters for the CYCBD method. Firstly， the signal model is established based on the vibration characteristics of the fault bearing， and then the envelope spectrum fault feature ratio (FFR) is maximized by PSO algorithm. The optimal filter length parameter is input into the CYCBD method， and the envelope spectrum of the filtered signal is analyzed to extract the fault feature frequency. Finally， the proposed method is applied to the measured signal， and the efficiency and accuracy of fault feature extraction are improved compared with the traditional envelope spectrum analysis， which verifies the effectiveness of the method proposed.

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Study on Decoupling Sliding Mode Control with RBF Network for the Interference Compensation of Seesaw System

LU Zhi-guo， WANG Shi-xiong， LIN Meng-lei

2021, 42 (5): 679-686. DOI: 10.12068/j.issn.1005-3026.2021.05.011

Abstract ( 472 )

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For a typical unstable， high-order， multi-variable， strong-coupling， nonlinear seesaw system， an adaptive decoupling sliding mode control (SMC) algorithm based on RBF network(RBF-SMC) is proposed considering the effect of the environment on the seesaw. The decoupling algorithm is used to decouple the model， and the RBF neural network is used to compensate for the interference and uncertainty of the model， which realizes the seesaw balance control under large interference with small switching gain. The algorithm is simulated in Matlab and Matlab/Adams and the results indicate that compared with the existing SMC methods， using the RBF network in an uncertain environment to learn and evaluate the external interference， modeling error， model simplification， external excitation， friction damping and so on， not only improves the anti-interference ability of the system effectively， but also reduces the switching gain of the system and realizes the balance control of the seesaw in a limited time. Through the comparison of simulation results， the validity and practicality of the proposed algorithm are proved.

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Weakly-Supervised Steel Plate Surface Defect Detection Algorithm by Integrating Multiple Level Features

HE Yu， SONG Ke-chen， ZHANG De-fu， YAN Yun-hui

2021, 42 (5): 687-692. DOI: 10.12068/j.issn.1005-3026.2021.05.012

Abstract ( 698 )

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Due to the lack of instance-level annotations， the application of deep neural network in the field of industrial surface detection is limited. In order to solve this problem， a weakly-supervised-learning-based defect detection network is proposed for the practical defect detection task of hot rolled steel plate surfaces. This network introduces the class activation mapping model， which can be used to train the model with the image-level annotations that can be obtained relatively easily， and performs the defect detection on the surface of steel plates. In order to further improve the detection accuracy and overcome the shortcomings of the class activation mapping model， the residual network with better performances is used as the backbone network for feature extraction， and the multi-level feature integration network is proposed to generate the class activation maps. In this way， the network can obtain more detail information and activate target areas more accurately. Extensive experiments have been carried out on the NEU-CLS dataset， and the results show that the proposed method can detect defects with incomplete labels， and obtain the classification error rate of 0.68% and the localization error rate of 17.75%， which are better than the other related methods.

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Reliability Sensitivity Analysis of Turning Error for Slender Shaft

DING Peng-fei， WANG Chang-li， HUANG Xian-zhen， LI Yu-xiong

2021, 42 (5): 693-699. DOI: 10.12068/j.issn.1005-3026.2021.05.013

Abstract ( 609 )

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The randomness of turning parameters will affect the diameter error. So， a reliability sensitivity analysis method for the diameter error of slender shaft is proposed. The shear zone model and geometric analysis method are used to establish the diameter error model. Kriging method is used to reconstruct the functional relationship between the machining error and the cutting parameters of slender shaft. The reliability sensitivity analysis is carried out by using the Monte Carlo method， and the influence degree of each parameter on the diameter error is evaluated. The results show that the system reliability increases with the increasing of cutting speed， tool rake angle and diameter， while it decreases with the increasing of cutting depth， cutting width， distance between tool holder and tool， and length diameter ratio of the slender shaft. The research results can provide theoretical basis for reducing the diameter error of slender shaft.

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Finite Element Simulation Analysis of Welding Deformation and Welding Residual Stress of Automobile Drive Axle Housing

ZHANG Dong-xiang， GUO Li-xin

2021, 42 (5): 700-705. DOI: 10.12068/j.issn.1005-3026.2021.05.014

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The complex temperature field and welding residual stress distribution in the welding process of automobile drive axle housing make the axle housing produce large welding deformation. A three-dimensional model of axle housing is established by CATIA， and the welding temperature field， welding residual stress and welding deformation are simulated and analyzed by Simufact Welding software. The influence of clamping conditions on the welding deformation and residual stress of axle housing is studied. The results show that the welding deformation of axle housing is mainly caused by the shrinkage and warpage of both ends of the axle housing in the direction of the welding seam， and the maximum value is 11.63mm. The residual stress of axle housing welding is mainly the axial tensile stress of the axle housing. In the cooling stage of axle housing welding， prolonging the constraint control time(600s)of the fixture on the axle housing can effectively reduce the welding deformation and residual stress of axle housing. Compared with the full free cooling(keeping the cooling control time of the fixture on axle housing for 30s)， the welding deformation of axle housing is reduced by 20%~26%.

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Construction Method of the Dynamic 3-D Geological Model Based on Shearer Cutting Path

LI Juan-li， JIANG Shuo， XIE Jia-cheng， SUN Meng-zhen

2021, 42 (5): 706-712. DOI: 10.12068/j.issn.1005-3026.2021.05.015

Abstract ( 487 )

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Given that it is difficult to construct a real-time dynamic coal seam in a virtual fully mechanized coal mining face， a method of constructing the 3-D geological model based on the walking trajectory of the shearer is proposed. The initial 3-D geological model and dynamic 3-D geological model are established， and the trajectory curve of the target coal seam is extracted， which provides the target cutting path for the shearer. Based on the actual cutting situation and future development trend of the shearer， three kinds of shearer cutting schemes are put forward， which are memory cutting， memory cutting with manual intervention and autonomous cutting. The real virtual fully mechanized coal mining face is established， the actual coal seam morphology of three schemes is constructed， and the simulation contrast experiment is carried out. The results show that the overall average error of the actual coal seam constructed by the shearer’s autonomous cutting scheme is 15.73mm， which can achieve smaller rock cutting amount and higher mining efficiency.

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Construction Mechanics of In-situ Expansion of the Intersection of Existing Tunnel Shaft and Main Tunnel

ZHAO Wen， WANG Xin， BAI Qian

2021, 42 (5): 713-719. DOI: 10.12068/j.issn.1005-3026.2021.05.016

Abstract ( 492 )

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Taking the in-situ expansion project of the Nanling Railway Tunnel as the engineering background， a vibrating wire borehole stress gauge was used to monitor the circumferential stress changes in the surrounding rock during the expansion of the tunnel. A three-dimensional finite element model of the expansion construction process at the intersection of the main tunnel and the shaft was established， after verifying the accuracy of the model by comparing the monitoring data with the model results， the change law of surrounding rock deformation and stress was studied when the full-face method was adopted for expansion. On this basis， the influence of expansion method and cyclic footage on expansion stability was analyzed. The results show that during the expansion， the circumferential stress of the surrounding rock at the arch toe and side wall of the main tunnel at the intersection shows stress release， and the shaft destroys the arching effect of the main tunnel; compared with the non-intersection points of the shaft and the main tunnel， the horizontal displacement of the tunnel increases by 47.5% after the expansion， and the vertical displacement of the tunnel increases by 29.3%. The stress of the surrounding rock of the vault changes from compressive stress to tensile stress; the second disturbance degree of surrounding rock is lower by using full-face method， and the safety of expansion can be effectively improved by reducing the cycle footage.

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Acoustic Emission Characteristics of CFST Columns Under Uniaxial Compression

KANG Yu-mei， ZHANG Nai-yuan， REN Chao， CHEN Meng

2021, 42 (5): 720-726. DOI: 10.12068/j.issn.1005-3026.2021.05.017

Abstract ( 473 )

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Based on the uniaxial compression acoustic emission (AE) test of concrete-filled steel tube (CFST) columns with different reinforcement ratio and wall thickness， the AE signal characteristics of each specimen in the whole failure process were analyzed. The test results show that the entire failure process of the specimen can be divided into four stages: elastic section， elastoplastic section， strengthening section and failure section. The change of AE characteristic parameters shows a good corresponding relationship with the failure process of the specimen. The AE cumulative energy and AE cumulative impact number rise with the load increases. The b value has experienced a slow rise， steady fluctuation， and rapid decline， reflecting the gradual expansion of the internal cracks of the specimen; through the analysis of the RA value and AF value of AE， it can be seen that the failure process of the CFST column generates both tensile and shear cracks. With the increase of load， the proportion of shear crack in failure increases gradually. The results show that the AE method can effectively monitor the damage status of CFST columns under uniaxial compression.

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Numerical Simulation of Droplet Transport in Bus

LIN Xiu-li， ZHANG Ying-ying， LIU Jing-xian

2021, 42 (5): 726-733. DOI: 10.12068/j.issn.1005-3026.2021.05.018

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Based on the numerical simulation method of computational fluid dynamics， the evaporation， sedimentation and diffusion of droplets produced by coughing when the air velocity is 0.25~2m/s and the passengers are in the front， middle and rear of the car compartment are studied. The results show that the droplets evaporate quickly after spraying. When the air inlet velocity is small， the large-particle droplets will settle rapidly， and the small-particle droplets will stay in the space for a long time and have a large influence. When the air inlet velocity is high， the large droplets stay in the space longer and spread farther， while the small droplets stay in the space for a short time. Considering comprehensively， the recommended air inlet speed of the carriage is 1m/s under the conditions of this model. When the patient is in the front of the vehicle， the droplets mainly settle on the vehicle wall， followed by the ground. When the patient is in the middle and rear of the car， the droplets mainly settle on people and seats， followed by the ground. Compared with the front and the middle， the droplets have a larger impact when the patient coughs in the back of the compartment. This study can provide guidance for the correct understanding of droplet propagation， ventilation and elimination in bus.

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Propagation Law of Dust Explosion in Double-Sided Branch Structure Pipes

LI Gang， CUI Zhen， HU Peng， NI Lei

2021, 42 (5): 734-740. DOI: 10.12068/j.issn.1005-3026.2021.05.019

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To investigate the propagation law of dust explosion in pipe network of industrial dust removal system， the experiments based on standard 1m³ dust explosion test system and self-designed double-sided branch structure pipes were conducted. The flame propagation velocity and overpressure of cornstarch explosion in pipes with double-sided branch structure were studied. The results show that the flame front propagation velocity in primary pipe shows a continuous acceleration trend with the increase of the propagation distance under three dust concentration conditions. The double-sided branch structure has a weakening effect on the flame propagation， and the decreased distance to the ignition end leads to an enhanced weakening effect.The installation positions of the branch structure will affect the overpressure in the pipe. The decreased distance to the ignition end leads to a continuous attenuation trend， while the far distance from the ignition end shows a trend of rapid decline followed by a rising and then decays slowly. The studies provide reference and practical value for the explosion prevention design of the dust removal system.

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Fracture Extension Mechanism and Water Control Significance of Fractured Reservoir

WANG Zhi-rong， SONG Pei， CHEN Ling-xia， HU Kai

2021, 42 (5): 741-747. DOI: 10.12068/j.issn.1005-3026.2021.05.020

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Aiming at geological problems such as water inrush in fractured reservoirs triggered by hydraulic fractures. Firstly， according to the principle of elastic mechanics and fracture mechanics strength criterion， based on the geometric characteristics of reservoir primary fracture and the seepage law of fracturing fluid， the calculation model of fracture initiation pressure under vertical well condition is established. Secondly， considering the damage constitutive relationship of coal reservoir， the Dougill damage factor is combined with the fracture initiation pressure formula to further establish the extension pressure calculation model. Using the classic PKN model and the nonlinear pressure drop law of the net pressure in the fracture， an improved fracture propagation model is established. The model reveals the non-linear relationship between fracture length L and fracturing time t in fractured reservoirs， showing that the extension distance of fractures increases with time， but it increases rapidly in the early stage and basically stabilizes in the later stage. The calculation results of three test wells in the Encun block of Jiaozuo in northern Henan Province are in good agreement with the microseismic data of the adjacent block， which verifies the correctness of the theoretical model and provides reliable technical support for on-site fracturing parameter control and prevention of fracture water inrush.

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Emotional Contagion， Stock Volatility and Stock Price Synchronization: Empirical Evidence from the Fund′s Heavy Warehouse Stocks

HOU Hui， NARINMandura， LIU Jian， WANG Jian

2021, 42 (5): 748-754. DOI: 10.12068/j.issn.1005-3026.2021.05.021

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Based on the principal-agent investment relationship behind fund’s heavy warehouse stocks， which uses emotional contagion indexes established on the open-ended fund flow data， the effect of emotional contagion on stock volatility and stock price synchronization is investigated at the stock level and market level in fund investment. Research finds that emotional contagion has a significant promoting effect on the volatility of heavy warehouse stocks regardless of optimism contagion or pessimism contagion. Further study shows that it has a remarkable reinforcing effect on stock synchronization. The findings explain market anomalies from a new perspective of emotional contagion among different entities in fund investment， which serves as a supplement to the behavior asset pricing theory studies. The conclusions can provide reference for investors， fund companies and market regulators.

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Spatial-Temporal Characteristics and Driving Factors for Urban Agglomeration in Harbin-Changchun and Central-Southern Liaoning Province

WANG Yu-feng， CAO Hong-jun

2021, 42 (5): 755-760. DOI: 10.12068/j.issn.1005-3026.2021.05.022

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Aiming to investigate the crucial reason of urban sprawl disorder and slow economic development in Northeast China thoroughly， as well as quantitatively reveal the path of spatial-temporal expansion and the driving factors of urban agglomeration， such model indexes as urban expansion hotspots and driving forces with 172 districts and counties in the city cluster of Harbin， Changchun and central-southern Liaoning Province were constructed based on DMSP， VIIRS night images， and urban statistics data. The results indicated that the expansion of urban agglomeration reaches its peak during 2005—2009 and continues to decline after the peak， and the resources of central cities are concentrated while the development of sub-central cities is weak. Centripetal agglomeration centering around Harbin， Changchun， and the economic belt of central-southern Liaoning Province reflects the overall performance of urban agglomeration， with the western and southern areas expanding faster than the eastern and northern areas. The primary/secondary industries， population， and GDP are the main driving factors of urban agglomeration. From the perspective of spatial-temporal trend， industrial structure adjustment， population loss and weakening growth are the main influencing factors of the changes on urban agglomeration. The results of this research can provide reference for the future development planning of the city cluster of Harbin， Changchun and central-southern Liaoning Province.

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