Archive

15 June 2024, Volume 45 Issue 6 Previous Issue   
---
Information & Control
Materials & Metallurgy
Mechanical Engineering
Resources & Civil Engineering
Management Science


For Selected:

Download Citations EndNote Ris BibTeX

Toggle Thumbnails

Information & Control

Select

A Method for Anomaly Detection and Fault Diagnosis of Elevator Door Machine Yu-chuan FAN, Bo FAN, Zhuo CHEN, Xiao-shun ZHANG 2024, 45 (6):  761-768.  DOI: 10.12068/j.issn.1005-3026.2024.06.001 Abstract ( 792 )   HTML ( 78)   PDF (1731KB) ( 538 )   A method for anomaly detection and fault diagnosis of elevator door machine operation is proposed. Firstly， the opening and closing door curve is spearated from the operation data of the elevator door machine and divided it into 10 operating segments， and the data characteristics of each section is extracted. Secondly， an anomaly detection method based on boxplot is proposed， and the accumulated data characteristics of each running section are used for anomaly diagnosis. In order to prevent the diagnostic error caused by the data not satisfying the normal distribution， the normality test method of the feature data of the door machine is added， and the Box-Cox transformation is performed on the data that does not meet the normal distribution. Finally， the segmented feature data of the elevator door is extracted， and the extreme learning machine（ELM） is used to train the classification model for three faults： door knife jamming fault， overall resistance increase fault and synchronous belt loosening fault. Experiments have verified that the proposed anomaly detection method and fault diagnosis method have high accuracy and value of application and promotion. Figures and Tables | References | Related Articles | Metrics

Select

State Detection Algorithm of Manipulator Based on Improved YOLOv4 Lightweight Network Li-xin GUO, Su-tao BI, Ming-yang ZHAO 2024, 45 (6):  769-775.  DOI: 10.12068/j.issn.1005-3026.2024.06.002 Abstract ( 398 )   HTML ( 27)   PDF (1554KB) ( 192 )   The YOLOv4 network is difficult to be widely used in industry due to its complex structure， many parameters， and large model size. In view of this problem， an improved lightweight network based on YOLOv4 is proposed.Firstly， GhostNet is used to replace the YOLOv4 backbone network， simplifying the network structure and reducing the number of model parameters； Secondly， in order to make up for the accuracy loss caused by network simplification， Spatial Pyramid Pooling structure is added after the other two output feature layers to enhance feature extraction. Thirdly， the attention mechanism of channel， which is Squeeze and Excitation Network， is added to improve the network’s ability to extract important information. Finally， the loss function CIOU is replaced by SIOU to accelerate the convergence of the model and thus produce a better model. Experimental results show that， on the premise of meeting industrial requirements， compared with YOLOv4 network， the improved lightweight network significantly reduces the number of model parameters and the amount of computation， while improving the detection speed， at the same time， at the expense of less detection accuracy， thus proving the effectiveness of the improved algorithm in the identification and detection of the clamping state of the manipulator in the optical fiber plugging task. Figures and Tables | References | Related Articles | Metrics

Select

Research on Emotion Recognition Method of Music Multimodal Data Dong-hong HAN, Yan-ru KONG, Yi-meng ZHAN, Yuan LIU 2024, 45 (6):  776-785.  DOI: 10.12068/j.issn.1005-3026.2024.06.003 Abstract ( 511 )   HTML ( 17)   PDF (1681KB) ( 347 )   The research of music emotion recognition has broad application prospects in the fields of music intelligent recommendation and music visualization. Aiming at the problem that only using low?level audio features for emotion recognition has limited effectiveness and poor interpretability. Firstly， an emotion recognition model ERMSLM based on MIDI （musical instrument digital interface） data is constructed， which can learn the semantic information of notes. The features of this model are composed of melodic features extracted with skip?gram and LSTM（long short?term memory）， tonal features extracted by pre?trained MLP and manually constructed features. Secondly， an emotion recognition model ERMBT based on text data that integrates lyrics and social tags is constructed. The lyrics features are composed of emotional features extracted with BERT， emotional dictionary features constructed by using ANEW lists and TF-IDF features of lyrics. Finally， two multimodal fusion models of feature?level fusion and decision?level fusion are constructed based on MIDI and text data. The experimental results show that the ERMSLM and ERMBT models can achieve accuracies of 56.93% and 72.62% respectively. And the decision?level multimodal fusion model is more effective. Figures and Tables | References | Related Articles | Metrics

Select

Adaptive Graph Convolutional 3D Point Cloud Recognition Algorithm Based on Attention Mechanism Yuan MA, Li-huang SHE, Jia-wei LI, Xi-rong BAO 2024, 45 (6):  786-792.  DOI: 10.12068/j.issn.1005-3026.2024.06.004 Abstract ( 441 )   HTML ( 9)   PDF (915KB) ( 127 )   To better capture the local geometric structural information of 3D point clouds， an adaptive graph convolutional 3D point cloud recognition algorithm is proposed based on attention mechanism. To address the drawback of fixed convolutional kernels ignoring features， the algorithm first dynamically learns adaptive convolutional kernels based on graph structural features. Furthermore， to enhance the modeling capability of the model for local geometric structures， the weight distribution of the convolutional kernels using a vector attention mechanism is adjusted adaptively. Subsequently， a graph is constructed using the position features of the point cloud and perform convolution operations on the newly constructed graph structural features using the adaptive convolutional kernels. Finally， new point cloud features through pooling is obtained. Experimental results demonstrate that the proposed algorithm effectively extracts local geometric structural information and achieves higher accuracy in classification tasks even with a limited number of sampled points， outperforming previous point cloud convolutional algorithms. The proposed algorithm also exhibits certain advantages compared to existing methods for point cloud classification and segmentation， as evidenced by the performance evaluation on the ModelNet40， ScanObjectNN， and ShapeNetPart datasets. Figures and Tables | References | Related Articles | Metrics

Select

VMD Based Binary Channels Speech Feature Map Extraction Algorithm for Dysarthria Pei-yun XUE, Jing BAI, Nan ZHANG, Jian-xing ZHAO 2024, 45 (6):  793-801.  DOI: 10.12068/j.issn.1005-3026.2024.06.005 Abstract ( 295 )   HTML ( 6)   PDF (1155KB) ( 79 )   A multiscale binary channels filter banks （MBCFbank） feature extraction algorithm based on variational modal decomposition （VMD） is proposed to address the issue of poor speech recognition caused by insufficient extraction of effective feature information from speech of patients with dysarthria. Firstly， in order to better extract the acoustic features that conform to the structural characteristics of human ears， a binary?channels filter banks （BCFbank） feature extraction algorithm is proposed， which uses Mel filtering and performs logarithmic transformation， simultaneously using Gammatone filtering to perform nonlinear loudness transformation. Secondly， VMD is used to optimize the BCFbank features. Three components with higher correlation coefficients are selected from the decomposed multiple speech signal components， and their BCFbank features and differential features are extracted respectively. At the same time， BCFbank features are extracted from the undecomposed speech signals to form the MBCFbank feature map spectrum. Finally， training and recognition are conducted on a dual channel speech recognition model. The experimental results show that the speech recognition model based on BCFbank features and MBCFbank feature maps has the highest accuracy of 87.82% and 94.34%， respectively， which is superior to the recognition effect of Fbank features. Figures and Tables | References | Related Articles | Metrics

Materials & Metallurgy

Select

Effect of SiCp Particle Size Grading on the Microstructure and Properties of 55%SiCp/6061Al Composites Meng-qi WANG, Yue LIU, Chun-lin XIAO, Chun-ming LIU 2024, 45 (6):  802-807.  DOI: 10.12068/j.issn.1005-3026.2024.06.006 Abstract ( 499 )   HTML ( 11)   PDF (2462KB) ( 152 )   55%SiCp/6061Al （55% is volume fraction） composites were prepared using the vacuum hot pressing method. The effects of SiCp particle size on distribution uniformity，density and bending strength of the composites were investigated. The results showed that composites with particle size grading have a dense microstructure，uniform SiCp distribution and high interfacial bonding strength between SiCp and the 6061Al alloy matrix. The bending strength of （60+25） μm composite with a mass ratio of 4∶1 raises from 395 MPa to 548 MPa. The bending strength of （120+60+25） μm composite with a mass ratio of 1∶1∶1 is the highest，reaching 397 MPa. The double grain size grading （106+25） μm composite with a mass ratio 4∶1 exhibits excellent comprehensive properties，with density>99.00%，uniformity>90.00% and bending strength>400 MPa after heat treatment. Figures and Tables | References | Related Articles | Metrics

Select

Deformation and Bursting of Bubbles When Particles Break Through Bubbles Fei WANG, Ze YANG, Jin CHEN, Zhi-jian SU 2024, 45 (6):  808-815.  DOI: 10.12068/j.issn.1005-3026.2024.06.007 Abstract ( 423 )   HTML ( 7)   PDF (1864KB) ( 149 )   The evolution of the particle?induced hemispherical bubble bursting process is invistigated using high?speed camera filming. The edge regeneration and convection after bubble formation， the probability of bubble bursting when subjected to particle penetration， and the bubble bursting behavior after hole formation are observed and analyzed. Through dimensional analysis and experimental research， it is found that the probability of bubble breaking probability is a function of Reynolds number and Weber number. The probability is given by\text{?}P=\mathrm{1.08}\text{?}{\left(R{e}^{\mathrm{0.5}}W{e}^{\mathrm{0.25}}\right)}^{\mathrm{0.664}}， and the probability is reaches to 100% when R{e}^{\mathrm{0.5}}W{e}^{\mathrm{0.25}}>1 020. The number of ligaments formed by bubble bursting is a function of the Oh number. The rim receding velocity of the bubble liquid film increases with the concentration of the solution increases and the film thickness decreases with the concentration increases. Figures and Tables | References | Related Articles | Metrics

Select

Effect of Sintering Process on Microstructure and Mechanical Property of Porous Ti Jia-hao ZHAO, Yang QU, Hong-jie LUO, Shi-jie YANG 2024, 45 (6):  816-822.  DOI: 10.12068/j.issn.1005-3026.2024.06.008 Abstract ( 407 )   HTML ( 6)   PDF (1767KB) ( 138 )   Sintering is a critical step in the formation process of porous Ti. Porous Ti can be endowed with excellent mechanical properties by controlling sintering conditions. Porous Ti for liquid?solid filtration with a 60% space holder was manufactured using vacuum distillation sintering， which uses Mg powder and Mg particles as the space holder under different sintering conditions. The microstructure， compressive property and bending property were characterized and tested， providing a reference for the preparation and performance optimization of porous Ti. The results show that with increasing of sintering temperature and time， the pore size of porous Ti decreases， the porosity decreases， and the pore spheroidizes. When the sintering temperature is below 1 150 ℃， the axial shrinkage of porous Ti is always greater than the radial shrinkage. The yield strength and bending strength reach the maximum values of 158.60 MPa and 230.40 MPa respectively at a sintering temperature of 1 150 ℃ and a sintering time of 180 min. Figures and Tables | References | Related Articles | Metrics

Select

Raman Spectroscopy on Ionic Structure of LiF-ZrF4 Molten Salt System Hong-guang KANG, Xian-wei HU, Wan-ting ZHAO, Jiang-yu YU 2024, 45 (6):  823-828.  DOI: 10.12068/j.issn.1005-3026.2024.06.009 Abstract ( 391 )   HTML ( 8)   PDF (1379KB) ( 212 )   The Raman spectroscopy and quantum chemistry calculations were employed to analyze the ionic structure and variation rule of the LiF-ZrF4 molten salt system with the molar fraction of ZrF4 ranging from 10% to 60% at 803~1 086 K. The study identified four complex ions in the molten salts： ZrF{}_{\mathrm{5}}^{-}， ZrF{}_{\mathrm{6}}^{\mathrm{2}-}， ZrF{}_{\mathrm{7}}^{\mathrm{3}-}， and ZrF{}_{\mathrm{8}}^{\mathrm{4}-}. In the molten salts， ZrF{}_{\mathrm{7}}^{\mathrm{3}-} and ZrF{}_{\mathrm{8}}^{\mathrm{4}-} are the major components， accounting for 90%~94%， while ZrF{}_{\mathrm{5}}^{-} and ZrF{}_{\mathrm{6}}^{\mathrm{2}-} are present in lower amounts. At the initial stage of temperature increase， a reaction between ZrF{}_{\mathrm{7}}^{\mathrm{3}-} and ZrF{}_{\mathrm{6}}^{\mathrm{2}-} occurs， producing ZrF{}_{\mathrm{8}}^{\mathrm{4}-} and ZrF{}_{\mathrm{5}}^{-} （\mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{7}}^{\mathrm{3}-}+\mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{6}}^{\mathrm{2}-}\to \mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{8}}^{\mathrm{4}-}+\mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{5}}^{-}）. At a certain temperature， a reaction between ZrF{}_{\mathrm{8}}^{\mathrm{4}-} and ZrF{}_{\mathrm{6}}^{\mathrm{2}-} takes place and produces ZrF{}_{\mathrm{7}}^{\mathrm{3}-}， ZrF{}_{\mathrm{5}}^{-}， and F- （\mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{8}}^{\mathrm{4}-}+\mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{6}}^{\mathrm{2}-}\to \mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{7}}^{\mathrm{3}-}+\mathrm{Z}\mathrm{r}{\mathrm{F}}_{\mathrm{5}}^{-}+\mathrm{2}{\mathrm{F}}^{-}）. With the increase of ZrF4， the amount of ZrF{}_{\mathrm{5}}^{-} increases， while the amounts of ZrF{}_{\mathrm{6}}^{\mathrm{2}-}， ZrF{}_{\mathrm{7}}^{\mathrm{3}-}， and ZrF{}_{\mathrm{8}}^{\mathrm{4}-} decrease. Figures and Tables | References | Related Articles | Metrics

Mechanical Engineering

Select

Multi-objective Optimization Allocation of Geometric Parameter Tolerances for Serial Robots Based on NSGA-II Li-jin FANG, Yue GAO, Xin-xing CAO, Yun-peng GONG 2024, 45 (6):  829-836.  DOI: 10.12068/j.issn.1005-3026.2024.06.010 Abstract ( 508 )   HTML ( 5)   PDF (1644KB) ( 165 )   In order to improve the geometric positioning accuracy of robot end?effectors and allocate geometric parameter tolerances reasonably in the initial design stage of robot precision， a multi?objective tolerance optimization allocation method based on fast non?dominated sorting genetic algorithm （NSGA-II） with elite strategy was proposed. ROKAE XB7 6-DOF serial robot was studied， and the minimum cost single?objective tolerance optimal allocation based on genetic algorithm （GA） and NSGA-II multi?objective tolerance optimal allocation method were used to optimize the tolerance allocation of DH（Denavit?Hartenberg） parameters. In the case of the same precision design objectives and genetic algorithm parameter settings， compared with the minimum cost geometric parameter tolerance optimization allocation based on the genetic algorithm， the multi?objective optimal allocation based on NSGA-II could provide a series of optimal solutions with different manufacturing costs and different precision design requirements. The relaxation rate of tolerance is relatively high， and the result of parameter tolerance optimization is better. Figures and Tables | References | Related Articles | Metrics

Select

Development and Simulation of Constitutive Relationship of Fluorophlogopite Based on Improved JH-2 Model Lian-jie MA, Xue-qiao YU, Zhi-bin HAN, Shuai PAN 2024, 45 (6):  837-842.  DOI: 10.12068/j.issn.1005-3026.2024.06.011 Abstract ( 397 )   HTML ( 0)   PDF (1323KB) ( 117 )   Based on the JH-2 theoretical model， an improved JH-2 discrete model for the finite element simulation of brittle materials is established， which is used to redevelop the client module of DEFORM software as a constitutive model. And the cutting force of engineering ceramics is simulated and analyzed. Through the fluorophlogopite turning test， the simulation effects of the JH-2 discrete model and J-C idealized model are compared. The effects of three process parameters， namely cutting speed， feed speed and cutting depth， on the cutting force simulation are analyzed. And the accuracy and reliability of the JH-2 model are verified. The test results show that the variation trend of the simulation value of cutting force is the same as that of the test value， and the precision is good. Compared with the J-C idealized model， the machining morphology of brittle materials simulated by the JH-2 discrete model is more consistent with the actual situation. Therefore， in the finite element research of engineering ceramics， the improved JH-2 discrete model has significant advantages over the J-C model in theoretical analysis and simulation prediction. Figures and Tables | References | Related Articles | Metrics

Select

Uniaxial Mechanical Behavior of 316LN Stainless Steel Based on Crystal Plasticity Finite Element Method Xiao-hui CHEN, Tian-xiang CHEN, Lin ZHU, Lang LANG 2024, 45 (6):  843-849.  DOI: 10.12068/j.issn.1005-3026.2024.06.012 Abstract ( 266 )   HTML ( 3)   PDF (2089KB) ( 122 )   To describe the uniaxial mechanical behavior of 316LN stainless steel more accurately， a polycrystalline cyclic plasticity constitutive model is constructed based on the Ahmadzadeh-Varvani （A-V） kinematic hardening rule in the framework of the rate?dependent crystal plasticity theory. The constitutive model is implemented to the finite element software ABAQUS through the UMAT， and a two?dimensional polycrystalline finite element model is established through Voronoi diagrams. And then the deformation behavior of 316LN stainless steel is simulated under different loading rates， strain cycles and asymmetric stress cycles， respectively. The simulated results compared with the experimental data show that under the uniaxial tensile condition， the stress errors of both fluctuate around±0.9%， and the maximum stress error is only 1.9%； under the strain cycle condition， the maximum stress error between the two appears in the 5th cycle， with 11.4% and 12.2% errors in the tensile and compression phases， respectively， and 7.4% and 7.9% errors in the tensile and compression phases， respectively， after cycle stabilization. Under the asymmetric stress cycle condition， the errors of both mainly appear in the hysteresis loop width， the simulated hysteresis loop width is narrower， but the error of the hysteresis loop evolution trend is smaller. Figures and Tables | References | Related Articles | Metrics

Select

Multi-source Physiological Energy Consumption Prediction for Exoskeleton Performance Evaluation Tan LI, Hong WANG, Bo-pi JIN, Zhi-wei WU 2024, 45 (6):  850-857.  DOI: 10.12068/j.issn.1005-3026.2024.06.013 Abstract ( 408 )   HTML ( 1)   PDF (1756KB) ( 119 )   In the process of exoskeleton design， the evaluation of assistance performance directly impacts the overall structural safety and efficiency. Addressing the current issue of predominantly utilizing single metrics for performance evaluation， a method based on multi?source physiological signals （surface electromyography， photopretismography， and respiration） for LSTM prediction of motion energy consumption was proposed. This method involves preprocessing and feature extraction of physiological signals， followed by prediction using a 6?layer LSTM model and validation through K-fold cross?validation. Comparative experiments with DT and SVM were conducted. Finally， an online energy consumption monitoring system was established， serving as a basis for evaluating exoskeleton assistance performance. Results indicate the feasibility of utilizing multi?source physiological signals for fusion prediction， with an RMSE of 0.073 kJ for the three?source signal. The LSTM model achieves a 39.53% and 15.68% reduction in RMSE compared to DT and SVM， respectively. The total energy consumption error on the test set is 23.98 kJ， demonstrating the superior performance of the LSTM model for total energy consumption prediction and its suitability for exoskeleton assistance performance evaluation. Figures and Tables | References | Related Articles | Metrics

Select

Trajectory Tracking Control Method of Wheeled Mobile Robot with Uncertain Slippage Hao WU, Zhong-chao LIANG, Wen-cheng WANG, Yong-fu WANG 2024, 45 (6):  858-865.  DOI: 10.12068/j.issn.1005-3026.2024.06.014 Abstract ( 477 )   HTML ( 6)   PDF (2131KB) ( 164 )   Wheeled mobile robots are prone to wheel slippage on soft and complex terrains， which affects trajectory tracking accuracy. To improve the trajectory tracking accuracy of robots under such conditions， an adaptive slip compensation controller （ASCC） based on fault?tolerant control （FTC） is proposed. Firstly， a kinematic model of a four?wheeled mobile robot （4 WMR） is established by considering wheel slippage rates， and the corresponding trajectory tracking error model is constructed. Then， based on the FTC method， a slippage compensation term is designed. The stability of the ASCC is proven using Lyapunov stability theory， achieving accurate compensation for the velocity error caused by wheel slippage. Finally， experiments under two working conditions are conducted on the 4 WMR. The results show that the designed controller enables the mobile robot to track the desired path under unknown wheel slippage rates， and it exhibits stronger robustness and higher tracking accuracy compared to the conventional controllers. Figures and Tables | References | Related Articles | Metrics

Resources & Civil Engineering

Select

Surface Deformation Monitoring and Mining Parameters Inversion of Puhe Coal Mine Goaf Based on DS-InSAR Meng AO, Ying SUN, Lian-huan WEI, Hua-nan ZHANG 2024, 45 (6):  866-873.  DOI: 10.12068/j.issn.1005-3026.2024.06.015 Abstract ( 444 )   HTML ( 6)   PDF (2652KB) ( 205 )   Interferometic synthetic aperture radar （InSAR） technology has shown great application potential in monitoring geological disasters in mining areas. However， it is difficult for conventional time?series InSAR technology to detect enough radar targets in mining areas covered by vegetation， which causes underestimation or inaccurate estimation of deformation results. Aiming at the scarcity of measurement points in complex mining areas， the distributed scatterer InSAR analysis method can effectively increase the number of measurement points in the vegetation covered area， thereby accurately describing the temporal evolution and spatial distribution characteristics of deformation in mining areas. The long?term and high?intensity mining activities will cause the surface deformation of the goaf， posing serious threats to sustainable mining， infrastructure construction and the safety of lives and property. In order to understand the mining situation in the goaf of Puhe Coal Mine in Shenyang， based on InSAR high?precision monitoring data， the key underground mining parameters in the mine area are obtained through geophysical modeling inversion. The deformation field simulated based on the optimal parameters is consistent with the InSAR monitoring results， and the inversion mining parameters conform to the actual mining situation. Combining InSAR monitoring results with Okada model to invert mining area parameters can truly reflect the actual mining situation， accurately describe the surface deformation of goaf， and provide important information for scientific formulation of underground mining plans and sustainable development of the mining area. Figures and Tables | References | Related Articles | Metrics

Select

Compression-Shear Fracture Criterion for the Rockmass Considering T-Stress and Crack Parameter Hong-yan LIU, Feng-jin ZHU, Yue-zhi ZHOU, Xiu-hua ZHENG 2024, 45 (6):  874-882.  DOI: 10.12068/j.issn.1005-3026.2024.06.016 Abstract ( 365 )   HTML ( 6)   PDF (1250KB) ( 99 )   For the mechanical characteristic of the crack surface closure and friction sliding under compression?shear load， Kolossoff-Muskhelishvilli stress function of the cracked rockmass subjected to compression and shear load is firstly established based on Muskhelishvili complex function theory. Then the calculation formulae of the stress intensity factor K and three T-stress components at the crack tip considering three kinds of crack parameters （namely geometry parameter， friction strength parameter and deformation parameter） are proposed. Secondly， a revised maximum tangential stress criterion is obtained by incorporating T-stress at the crack tip and three kinds of crack parameters into the classic maximum tangential stress（MTS） criterion. Meanwhile this proposed criterion assumes that the crack deformation parameter such as crack normal and shear stiffness is not a constant and is closely related to the stress characteristic on the crack face. Additionally， the crack deformation parameters for different crack dip angles are given. Finally， the experiment results of the wing?crack initiation angle under compression and shear load are adopted to preliminarily valid the revised criterion. It indicates that it is necessary to consider the crack deformation parameter. Figures and Tables | References | Related Articles | Metrics

Select

Analysis of the Aging Behavior of Polyester Filter Media for Steel Companies in a Composite Environment Feng DAI, Jing-xian LIU 2024, 45 (6):  883-889.  DOI: 10.12068/j.issn.1005-3026.2024.06.017 Abstract ( 298 )   HTML ( 5)   PDF (1524KB) ( 124 )   To study the effect of high?temperature flue gas on the performance of filter bags， acid?base interaction aging tests were conducted on polyester filter media at three different temperatures （45， 75 and 130 ℃）. The results revealed that polyester filter media exhibited poor resistance to hydrolysis in high temperature acid?base coupled environments， and when subjected to alkali followed by acid corrosion， the filter media experienced significant degradation. The tensile breaking strength and surface peeling strength of the filter media decreased from 1 638.8 and 143.1 to 1 100.8 and 19.1 N， respectively， after interactive aging in alkaline and acidic environments at 130 ℃， FT-IR showed that the C—O absorption peak was weakened， indicating that the macromolecular chain of polyethylene terephthalate was broken during hydrolysis， which was the main reason for the occurrence of hydrolysis and performance degradation. Figures and Tables | References | Related Articles | Metrics

Select

Tar Cracking Removal Technology in Biomass Gasification Process Xi-wen YAO, Qing-hua LIU, Hao-dong ZHOU, Kai-li XU 2024, 45 (6):  890-896.  DOI: 10.12068/j.issn.1005-3026.2024.06.018 Abstract ( 356 )   HTML ( 13)   PDF (935KB) ( 288 )   In order to grasp the research status and development of tar cracking technology during biomass gasification in recent years and aim at the production mechanism and thermochemical removal of tar during biomass gasification process， this study reviewed the characteristics of the gasification technology of different biomass gasifiers together with the characteristics of controlling the original emission of tar by means of literature research， summary and comparative analysis. The development of tar thermal cracking and catalytic cracking technology was analyzed， and the advantages and disadvantages of different tar cracking catalysts were compared and analyzed. The main direction of catalyst development was pointed out. The integration of tar catalytic cracking and physical removal （such as tar catalytic cracking， reforming， gas-liquid separation and electric tar capture） would be an effective approach to optimize the biomass gasification process. Figures and Tables | References | Related Articles | Metrics

Management Science

Select

Research on Distributional Preference for Time Based on the EET Non-parameter Method Yang LU, Jian WANG 2024, 45 (6):  897-904.  DOI: 10.12068/j.issn.1005-3026.2024.06.019 Abstract ( 381 )   HTML ( 1)   PDF (1641KB) ( 66 )   EET （equality equivalence test） non?parameter method was proposed to examine people’s distributional preferences for time. Firstly， time distributional preferences were classified into nine types by utilizing the EET method， assumptions were introduced to reflect the unique features in the time domain. Then， based on the two rounds of behavioral experiments conducted in both time and money domains， decision makers’ preference types were identified by the indifference curves， and the pattern was analyzed. The results showed that： relative to money， more people are influenced by others’ payoff when exposed to time distribution problems. As people use heuristic thinking due to the infungibility of time， their own payoff resultingly converges to the payoffs of others； people tend to be more benevolent when they have greater payoff relative to their counterparts， and more malevolent when having relatively less payoff； no extreme forms of spite are detected. Figures and Tables | References | Related Articles | Metrics

Select

Two-Stage Stochastic Inventory Optimization for the Assemble to Order System Ke JING, Yu LIU, Le-hua LI 2024, 45 (6):  905-912.  DOI: 10.12068/j.issn.1005-3026.2024.06.020 Abstract ( 327 )   HTML ( 1)   PDF (789KB) ( 114 )   Based on the replenishment strategy for the basic inventory level of parts and components， a two?stage stochastic optimization model is constructed with multi‐period uncertain order product demands. In the first stage， the basic inventory level of components is the decision variable and needs to be determined at the condition of unknown demands， and the objective is to achieve the maximum system revenue. In the second stage， the order assignment variable is designed when the order due date constraint is required， and the objective of this stage is to maximize the expected order revenue by taking order revenue and tardiness penalty into account. Additionally， a single?stage deterministic model by transforming the uncertain demand to the determined expected demand is presented and the objective function value of this deterministic model is compared with that of the stochastic model. The numerical experiment results show the performance of the stochastic model is worse than that of the deterministic model， which indicates some value of the unknown information. Meanwhile， a sensitive analysis is implemented for the parameters in the model and a strategy is put forward to improve the system revenue in practice. Figures and Tables | References | Related Articles | Metrics