50 results about "Material properties" patented technology

The invention discloses a control method and system of a servo press, and relates to the field of press control, a force displacement curve is obtained in real time from a current punching period, a key feature vector of the force displacement curve is extracted, the key feature vector is compared with an ideal golden feature vector, and a multi-dimensional deviation vector is obtained. Particularly, a deviation decoupling method based on morphological analysis is introduced, and the total deviation can be accurately decomposed into a thermal drift compensation amount caused by the thermal effect of equipment and a material characteristic compensation coefficient caused by plate performance fluctuation by analyzing translation and zooming differences of a current curve and a gold curve in form. Therefore, independent and accurate compensation can be carried out for a physical source, the problems of information aliasing and compensation failure caused by the fact that disturbance sources cannot be distinguished in the prior art are effectively solved, intelligent and feed-forward type cooperative compensation for the next stamping period is achieved, and long-term stability and high precision of the production process are ensured.

The invention provides a low-temperature-resistant performance evaluation method for a composite material, and belongs to the technical field of material performance determination.The method comprises the steps that firstly, in a low-temperature environment box, a temperature sensor is used for accurately controlling the temperature of a sample, and meanwhile, a high-frequency strain sensor is used for collecting data; then, wavelet transform is adopted to carry out denoising and decomposition on the strain signals, and key low-temperature characteristic parameters are extracted; and constructing a performance evaluation model based on deep learning, inputting the temperature field, the strain characteristics and the material basic parameters into the model, and predicting the low-temperature strength. A prediction result is verified through a standard test, a prediction error is calculated, an error distribution matrix is established, and an improved back propagation algorithm is adopted to optimize the model. Finally, a fuzzy comprehensive evaluation method is applied, indexes such as strength retention rate and strain stability are comprehensively considered, and the low temperature resistance grade of the composite material is scientifically evaluated. The method solves the problem that the actual mechanical properties of the composite material in the low-temperature environment are difficult to comprehensively reflect in the prior art.

The invention relates to the technical field of machining simulation, in particular to a composite material ring piece low-stress machining method based on finite element analysis. The method comprises the following steps: constructing a two-dimensional finite element model of the composite material ring piece; grid division is carried out on the geometric model, and the structure is decomposed into units; setting boundary conditions and loads of the simulation model; defining material attributes including density, thermal conductivity, specific hot melting, elastic modulus, Poisson's ratio, plasticity and creep; setting processing and heat treatment parameters, including processing procedures, processing amount, heat treatment temperature and time; the simulation model is operated, and the response of the geometric model under the given boundary and loading condition is obtained; and analyzing an operation result, summarizing an influence rule of machining parameters and heat treatment setting on machining stress, and optimizing a machining scheme. According to the method, a stable component low-stress machining scheme can be rapidly obtained through an analogue simulation technology for the machining process of the composite material ring piece, and high-precision machining of the large-size fiber reinforced composite material ring piece is achieved.

The invention provides a surface protection composite material formula optimization method, which belongs to the technical field of electric digital data processing, and comprises the following steps of: establishing a performance equation set comprising thermal stress, interface mechanics and chemical reaction kinetics by collecting initial formula data and interface chemical characteristics; and performing a precision test in a low-temperature saline water environment of-40 to-60 DEG C. And establishing a performance prediction model by adopting a least square method, and constructing a multi-dimensional formula space. A genetic algorithm and a grey wolf hunting algorithm are innovatively combined, multi-objective optimization of a formula is achieved, and minimization of interface stress and maximization of bonding strength are taken as core objectives. Through an orthogonal test and orthogonal analysis, an influence mechanism of component matching on material performance is deeply analyzed, and a failure mechanism criterion is established. Through multiple rounds of limit tests and directional optimization, the optimal surface protection composite material formula adapting to the extremely low temperature environment is finally obtained, and the problem that a global optimal formula is difficult to obtain in the prior art is solved.

The invention discloses a three-dimensional thermal stress coupling simulation method for borosilicate glass / Cu / dielectric layers. The method comprises the following steps: collecting and sorting effective information of material attributes and physical fields involved in a simulation process; preliminarily screening material characteristic parameters, and determining interfacial compatibility among different materials; a preliminary three-dimensional model of the borosilicate glass, Cu and dielectric layer composite material is constructed, stability analysis is carried out for different material combinations, and an optimal material combination is screened; establishing a three-dimensional thermal stress coupling simulation model by combining the preliminary three-dimensional model, simulating thermal stress distribution under different working conditions, analyzing a stress transfer mechanism between different material layers, and optimizing thermal adaptability of a material interface; optimizing the structure of the composite material by using a finite element analysis technology, and adjusting the thicknesses and proportions of different material layers; through a repeated optimization process, an optimal three-dimensional thermal stress distribution design scheme is finally determined, and the effectiveness and reliability of the three-dimensional thermal stress coupling simulation method are verified through experiments.

The present application belongs to the technical field of thermal load deformation and force load deformation measurement, and relates to a thermal and force deformation field decoupling method and system based on two-dimensional visual measurement. According to the temperature field at discrete temperatures, the thermal deformation field at discrete temperatures and the corresponding temperature, and by using a binary function model, the influence coefficient of fitting temperature on thermal strain is obtained, the jumps between discrete data are eliminated, and the continuity and prediction ability of thermal strain are improved. According to the influence coefficient of fitting temperature on thermal strain and the binary function model, a fitted binary function model is obtained, which is more in line with the actual material properties. According to the temperature field under the thermal and force coupling condition, the deformation field under the thermal and force coupling condition and the fitted binary function model, an equivalent thermal deformation field is obtained, the thermal and force coupling deformation is decoupled, the dynamic correlation of thermal strain and deformation field is realized, and the decoupling precision is improved.

This invention belongs to the field of additive remanufacturing technology, specifically relating to an optimization method and system for the additive remanufacturing process of brake discs for rail vehicles. The method analyzes the material properties of the brake disc substrate to obtain material property data, monitors the solidification front morphology of the molten pool in real time during the additive remanufacturing process, analyzes and infers the differences between the solidification morphology of the substrate and the molten pool based on these two sets of data, and optimizes and adjusts the additive remanufacturing process parameters according to the inference results. By accurately identifying the material properties of the substrate and combining real-time monitoring of the molten pool solidification front, this application can deeply analyze the underlying causes of local thermal anomalies in the molten pool, identify and correct specific problems such as insufficient or excessive laser energy, uneven laser spot energy distribution, or abnormal scanning paths, thereby achieving precise optimization and adjustment of the additive remanufacturing process parameters, providing a reliable and efficient solution for the additive remanufacturing of rail vehicle brake discs.

The invention discloses an on-line testing method for simultaneously measuring characteristic parameters of multiple MEMS materials. The on-line testing method comprises a design and use process of an MEMS on-line testing structure. A required testing structure consists of a V-shaped thermal actuator and two comb-tooth-shaped electrostatic actuators at the front end and the rear end of the V-shaped thermal actuator, and Young modulus, residual stress and thermal expansion coefficient of the silicon material layer can be calculated by analyzing behaviors of the actuators. Therefore, firstly, geometric parameters of two comb-shaped electrostatic actuators with different geometric parameters and a V-shaped thermal actuator are designed by establishing a physical model so as to ensure that the actuators are sufficiently sensitive to the properties of a material layer and are relatively easy to drive; the measurement process is completed by applying electric excitation, analyzing electric signal feedback and performing subsequent data processing, the method does not depend on other complex test equipment or harsh test environment, and the method can be suitable for different MEMS processes without adding extra process steps. The method has practical significance for improving the MEMS test efficiency and the automation degree of the test process.

This invention discloses a method and system for predicting fine-grained volumetric material properties based on a physical world model. The method includes: acquiring visual observation data and three-dimensional geometric data of a target object; extracting visual features from the visual observation data and geometric features from the three-dimensional geometric data, while simultaneously acquiring semantic description information characterizing the material properties of the target object; generating physical parameter reference constraint information for the corresponding material based on the semantic description information; fusing the visual features, geometric features, and physical parameter reference constraint information to obtain a multimodal global fusion feature; and using a hierarchical volume prediction network based on physical constraint distillation based on the multimodal global fusion feature to predict voxel-level volumetric material property data of the target object. The volumetric material property data includes at least the material category probability distribution and intrinsic physical parameters of the material corresponding to each voxel inside the target object, i.e., a fine-grained volumetric material property field.

This technology enables the numerical analysis of the effect that anisotropic materials have on the overall rigidity of a structure when the material is anisotropic. [Solution] A structural analysis method for an anisotropic material according to one aspect of the present invention comprises the steps of: assigning calculation points to structural data (S11); assigning material properties including anisotropy to structural data (S12); assigning load points, support points, and arbitrary points to the calculation points (S13); and determining an index (A) based on the ratio of a first work required for the displacement of the load point when the material axis vector at the arbitrary point is set according to the anisotropy of the material properties, and a second work required for the displacement of the load point when the direction of the material axis vector is rotated to coincide with the displacement direction of the load point. * The steps involve calculating the index (A) while changing an arbitrary point. * ) is calculated, and the index (A) in the structural data is calculated. * The system comprises the steps of calculating the distribution of (S14-S16) and

The invention discloses an uncertain quantization and propagation method for constitutive parameters of a viscoelastic composite material, which comprises the following steps of: developing a multi-scale micro-mechanical model on the basis of a fractional order differential and average field homogenization theory so as to reveal a nonlinear relation among component material performance, microstructure parameters and macroscopic viscoelasticity. And secondly, the Levenberg-Marquardt optimization algorithm and the Physics-Informed Neural Network proxy model are used for realizing the self-adaptive optimization of the sampling initial conjecture and the improvement of the calculation efficiency. Therefore, a Bayesian probability model is established, and model parameter posterior distribution is calculated by adopting a Markov chain Monte Carlo method so as to evaluate uncertainty, correlation and model errors of parameters. And finally, calculating posterior prediction distribution of the overall response, the constitutive response and the noise response. According to the method, the provided multi-scale Bayesian framework provides an effective way for optimizing component material performance and microstructure parameters, and the method has an important guiding effect on design of advanced viscoelastic composite materials with higher bearing capacity.

This application discloses a method for obtaining the detonation velocity and detonation pressure of energetic materials based on atomic-scale dynamics, relating to the field of materials science and technology. The method includes: acquiring an initial configuration file of the energetic material to be tested, and performing dynamic processing on the initial configuration file using a materials simulation model to generate a first training dataset; iteratively training the potential function using the first training dataset to obtain a structure file corresponding to each generation of training; sampling and screening the structure files, and calculating the accuracy adjustment parameters corresponding to the sampled and screened structure files using first-principles calculation software; adjusting the parameters of the materials simulation model using the accuracy adjustment parameters, and using the adjusted materials simulation model to generate a second training dataset from the structure files obtained from each generation of training and the first training dataset; and predicting the performance of the energetic material to be tested based on the potential function trained on the second training dataset. A general method for predicting material properties that balances accuracy and efficiency is proposed.

The invention relates to the technical field of gas insulation, in particular to an epoxy composite material internal crack defect detection method, equipment and a medium, structural parameters of a 110kV epoxy basin-type insulator are measured, and three-dimensional modeling software is adopted to construct a three-dimensional structural model equal to a real object in proportion; applying a thermal boundary condition to the three-dimensional structure model body, respectively setting the depth and the deflection angle of the crack defect as h and theta, and setting the material attribute of the bubble defect area as air; the method comprises the following steps: acquiring surface thermal imaging characteristics of the defect of the epoxy basin-type insulator based on a solid heat transfer theory, outputting the surface thermal imaging characteristics of the defect of the epoxy basin-type insulator, and acquiring surface thermal imaging characteristics of the crack defect at different deflection angles under different defect depths by changing the depth and the deflection angle of the crack defect for many times based on the solid heat transfer theory. Equipment temperature resolution is used as a judgment basis, and feasibility exploration of crack defect detection at different deflection angles under different defect depths is realized.

The application discloses a kind of ceramic matrix composite temperature-related mechanical properties inversion method, specifically related to the field of composite material performance characterization.It includes: the ceramic matrix composite to be measured is divided into multiple test pieces;Each test piece is heated to target temperature, and the measured thermal strain of multiple points on the surface of each test piece is obtained;For each test piece, at its target temperature, the test piece is uniaxially stretched by loading end, and the measured tensile strain of multiple points on the surface of the test piece during uniaxial stretching, the measured stress-strain curve is obtained;A parameterized function of the mechanical property parameter vector of the ceramic matrix composite to be measured changes with temperature is constructed, to minimize the error function as the goal, the hyperparameter vector is inverted and identified, to obtain the optimal hyperparameter vector, and the mechanical property parameter vector of the ceramic matrix composite to be measured is obtained in combination with the parameterized function.Based on the above method, the mechanical property parameters of microscale component materials can be obtained.

An accuracy of prediction of a characteristic value of a material is improved. A method according to one aspect of the present invention includes acquiring an image of a material, performing a topological data analysis on the image of the material to extract features of the material, and predicting a characteristic value of the material from the features of the material.

The application discloses a method for determining the Debye temperature of a crystal material, and comprises the following steps: collecting the isobaric heat capacity data C P (T) of a crystal material in a temperature range; P (T) of the crystal material, and finding the temperature T0 corresponding to the extreme point of C P (T) by derivation; P (T) of the crystal material, and calculating the isochoric heat capacity C P (T) of the crystal material according to a thermodynamic formula; V (T) of the crystal material according to a Debye isochoric heat capacity evaluation model; V (T) of the crystal material according to the extreme temperature T0; P (T0) determined according to the extreme temperature T0 and the isochoric Debye temperature θ V (T0) of T0, and the temperature closest to the isochoric Debye temperature θ (T0) is the Debye temperature of the material. The method for determining the Debye temperature of the crystal material is simple and easy to implement, and can provide strong support for rapid evaluation and accurate design of material performance in the material research and development process.

The application discloses a kind of laser fusion forging multi-physical field integrated numerical simulation method and system, belong to additive manufacturing technical field, numerical simulation method includes: establishing three-dimensional geometric calculation domain;Based on calculation domain, through the introduction of mass source term in mass conservation equation, the coaxial powder feeding laser cladding process is simulated;Based on mass source term, solve phase fraction field distribution, and then determine metal and gas interface;Based on phase fraction field, determine the temperature field distribution of calculation domain;Based on phase fraction field and temperature field, the material properties of each region of calculation domain are dynamically updated;Under the constraint of updated material properties, the flow field of liquid metal is calculated based on fluid momentum conservation equation;Based on phase fraction field and temperature field, solve solid momentum conservation equation, determine the stress field of solid region.The application establishes a unified multi-physical field solving framework, avoids the problem of heat-flow and heat-force model fragmentation in traditional method, effectively improves the integrity and accuracy of defect prediction.

The invention belongs to the technical field of material performance testing, and particularly relates to a composite material impact damage introducing device, a testing method and a control system.The composite material impact damage introducing device comprises an inner shell and an outer shell, a center hole is formed in the inner shell, and two lateral through holes are formed between the inner shell and the outer shell and located on the two sides of the center; a transmission mechanism is arranged at one end in the outer shell, an elastic mechanism is arranged in the center hole, one end of the elastic mechanism is connected with the transmission mechanism, the other end of the elastic mechanism is connected with an impact mechanism, and a limiting mechanism is arranged at the lower end in the outer shell and matched with the impact mechanism and the elastic mechanism to limit the impact mechanism; according to the device, the spring drive is combined with the gear set to accurately control energy, and the replaceable impact head and the limiting claw linkage mechanism are matched, so that impact at any angle, accurate energy adjustment and secondary impact prevention are realized, the universality, the accuracy and the reliability of the device are remarkably improved, and the device has important practical significance and application prospects in composite material performance testing.

The invention relates to the technical field of material performance testing, and provides a rheological property and heat-conducting property combined measurement method and equipment, and the method comprises the following steps: placing a sample to be tested on a first surface of a tray; adjusting the position of the rotor unit to enable the rotating head to be close to the first surface of the tray and to be in contact with the surface of the to-be-tested sample; the heating element and the refrigerating element are started, so that the heating surface of the heating element transmits heat to the rotating head through the rotating rod and transmits the heat to the to-be-tested sample through the rotating head, and the refrigerating surface of the refrigerating element transmits cold energy to the to-be-tested sample through the tray, and the to-be-tested sample is cooled under the combined action of the heating element and the refrigerating element. The temperature of the to-be-tested sample is maintained in a preset temperature range; the rotor unit is started, so that the rotating rod drives the rotating head to rotate, and the rotating head shears and stirs the to-be-tested sample according to a preset shearing rate; and maintaining the preset shear rate, and measuring the rheological property and heat-conducting property of the sample to be measured to obtain rheological property parameters and heat-conducting property parameters.

In some embodiments, a method includes determining an atom type of each atom from a set of atoms in a functional group of a molecular system. The method includes calculating, based on the set of atom types, a first set of ab initio molecular properties of a monomer and a second set of ab initio molecular properties of a multimer. The method further includes determining a set of parameters of a force field model by fitting the force field model to the first set of ab initio molecular properties and the second set of ab initio molecular properties until at least an agreement reaches a pre-determined threshold. The method includes determining, based on the set of parameters and the force field model, a molecular property of the molecular system and sending a signal to present the molecular property of the molecular system.

This invention discloses an online testing method for simultaneously measuring multiple MEMS material property parameters. The invention includes the design and application of an online MEMS testing structure. The required testing structure consists of a V-shaped thermal actuator and two comb-shaped electrostatic actuators at its front and rear ends. Analysis of the behavior of these actuators allows for the calculation of the Young's modulus, residual stress, and coefficient of thermal expansion of the silicon material layer. To achieve this, a physical model is first established to design the geometric parameters of the two comb-shaped electrostatic actuators and the V-shaped thermal actuator, ensuring that the actuators are sufficiently sensitive to the properties of the material layer and relatively easy to drive. This invention completes the measurement process by applying electrical excitation, analyzing the electrical signal feedback, and subsequent data processing. It does not rely on other complex testing equipment or harsh testing environments and is applicable to different MEMS processes without requiring additional processing steps. This has practical significance for improving MEMS testing efficiency and the degree of automation in the testing process.

The invention relates to an LLC transformer temperature prediction and control method, system, device and medium, and the method comprises the steps: obtaining the structure parameters and material attributes of an LLC transformer, and carrying out the parameterized three-dimensional modeling, and obtaining a transformer three-dimensional geometric model comprising complete material attributes; non-sinusoidal current waveforms of the LLC transformer during working are acquired through circuit simulation, key characteristic parameters of the current waveforms are extracted, and magnetic core loss is calculated by utilizing an IGSE formula based on the key characteristic parameters and material attributes; acquiring environment parameters of an environment where the LLC transformer is located, and calculating heat transfer key parameters between the surface of the LLC transformer and air based on the environment parameters; based on the magnetic core loss and the heat transfer key parameters, performing steady-state thermal simulation and transient thermal simulation by using the three-dimensional geometric model of the transformer to obtain a temperature distribution condition, and generating an LLC transformer temperature management strategy based on the temperature distribution condition; the system, the equipment and the medium are used for realizing the method. Compared with the prior art, more accurate transformer temperature prediction is realized.

The invention discloses a meshless EFGM-based topological optimization method for a multi-material periodic steady-state heat transfer structure. The method comprises the following steps: (1) inputting material attributes such as a heat conductivity factor, a material direction angle, a volume fraction ratio and a heat conductivity coefficient of the multi-material periodic structure; (2) discretizing a design domain by using a meshless method, and carrying out EFGM multi-material steady-state heat transfer analysis; (3) setting iteration parameters and an initial multi-material EFGM node relative density matrix; (4) solving an EFGM discrete control equation after punishment of the SIMP multi-material interpolation model; (5) establishing a topological optimization mathematical model of the multi-material periodic steady-state heat transfer structure based on EFGM; (6) performing periodic averaging processing, and solving volume sensitivity and thermal flexibility sensitivity; (7) optimizing and updating a multi-material EFGM node relative density matrix through two-phase competition; (8) inputting a termination condition, and judging whether loop iteration is continued or not; and (9) outputting a multi-material distribution cloud picture. According to the method, topological optimization of the anisotropic multi-material periodic steady-state heat transfer structure is carried out based on the meshless EFGM, and the structure is clear, simple and practical.

This invention discloses an adaptive control method and system for the discharge rate of compound materials. The invention relates to the field of compound material production control technology, and includes a multi-dimensional real-time data acquisition module, a data transfer module, a material calculation and analysis module, and a feeding and slag discharge collaborative control module. The material calculation and analysis module includes a material calorific value analysis unit, an optimal discharge calculation unit, and a collaborative control correction unit. The material calorific value analysis unit outputs a dynamic calorific value matching coefficient to normalize multi-dimensional heterogeneous parameters, automatically adapting to changes in material properties and eliminating material-side fluctuation interference. The optimal discharge calculation unit outputs a real-time optimal discharge rate threshold, taking into account emissions, combustion status, and flue gas treatment capacity boundaries to balance emission compliance and operational efficiency. The collaborative control correction unit outputs a control correction amount, synchronously adjusting the feeding and slag discharge parameters to avoid operating condition fluctuations and ensure the adaptability of control actions to operating conditions.

The application belongs to the technical field of material analysis, and particularly relates to a method and device for obtaining the performance of a two-dimensional structural material. The method comprises the following steps: for a two-dimensional structure, the two-dimensional structure is subjected to a thermal wave and an acoustic wave with a constant amplitude and a constant surface, and the axial stress and the shear stress are free; a fractional order heat conduction model is established, and a motion model, a constitutive model and a thermo-acoustic coupling model are established without considering body force; the fractional order heat conduction model, the motion model, the constitutive model and the thermo-acoustic coupling model are subjected to dimensionless processing to obtain a control equation; the control equation is solved by using a potential function method and wave theory to obtain the mechanical performance and acoustic performance distribution results of the two-dimensional structure. The establishment of the fractional order heat conduction model and the solving of the control equation by using the potential function method and the wave theory can improve the accuracy of the solving results of the mechanical performance and acoustic performance distribution law of the two-dimensional structure.

The invention relates to an unequal-thickness cold-rolled plate leveling method, which comprises the following steps of: adjusting equipment parameters and equipment initial states based on unequal-thickness plates and production requirements, and constructing a dynamic model with matched materials and processes: collecting thickness data of the unequal-thickness plates, performing de-noising processing on originally measured thickness signals by adopting a filtering algorithm, and calculating the thickness data of the unequal-thickness plates according to the de-noising processing; obtaining target thickness information; constructing a digital correction process model based on the target thickness information and the equipment parameters to obtain a roll gap curve; by constructing a digital correction process model of composite material attributes, a production target and a quality target and adopting prospective simulation and reverse iterative calculation, a roll gap sequence optimally matched with the thickness of each position of a plate is solved, and the purposes of automatically identifying a thick area and a thin area, dynamically adjusting a roll gap, avoiding the over-straightening risk of the thick area and improving the product quality are achieved. And full plastic deformation of the thin area is guaranteed, and the effect of uniform and consistent high-quality planeness is obtained on the whole plate length.

To improve the accuracy of predicting material properties of metals.SOLUTION: A material property prediction apparatus includes: a receiving unit 15A which receives an original image obtained by imaging a metal through a microscope; a division unit 15B which divides the original image into a plurality of partial images; and a prediction unit 15F which predicts material properties corresponding to the original image, on the basis of a label for material properties which is output for each partial image by a machine learning model by inputting the partial images to the machine learning model for each partial image.SELECTED DRAWING: Figure 1

The invention discloses an inversion method for temperature-related mechanical properties of a ceramic-based composite material, and particularly relates to the field of performance characterization of composite materials. Comprising the following steps: dividing a to-be-tested ceramic-based composite material into a plurality of test pieces; heating each test piece to a target temperature, and obtaining actually measured thermal strain of a plurality of points on the surface of each test piece; for each test piece, carrying out uniaxial stretching on the test piece through the loading end at the target temperature, and obtaining actually measured tensile strain and actually measured stress-strain curves of a plurality of points on the surface of the test piece in the uniaxial stretching process; and constructing a parameterization function of the mechanical property parameter vector of the to-be-tested ceramic matrix composite material along with the temperature change, performing inversion identification on the hyper-parameter vector by taking the minimization of the error function as a target to obtain an optimal hyper-parameter vector, and combining the parameterization function to obtain the mechanical property parameter vector of the to-be-tested ceramic matrix composite material. Based on the method, the mechanical property parameters of the micro-scale component material can be obtained.

The application discloses a material conveying ash-gas ratio adjusting method and a material conveying device. After each conveying is completed, step A is executed, and step A comprises the following steps: S1: obtaining an average value of a gas flow lower limit in a conveying process, comparing the average value of the gas flow lower limit with a preset gas flow lower limit value, if a deviation between the average value of the gas flow lower limit and the preset gas flow lower limit value is less than a preset deviation range, then the opening degrees of a primary gas adjusting valve and a tertiary gas adjusting valve are increased, and if the deviation between the average value of the gas flow lower limit and the preset gas flow lower limit value is greater than the preset deviation range, then the opening degrees of the primary gas adjusting valve and the tertiary gas adjusting valve are decreased. The application adjusts the gas flow in the conveying process, realizes dynamic adjustment of the ash-gas ratio, solves the system imbalance problem caused by the fact that the ash-gas ratio does not change along with the change of the material properties, and makes the material conveying device achieve an energy-saving, stable and efficient operation state.