An intelligent control system and method for a sintering trolley based on industrial automation technology

Abstract

The present invention relates to the technical field of sintering machine control, specifically an intelligent control system and method for sintering pallets based on industrial automation technology, including: a data acquisition module, a temperature detection module, a deformation analysis module, a combined analysis module, and a stability adjustment module; by obtaining the thickness distribution, temperature, and thermal stress of the sintering layer during the operation of the sintering pallet; generating a temperature cloud map of the trolley travel path according to the temperature of the sintering pallet, comparing the temperature cloud map features under different sintering layer thickness distributions, and setting a temperature-stress relationship curve; identifying the deformation concentration area on the sintering pallet, comparing the distribution of thermal stress in the deformation concentration area, and establishing a stress accumulation curve; predicting the change trend of the sintering pallet according to the temperature-stress relationship curve and the stress accumulation curve; setting a collaborative adjustment plan according to the change trend of the sintering pallet; realizing the stability and efficiency of the sintering process and improving the safety of equipment operation.

Description

Technical Field

[0001] The present invention relates to the technical field of sintering machine control, and specifically to an intelligent control system and method for sintering pallets based on industrial automation technology. Background Art

[0002] In the existing industrial automation field, the sintering pallet, as a key production equipment, plays a crucial role in multiple industries such as metallurgy and ceramics. The traditional sintering pallet control system mainly relies on manual operation and regular equipment inspection to ensure its stable operation and product quality. However, with the continuous expansion of production scale and the increasing improvement of production requirements, this traditional control method gradually exposes many deficiencies.

[0003] For example, Chinese Patent Publication No. CN114383423A discloses a method and system for on-line greasing of the axle of a sintering pallet, including the steps: S10, calculating the theoretical position acquisition times of each pallet wheel; S20, within the theoretical position acquisition times, obtaining the actual minimum vertical distance Lz1 between the vertical sensor and the circumferential wall surface of the pallet wheel measured by the vertical sensor; S30, obtaining the actual horizontal distance Lx between the horizontal sensor and the side wall surface of the pallet wheel measured by the horizontal sensor; S40, if the difference between the actual minimum vertical distance Lz1 and the theoretical standard distance Lz0 is within the preset vertical distance range, and the actual horizontal distance Lx is within the preset horizontal distance range, the greasing unit greases the axle of the corresponding pallet wheel.

[0004] For example, Chinese Patent Publication No. CN115218670A discloses a method for gas-steam intermittent injection-assisted sintering, which intermittently injects gas and steam periodically onto the surface of the sintering mixture. The gas enters the sintering material layer to burn and supply heat, and the steam enters the sintering material layer to react with carbon in the solid fuel to accelerate the combustion of the solid fuel; during the process of gas injection, by adjusting the injection duration of gas within a single cycle, the temperature control of the sintered ore zone and the combustion zone in the sintering material layer is realized.

[0005] The prior art shows that the current sintering pallet can be controlled according to the height difference under the actual acquisition times, and at the same time, the cycle number and duration of gas are adjusted to control the temperature on the sintering pallet; however, under these control methods, it is still necessary to verify the stress and strain received by the corresponding components on the current sintering pallet, and identify whether excessive deformation of some components and structures occurs due to the adjustment of the temperature control method, resulting in structural damage and reducing the service life of some components on the sintering pallet. Summary of the Invention

[0006] To solve the above technical problems, the technical solution adopted by the present invention is: an intelligent control system for a sintering trolley based on industrial automation technology, including: a data acquisition module for obtaining the equipment working information of the sintering trolley in all working cycles, and the equipment working information includes the sintering layer thickness distribution, temperature and thermal stress when the sintering trolley is working.

[0007] A temperature detection module for generating a temperature cloud map of the trolley travel path according to the temperature of the sintering trolley, comparing the characteristics of the temperature cloud map under different sintering layer thickness distributions, identifying the temperature distribution form, calculating the maximum temperature difference and thermal stress under the corresponding temperature distribution form, and setting a temperature-stress relationship curve.

[0008] A deformation analysis module for identifying the equivalent force according to the equipment conditions of the sintering trolley and identifying the deformation concentration area on the sintering trolley; comparing the distribution of thermal stress in the deformation concentration area under different sintering layer thickness distributions and temperatures, and establishing a stress accumulation curve.

[0009] A combined analysis module for identifying the residual stress when the sintering trolley is working and predicting the change trend of the sintering trolley according to the temperature-stress relationship curve and the stress accumulation curve.

[0010] A stability adjustment module for adjusting the working mode of the sintering trolley according to the change trend of the sintering trolley and setting a collaborative adjustment plan.

[0011] An intelligent control method for a sintering trolley based on industrial automation technology, including: S1, obtaining the equipment working information of the sintering trolley through devices such as sensors.

[0012] S2, generating a temperature cloud map based on the equipment working information, identifying the temperature distribution form under the temperature cloud map, and calculating the maximum temperature difference and thermal stress.

[0013] S3, identifying the deformation concentration area corresponding to the thermal stress and establishing a stress accumulation curve.

[0014] S4, constructing a mapping relationship between the temperature and the stress accumulation curve, and predicting the change trend of the sintering trolley.

[0015] S5, adjusting the working mode according to the change trend of the sintering trolley and setting a collaborative adjustment plan.

[0016] The beneficial effects of the present invention are as follows: First, by obtaining the equipment working information of the sintering trolley in all working cycles and identifying the relevant temperatures according to the trolley's traveling path, after obtaining the temperature distribution form of the sintering trolley during operation, setting the relationship curve between temperature and stress, it can identify whether the material expansion caused by different temperature differences exceeds the limit of normal deformation, and link temperature and stress, enabling real-time and accurate monitoring of the working state of the sintering trolley, improving the accuracy and reliability of monitoring.

[0017] Second, by identifying the deformation concentration areas on the sintering trolley and the thermal stress distribution therein, accumulating to obtain the stress accumulation curve, and timely identifying the stress accumulation situation of the corresponding components on the sintering trolley, it can reduce the structural damage caused by excessive deformation accumulation. Considering the relevant stress accumulation, while identifying the stress values within the corresponding range, identifying the center points of each range, and finding the corresponding stress concentration areas according to the time when residual stress appears at the center points of each range, it can reduce the failures caused by excessive material deformation and improve the equipment life.

[0018] Third, by mapping the temperature-stress relationship curve and the stress accumulation curve to identify the change trend of the sintering trolley, it can timely detect the equipment failures of the sintering trolley; based on the influence range under the change trend and the triggering conditions for failures, constructing a strategy control model for subsequent use, it can adaptively adjust the control method used according to the specific state of the sintering trolley, improving the production efficiency and safety of the sintering trolley. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the drawings and embodiments.

[0020] Figure 1 It is a system schematic diagram of an intelligent control system for a sintering trolley based on industrial automation technology.

[0021] Figure 2 It is a flowchart of the temperature detection module of an intelligent control system for a sintering trolley based on industrial automation technology.

[0022] Figure 3 It is a flowchart of the deformation analysis module of an intelligent control system for a sintering trolley based on industrial automation technology.

[0023] Figure 4 It is a flowchart of the stability adjustment module of an intelligent control system for a sintering trolley based on industrial automation technology.

[0024] Figure 5 It is a flowchart of an intelligent control method for a sintering trolley based on industrial automation technology. Detailed implementation manners

[0025] The embodiments of the present invention will be described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be construed as a limitation to the present invention. For those without specific technologies or conditions noted in the embodiments, they shall be carried out according to the technologies or conditions described in the literature in this field or according to the product specifications.

[0026] Refer to Figure 1 , an intelligent control system for a sintering trolley based on industrial automation technology, comprising: a data acquisition module, a temperature detection module, a deformation analysis module, a combined analysis module, and a stability adjustment module; wherein, the output end of the data acquisition module is connected to the temperature detection module, the output end of the temperature detection module is connected to the deformation analysis module, the output end of the deformation analysis module is connected to the combined analysis module, and the output end of the combined analysis module is connected to the stability adjustment module.

[0027] The data acquisition module is used to obtain the equipment working information of the sintering trolley in all working cycles, and the equipment working information includes the thickness distribution, temperature, and thermal stress of the sintering layer when the sintering trolley is working.

[0028] The temperature detection module is used to generate a temperature cloud map of the trolley travel path according to the temperature of the sintering trolley, compare the characteristics of the temperature cloud map under different sintering layer thickness distributions, identify the temperature distribution form, calculate the maximum temperature difference and thermal stress under the corresponding temperature distribution form, and set the temperature-stress relationship curve.

[0029] The deformation analysis module is used to identify the equivalent force according to the equipment conditions of the sintering trolley and identify the deformation concentration area on the sintering trolley; compare the distribution of thermal stress in the deformation concentration area under different sintering layer thickness distributions and temperatures, and establish a stress accumulation curve.

[0030] The combined analysis module is used to identify the residual stress when the sintering trolley is working according to the temperature-stress relationship curve and the stress accumulation curve, and predict the change trend of the sintering trolley.

[0031] The stability adjustment module is used to adjust the working mode of the sintering trolley according to the change trend of the sintering trolley and set a collaborative adjustment plan.

[0032] When measuring the temperature related to the sintering trolley, an infrared thermal imager arranged in an array is used to detect the trolley's traveling path in real time. Infrared thermal imagers are set at the head, middle section, and tail of the sintering trolley. According to the continuous movement of the trolley, the temperature changes along the trolley's traveling route are converted into a temperature cloud map. The core of the temperature cloud map is the data value, which represents the value at different positions at relative time points. This value can be the instantaneous value at a time point or the average value and maximum value at a certain position within a certain period of time, etc. It is mainly used to show whether the current temperature will cause changes in the curvature radius of the side plates and strain accumulation of the grate bars on the sintering trolley under the corresponding thermal forces, resulting in parts of these structures exceeding the maximum elastic change, leading to excessive deformation damage to the structures on the sintering trolley, which is not conducive to subsequent normal operation.

[0033] The thermal stress generated by the measurement is mainly detected by using a device containing a laser displacement sensor array and a strain gauge network at positions on the sintering trolley where there is no sintering layer covering. The deformation of relevant structures is detected, and the corresponding thermal stress is identified. The thermal stress described here represents the thermal expansion of the structure due to temperature difference. When these structures expand, they will show certain bending or deformation. If the deformation exceeds the normal elastic modulus, the structure will be damaged. At this time, the displacement sensor is used to identify the deformation generated by these structures, and based on the temperature difference, the thermal stress generated by the expansion at this time is identified. Then, these data are combined to facilitate subsequent analysis of the temperature and the cumulative distribution of relative thermal stress to find out whether the parameters such as the hot blowing time and temperature set currently will affect the structure of the sintering trolley itself.

[0034] For the thickness distribution of the sintering layer, a 3D line laser scanner and a thermal radiometer can be used to achieve the spatial mapping of the thickness distribution and temperature gradient of the sintering layer, so as to obtain the temperature gradient of the sintering layer during its operation at the set thickness, which is convenient for subsequent verification of relevant thermal stress and its influence on the operation of the sintering trolley.

[0035] In an embodiment of the present invention, when generating the temperature cloud map of the production trolley's traveling path, it is necessary to mark the temperature collected on the trolley's traveling path, and according to the specific situation of the trolley's movement, identify the temperature cloud maps generated under different operating times, and according to the manifestation form of the temperature cloud map, identify the characteristics of the temperature cloud map at different positions and times, and use these characteristics in the form of an image layer.

[0036] For the temperature cloud map, after interpolating the collected two-dimensional temperature field, the used temperature cloud map is obtained. For example, when inputting the currently collected temperature value and the coordinates corresponding to the temperature value, after generating a grid of coordinates and temperature, the value is output to obtain a temperature cloud map containing the temperature value and coordinates.

[0037] Such asFigure 2 As shown, the implementation method of the temperature detection module includes: setting multiple detection points at equal intervals on the traveling path of the trolley, obtaining the temperature values and coordinate values of each detection point, and setting a temperature cloud map matrix according to the temperature values and coordinate values of each monitoring point. At this time, the described temperature cloud map matrix represents that the temperature cloud map uses a matrix form.

[0038] At the same time, an infrared thermal imager array is deployed at equal intervals in the traveling direction of the trolley for the set detection points, and multiple detection positions are set in the vertical direction to cover the bottom to the top of the sintering layer; for the detection points set at equal intervals in the traveling direction of the trolley, a detection point can be set every 20 cm, or a larger or smaller interval can be used to identify the working conditions of the sintering trolley.

[0039] Compare the temperature cloud map matrices under different sintering layer thickness distributions, identify the temperature distribution types of the temperature distribution forms, and determine the associated description factors for each temperature distribution type.

[0040] At this time, when describing the different sintering layer thicknesses and temperature distribution situations, it will be divided into multiple intervals according to the sintering layer thickness, and the temperature distribution forms on the sintering car path under each interval will be identified. For example, the temperature distribution types include ring distribution, band distribution, and gradient distribution, etc. Then, according to the occurrence situations of this temperature distribution type under different thicknesses of the sintering layer in the historical data, and combined with the temperature at the corresponding position in the current temperature cloud map matrix, the current temperature distribution type is selected. After that, the associated description factors of the temperature distribution type are set. The associated description factors are mainly used to explain the current temperature distribution type and the temperature conditions presented at the corresponding positions. Then, according to this associated description factor, the uniformity and non-uniformity of the temperature to be described can be directly found, and then the maximum temperature difference is calculated to identify the generated thermal stress.

[0041] The implementation method of determining the associated description factors for each temperature distribution type can also include: identifying the color codes corresponding to each temperature classification type, converting the positions corresponding to each temperature distribution type into corresponding color regions, performing linear gradient on each color region, and determining the intersection regions of each color region; for the linear gradient, interpolation is performed between adjacent color regions to describe the boundaries between the current different color regions.

[0042] Use the area and boundary length of the intersection regions of each color region as the associated description factors for each temperature distribution type.

[0043] At this time, it is to further describe the situation of the current temperature distribution described by the associated description factor, so as to know the relative situation of the actual distribution under the current temperature distribution type, identify the corresponding temperature range when the current sintering trolley is moving under different sintering layer thicknesses, and finally more comprehensive description information can be obtained, which is convenient for the staff to timely control the working state of the sintering trolley.

[0044] For example, Table 1 can be used to describe the current temperature distribution type.

[0045] Table 1. Schematic Table of Temperature Distribution Types

[0046]

[0047] In Table 1, the possible distribution situations of the current temperature distribution type are described, as well as the corresponding sintered layer thickness for each situation. After describing the content represented, the corresponding characteristic values are displayed for subsequent related calculations. The content shown here does not represent all situations in actual identification of the sintering table machine, but only explains the main possible situations and types.

[0048] Use the associated description factors of each temperature distribution type to set characteristic quantization indicators, and use the characteristic quantization indicators to calculate the maximum temperature difference and thermal stress at each detection point position.

[0049] For the characteristic quantization indicators, the relative square difference is used to describe the overall temperature difference. The part with a relatively large temperature difference in a certain area is identified, and the maximum temperature difference and related thermal stress values that can be obtained at this position are calculated. The relative square difference is the difference between the values of these points and the average value at a certain position. The larger this value, the more obvious the temperature gradient change in this part, and the more likely it is to have excessive expansion and excessive deformation.

[0050] The thermal stress is expressed as: ; where represents the thermal stress, represents the coefficient of thermal expansion of the material, represents the elastic modulus, represents the Poisson's ratio, represents the geometric shape factor, which is set according to the currently mainly identified structure. For example, for the railing on the sintering trolley, it is taken as 1.2, and for the grate bar, it is taken as 0.8; represents the temperature difference. It can be directly found that the temperature difference existing in the corresponding structure affects the thermal stress distribution. Then, by identifying the temperature difference, the parts with excessive thermal stress in some structures can be found to verify whether the corresponding structures are prone to excessive deformation problems.

[0051] Perform multi-constraint correction on the thermal stress at each detection point position, identify the characteristic interval of the thermal stress after multi-constraint correction, and generate a temperature-stress relationship curve according to the characteristic interval.

[0052] When performing multi-constraint correction, introduce the current sintered layer thickness and the standard thickness to determine the characteristic interval of the current thermal stress after correction and set the subsequent relationship curve.

[0053] For example, the thermal stress after multi-constraint correction Expressed as: wherein, represents the sintering layer thickness, represents the standard thickness of the sintering layer, represents the empirical proportionality coefficient, indicating the influence weight of the sintering layer thickness on the thermal stress. A value of 0.15 can be adopted to represent the relative weight between the sintering layer thickness and the thermal stress; represents the correction coefficient, which is used to describe the non - linear relationship between the change in the sintering layer thickness and the thermal stress. In order to fit the error under the multi - constraint corrected thermal stress, this coefficient can adopt a value of 0.6 to describe the situation of using the sintering layer thickness to correct the thermal stress; At this time, it can be known what method will be adopted to represent the values of the thermal stress at different sintering layer thicknesses.

[0054] As shown in Table 2, the characteristic intervals of the multi - constraint corrected thermal stress can be represented in the following way.

[0055] Table 2. Schematic Table of Characteristic Intervals

[0056]

[0057] That is, after obtaining the change in the corrected thermal stress in the corresponding area and the corresponding temperature, the relevant situations of the thermal stress are classified by characteristics, and then the data under each characteristic interval are displayed to obtain the temperature - stress relationship curve. In the temperature - stress relationship curve, when describing any one of the linear elastic region, plastic transition region, and non - linear creep region, the slopes expressed by the curves are all different.

[0058] For example, the slope of the linear elastic region is usually large and remains constant, reflecting the normal deformation process of the material within the elastic range. In this process, the slope value is generally equal to the product of the elastic modulus of the material itself and the material expansion coefficient. This value generally remains relatively stable with the increase of the thermal stress. After the mechanism of the trolley in this region completes the processing of the corresponding material, the deformation generated by the stress will be completely restored without residual deformation. In this case, it is mainly used to evaluate the stiffness and elastic properties of the material.

[0059] The slope of the plastic transition region begins to gradually change, indicating that plastic deformation begins to occur in the corresponding structure on the trolley, and its stiffness gradually decreases. In this case, the stress increase rate begins to slow down, and at the same time, there will be some strains that cannot be restored after the work is completed, resulting in residual deformation.

[0060] The slope of the non - linear creep region changes with time and gradually decreases with the change of stress, and then slowly tends to a stable form. This region is generally used to evaluate the long - term stability and creep performance of the trolley structure.

[0061] After that, according to the different forms of these three expressions, relevant characteristic points are extracted from the temperature-stress relationship curve, such as turning points, fracture points, and points where the display values differ due to the corresponding hysteresis effect. Analyze the conditions of these points to obtain the characteristic interval of the current temperature-stress relationship curve, so as to complete the analysis of the corresponding curve. In the temperature-stress relationship curve, the temperature can be used as the curve identifier, and the thermal stress and strain corresponding to this curve can be used as the coordinates represented by the curve. Alternatively, the temperature and stress can be used as the coordinates represented by the curve to reflect the thermal stress distribution existing on the current sintering trolley under different temperature distributions.

[0062] Therefore, the implementation method of identifying the characteristic interval of the thermal stress after multi-constraint correction and generating the temperature-stress relationship curve according to the characteristic interval includes: obtaining the stress relationship curve corresponding to the corrected thermal stress, and sequentially identifying the yield point, creep limit point, and slope value on the stress relationship curve; the yield point refers to the critical point where the material changes from elastic deformation to plastic deformation. After this point, even if the stress no longer increases, the material will continue to undergo permanent deformation. The yield point can be identified by the 0.2% offset method, direct observation method, and numerical analysis method.

[0063] The stress relationship curve represents the relationship curve between thermal stress and strain. This curve indicates whether the elastic modulus changes when the stress changes, so as to determine whether there is a corresponding structural change on the current sintering trolley. The corresponding formula for strain is to divide the content calculated by the thermal stress by the elastic modulus; and identify which of the linear elastic region, plastic transition region, and non-linear creep region the corresponding structure belongs to under the current temperature change through the stress change curve.

[0064] The 0.2% offset method is to draw a straight line parallel to the slope of the initial line, but this line passes through the 0.2% point of the stress relationship curve, that is, the part representing 0.2% of the stress on the vertical coordinate. Then the intersection point of this straight line and the stress relationship curve is the identified yield point.

[0065] The direct observation method is to find the obvious inflection point or area in the stress relationship curve. This part usually indicates the start of yielding, and this inflection point is regarded as the yield point.

[0066] The numerical analysis method is to differentiate the slope value on the stress relationship curve and find the position where the slope changes significantly. When there is a position with a significant change, the point represented by this position is the yield point.

[0067] The creep limit point refers to the maximum stress that a material can withstand without causing excessive creep strain under given temperature and time conditions. The creep limit point identified here is set by testing the material of the corresponding structure on the current sintering trolley and finding the point corresponding to the maximum stress value that the material can withstand under normal use. This limit point can be represented by the maximum stress value shown by the current sintering trolley in historical data during long-term operation. It should be noted that this maximum stress value represents the sintering trolley under normal operation, rather than directly finding the maximum value.

[0068] Determine the slope value at the adjacent position of the yield point and calculate the yield similarity coefficient between this yield point and the historical data; the yield similarity coefficient is calculated using the Pearson correlation coefficient between the slope values of the adjacent data points of the yield point and the slope values at the adjacent positions of the yield points in the historical data to obtain the yield similarity coefficient. This coefficient indicates whether the adjacent points are consistent with the historical data when the current yield point occurs. If the final value of this yield similarity coefficient is small, it means that the linear relationship between the slope value at the adjacent position of the current yield point and the slope value in the historical data is weak, that is, the adjacent deformation behavior of the current yield point is inconsistent with the historical data. This may mean that the material properties have changed or the conditions of the two comparisons are different. At this time, this coefficient will be recorded and a new data mapping will be established. If the yield similarity coefficient is large, it indicates that the slope value at the adjacent position of the yield point in the current experiment has a strong linear relationship with the slope value in the historical data.

[0069] If the value of the yield similarity coefficient is greater than the expected yield coefficient, record the relative distance between the current yield point and the creep limit point, and use the yield point and the creep limit point to divide the characteristic interval of the current thermal stress into a linear elastic region, a plastic transition region, and a non-linear creep region. According to the divided characteristic intervals, a temperature-stress relationship curve can be generated to obtain the manifestation form of the current temperature difference and the direct relationship shown by the thermal stress under different characteristics, and relevant data can be adjusted and processed based on this.

[0070] If the yield similarity coefficient is less than the expected yield coefficient, the relative distance between the current yield point and the creep limit point is added as a new mapping relationship to the database. The expected yield coefficient takes into account the yield points with positive correlation. For example, a value of 0.3 can be used, and the yield points greater than this value are used. Generally, the value of the yield similarity coefficient ranges from -1 to 1. The closer its value is to 1, the more obvious the positive correlation is. When it is close to -1, it shows a negative correlation or no direct correlation. As for the method of dividing the characteristic interval of the current thermal stress into a linear elastic region, a plastic transition region, and a non-linear creep region, the yield point is used as a dividing point to identify the linear elastic region and the plastic transition region. Taking the stable curve close to the creep limit point as the standard, the plastic transition region and the non-linear creep region are obtained. Recording the relative distance can intuitively show how much stress range is available for the material before entering dangerous creep deformation. A larger distance means a higher safety margin, allowing a greater operating margin without immediately causing structural failure.

[0071] The finally obtained temperature-stress relationship curve can represent the situations of the parapet and grate bar under different working conditions, preventing excessive structural damage and affecting the operation of the sintering trolley itself.

[0072] For the temperature-stress relationship curve, it shows the stress change when the temperature changes at a certain position on the trolley's traveling path, and the generated curves are separately represented according to the three types represented by the characteristic intervals. That is, taking the value of the temperature changing with time at a certain position as the abscissa and the value of the thermal stress changing with time as the ordinate for display; or using temperature as the label of this relationship, time as the abscissa, and thermal stress as the ordinate for display, setting curves under multiple temperatures or temperature differences and using them as the temperature-stress relationship curve at this time; or taking the temperature values of all position points on the trolley's traveling path as the abscissa and the thermal stress of all position points as the ordinate to describe the distribution relationship in relative space, and taking the average value of the values at these position points per unit time and generating multiple curves marked with time to display the manifestation form of the temperature-stress relationship curve at the corresponding position.

[0073] In an embodiment of the present invention, the equipment conditions of the sintering trolley represent the specific equipment composition of the current sintering trolley. The equivalent force identification processes the superposition of the thermal stress distribution and the deformation corresponding to the thermal stress, that is, to identify whether there are corresponding regions on the current sintering trolley for the stress changes of any one of the linear elastic region, the plastic transition region, and the non-linear creep region, and to identify the parts where the deformation concentration and the stress concentration accumulate in these regions to find the position most prone to excessive deformation.

[0074] Such as Figure 3As shown in the figure, the implementation method of the deformation analysis module includes: according to the obtained temperature-stress relationship curve, identifying the stress change regions existing in the temperature-stress change curve, and finding out the parts where deformation will concentrate and the parts where stress will concentrate and accumulate in these change regions.

[0075] Compare the thermal stress magnitudes of the sintering trolley in different cycles for the corresponding stress change regions, identify and record the occurrence positions of the residual stress and the residual stress cumulative effect, and obtain stress analysis data according to the occurrence positions of the cumulative effect. The stress analysis data includes the stress magnitude and the distribution range.

[0076] For the cumulative effect, after the thermal stress generates strain, the positions where the residual stress appears and accumulates will be identified through the curve data on the plastic transition zone existing in the temperature-stress relationship curve. For the non-linear creep zone, which is the change situation after the plastic transition zone, the residual stress will also appear at this position. Then, at this time, the identification and processing will be carried out for the occurrence of the residual stress accumulation to find out the deformation concentration region under the premise of the same equipment operation, and to identify the change situation of the stress accumulation.

[0077] Identify the change range and the size of the distribution range of the stress values in the stress analysis data; at this time, identify the distribution situation of the stress value's value and position under a specific operation range, such as the gap between the maximum value and the minimum value generated by the stress value within the corresponding temperature range. This range can directly show the stress situation received by the structure on the sintering trolley, and whether this stress situation can cause problems such as structural fatigue damage and premature equipment failure; as for the distribution range, it is to evaluate the area where the change range of the same stress value is distributed on the current sintering trolley, which is used to express the distribution situation of the stress value in terms of space. Record the relative distance between the center points of each range under the corresponding change range and distribution range. Take the frequency difference of the corresponding values of each range center point in the historical data as the relative distance between the center points of each range; the corresponding value of each range center point represents the frequency of the stress value at this point in the historical data, and the difference between these frequencies is used to obtain the relative distance between different range centers.

[0078] It should be noted that the center point of the variation range is the value of the center point of the stress value variation range, that is, the value located at the center of a range containing the maximum and minimum stress values. The center point of the distribution range describes the value at the center of the area represented by this position under the relative position distribution range. The stress values ​​represented by these values ​​are calculated in the historical data. The frequency is calculated, and the relative distance between these center points is expressed by the frequency difference. By calculating the center point of the stress value variation range and the distribution range, and associating it with the frequency in the historical data, the stress variation and spatial distribution can be quantitatively described. This helps to more accurately understand the stress response of the structure under different operating conditions. By comparing the relative distances of the center points of different ranges (based on the frequency difference), the areas with the most intense stress concentration or changes can be identified. These areas are often high-risk areas for structural fatigue damage, and are therefore the focus of monitoring and maintenance.

[0079] The relative distances of the center points of each range are checked. If the relative distances of the center points of each range are not within the processing range, the relative distances with the largest difference each time are eliminated, and the standard time for residual stress to be generated by the center points of the remaining ranges is recorded. The processing range is used to measure the rationality of the relative distances between the centers of each range. If it exceeds this range, it is considered that the difference between the centers of the ranges currently quantified by the frequency is too large, and it is not convenient to directly compare whether the stresses at the corresponding positions overlap and accumulate. The standard time is similar to an absolute time point, which is a standard time point for measurement based on the working time of the sintering trolley. It also indicates the relative position of the time point in the corresponding working cycle.

[0080] The standard time for residual stress to be generated at the center point of each remaining range is used to find the relative co-occurrence probability of the standard time under different cycles, and when the relative co-occurrence probability is greater than the preset threshold, the area where the center point of the corresponding range is located is set as the deformation concentration area.

[0081] Finding the relative co-occurrence probability of the standard time under different cycles is to find the probability of the length of the time period in which residual stress appears at this position at this time point relative to the normal working calculation, and the probability of the stress value at the corresponding position, that is, the conditional probability value that satisfies both the probability of the time length and the probability of the stress value. This value is used as the relative co-occurrence probability at this time, and when the relative co-occurrence probability is greater than the average value of the corresponding co-occurrence probability in the historical data, the corresponding area is recorded as a deformation concentration area, and these areas will show concentrated and obvious stress accumulation.

[0082] Afterwards, the deformation concentration area is detected and screened to determine whether the stress distribution in this deformation concentration area is similar and what the strain energy density of the area is, so as to obtain the subsequent processing method for this position.

[0083] The implementation methods of the stress accumulation curve include: based on the obtained deformation concentration region, comparing the strain energy density coefficient and the stress distribution similarity index of the corresponding deformation concentration region under different sintering layer thickness distributions and temperatures.

[0084] Based on the stress distribution similarity index pairs, data screening is carried out, and the screened data is combined into a stress accumulation model, and the output of the stress accumulation model is used as the stress accumulation curve.

[0085] The strain energy density coefficient can be expressed as: ; where represents the strain, that is, the degree of material deformation in the case of thermal stress; represents the strain energy density coefficient, represents the critical strain energy density when the material yields, which can be measured through the material tensile test experiment. This value can be used to judge the plastic deformation risk of the current deformation concentration region. When half of the thermal stress or strain exceeds 80% of the material's own limit, plastic deformation is likely to occur. Generally, a safety margin of 10%-20% is selected for the limit that the material itself can bear. At this time, a safety margin of 20% is selected to judge whether the current strain energy density coefficient itself can be greater than 80% of the critical strain energy density. If it is greater, it means that the stress generated at the current position will affect the material itself, causing damage to the corresponding structure on the sintering trolley.

[0086] For the stress distribution similarity index, the calculation method of the Pearson correlation coefficient can be adopted, and the deformation concentration region is calculated with the corresponding value in the historical data. When the stress distribution similarity index is greater than 0.85, it is considered that the data in this region passes the screening.

[0087] After that, according to the remaining data points, a stress accumulation model is established, ; where represents the output of the stress accumulation model, represents the number of time periods, and the value range of i is from 1 to n; represents the average thermal stress in the time period i, represents the reference stress, which is 80% of the material fatigue limit and can be taken as 120 MPa; represents the thermal stress action time in the time period i, represents the material sensitivity index, and here a value of 3.2 is taken.

[0088] After that, according to the content output by these data, a curve representing the accumulation of stress over time is obtained. As shown in Table 3, there are the following results for the positioning of the deformation concentration region.

[0089] Table 3. Example table of deformation concentration region

[0090]

[0091] It is found in Table 3 that the parapet welds and the bearing seats are deformation concentration areas, and the cooling strategy needs to be optimized preferentially, and the stress level in the middle of the grate bars is within the safe range; this part of the data will be shown in the areas where obvious deformation accumulates, and whether these areas need repair and related treatment to improve the judgment and handling of the specific working content of the sintering trolley by the whole system.

[0092] In one embodiment of the present invention, the combined analysis module will synthesize the data corresponding to the two curves by combining the changes that these thermal stresses can cause to the current structure and the specific situation under actual thermal control, so as to describe the main data factors when the sintering trolley shows a change trend.

[0093] The implementation method of the combined analysis module includes: constructing a mapping relationship between the temperature-stress relationship curve and the stress accumulation curve to form a relationship mapping table; using the relationship mapping table to perform finite element difference on the residual stress during the operation of the sintering trolley to obtain the difference coefficient; at this time, the finite element difference is to calculate the data under the same conditions after mapping, such as the same temperature, calculate the error related to its stress, and regard this error as the difference coefficient.

[0094] If there is a temperature deviation, calculate the thermal stress existing under this deviation, obtain the covariance of this thermal stress in space, and calculate the residual stress under the corresponding covariance to obtain the output relative error.

[0095] According to the obtained difference coefficient, determine the relative error corresponding to the residual stress, and use the relative error as the change trend of the sintering trolley. The residual stress is compared with the theoretically calculated stress to determine the magnitude of the current residual stress.

[0096] After mapping the temperature-stress relationship curve and the stress accumulation curve using the relationship mapping table, the distribution of these residual stresses can be shown as the content of Table 4.

[0097] Table 4. Example of Residual Stress Distribution

[0098]

[0099] In Table 4, the existing residual stress is associated with other data, and mapped with temperature, residual pressure, and the coordinates of the position where the residual stress is identified, so as to describe the distribution of the residual stress, and determine the relative error that can be generated at different temperatures, so as to describe the overall change trend of the current sintering trolley under the comprehensive influence of this temperature and stress.

[0100] In one embodiment of the present invention, such as Figure 4As shown in the figure, the implementation method of the stable adjustment module includes: recording the deformation influence range existing under the change trend, and determining the event information of each deformation occurrence and the preset trigger conditions of each event information according to the deformation influence range; based on the preset trigger conditions of each event information, verifying the overall state of each component in the current sintering trolley.

[0101] The deformation influence range represents the components within the spatial range around the currently deformed part, as well as a list of these components; for example, if the middle part of the guard plate is deformed, then its influence range includes at least the adjacent 3 grate bars. At this time, a list of its surrounding components and relevant detection data will be obtained with this guard plate as the center point to identify whether this guard plate will affect the local sintering layer thickness or cause large thermal stress changes in other components, resulting in a reduction in service life.

[0102] Each event information represents the temperature, thermal stress, strain energy density, temperature distribution, and characteristic intervals corresponding to temperature measured in the temperature-stress relationship curve and stress accumulation curve, etc. The preset trigger condition for each event information is to find out whether the currently measured data can trigger an alarm partially. If so, the content corresponding to the triggered alarm will be used as the overall state of each component.

[0103] As shown in Table 5, examples of each event can be represented as follows.

[0104] Table 5. Schematic Diagram of Typical Events

[0105]

[0106] This table shows the influence range and trigger conditions of the influence situation that occurs in the sintering trolley under relevant circumstances. When similar situations occur, the positions of these components and the corresponding triggered situations will be used as the corresponding states of each component at this time, which is convenient for subsequent selection of how to adjust and control the sintering trolley according to the states of each component.

[0107] Construct each policy sub-model corresponding to each event information, and combine each policy sub-model with the overall state of each component in the sintering trolley to generate a policy control model corresponding to the change trend.

[0108] Each policy sub-model represents a description method for processing the overall state of a single component, while the policy control model is a method for overall control of multiple components.

[0109] Use the policy control model to predict the next event information under the change trend, and compare the overall state of the next event information with the overall state of each component in the current sintering trolley to select the collaborative adjustment plan in the policy control model.

[0110] For the policy sub - model, it will describe each component according to the components corresponding to the event information, and then combine these contents to obtain the policy control model.

[0111] That is, for the policy sub - model, according to the corresponding event information, obtain the weights of the event information in the current policy sub - model, and combine the policy sub - models into a policy control model according to the weights corresponding to the event information.

[0112] Each policy sub - model represents that under the condition of a single event information and a preset trigger condition, the corresponding event information is calculated with historical data to obtain the recommended solution corresponding to the policy sub - model. Then, the data that needs attention in each component is combined to obtain a comprehensive policy control model. The policy control model will comprehensively summarize the recommended solutions corresponding to all policy sub - models to select the final processing solution at this time.

[0113] As shown in Table 6, the solutions in the policy control model can be represented as follows.

[0114] Table 6. Example of the policy control model solution

[0115]

[0116] In Table 6, T represents the temperature of the corresponding component, σ represents the stress of the corresponding component, δ represents the deformation of the corresponding component, and v represents the speed of the corresponding component. Then, according to the parts that need to be adjusted for these components, a combined solution of relevant recommendations will be generated from these parts to be adjusted. This combined solution will be regarded as the policy control model used at this time to make corresponding adjustments to the subsequent overall control of the sintering trolley.

[0117] The implementation methods for selecting the collaborative adjustment solution in the policy control model also include: taking temperature and thermal stress as the main factors, using the event information as the input vector to construct an event vector matrix corresponding to the event information; the event vector matrix represents combining the currently input event information in matrix form to determine the matrix for expressing the content of a single event information; the event vector matrix will be calculated as the overall state of each component to assist in screening out the collaborative adjustment solution.

[0118] Calculate the state transition probabilities of each element in the event vector matrix, and determine the next event information according to the state transition probabilities; at this time, the part with the largest value in the state transition probabilities will be used as the predicted next event information.

[0119] Calculate the difference metric between the event vector matrix for calculating the next event information and the current event vector matrix, and select a collaborative adjustment scheme according to the difference metric. The difference metric represents that after obtaining the squared ratio of the difference of each element in the event vector matrix, the squared ratio is summed according to the number of elements existing in the event vector matrix to obtain the comparison result of the overall state of the next event information and the overall state of each component in the current sintering trolley; finally, select the corresponding collaborative adjustment scheme from the database according to this difference metric. The selection can be based on the comprehensive value of the difference metric. Calculate the correlation coefficient between the difference metric and the corresponding scheme in the database, such as the calculation method of the Pearson correlation coefficient, and use the content of the scheme with the largest correlation coefficient value as the collaborative adjustment scheme to be used.

[0120] As Figure 5 shown, the present invention also provides an intelligent control method for a sintering trolley based on industrial automation technology, including: S1, obtaining the equipment working information of the sintering trolley through devices such as sensors.

[0121] S2, generating a temperature cloud map based on the equipment working information, identifying the temperature distribution form under the temperature cloud map, and calculating the maximum temperature difference and thermal stress.

[0122] S3, identifying the deformation concentration area corresponding to the thermal stress and establishing a stress accumulation curve.

[0123] S4, constructing a mapping relationship between the temperature and the stress accumulation curve to predict the change trend of the sintering trolley.

[0124] S5, adjusting the working mode according to the change trend of the sintering trolley and setting a collaborative adjustment scheme.

[0125] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention, and still be covered by the protection scope of the present invention.

Claims

1. An intelligent control system for a sintering trolley based on industrial automation technology, characterized in that: include: A data acquisition module is used to obtain the equipment working information of the sintering trolley in all working cycles. The equipment working information includes the sintering layer thickness distribution, temperature and thermal stress when the sintering trolley is working; The temperature detection module is used to generate a temperature cloud map of the trolley's travel path according to the temperature of the sintering trolley, compare the temperature cloud map characteristics under different sintering layer thickness distributions, identify the temperature distribution form, calculate the maximum temperature difference and thermal stress under the corresponding temperature distribution form, and set the temperature-stress relationship curve; The deformation analysis module is used to identify the equivalent force according to the equipment conditions of the sintering trolley and identify the deformation concentration area on the sintering trolley; Compare the distribution of thermal stress in the deformation concentration area under different sintering layer thickness distribution and temperature, and establish the stress accumulation curve; Combined analysis module, used to identify the residual stress of the sintering trolley during operation according to the temperature-stress relationship curve and the stress accumulation curve, and predict the change trend of the sintering trolley; The stable adjustment module is used to adjust the working mode of the sintering trolley according to the changing trend of the sintering trolley and set up a coordinated adjustment plan.

2. According to claim 1, the intelligent control system for sintering trolley based on industrial automation technology is characterized in that: The implementation methods of the temperature detection module include: Multiple detection points are set at equal intervals on the trolley's travel path, the temperature value and coordinate value of each detection point are obtained, and a temperature cloud map matrix is ​​set according to the temperature value and coordinate value of each monitoring point; Compare the temperature cloud map matrix under different sintering layer thickness distributions, identify the temperature distribution type of the temperature distribution form, and determine the associated description factors of each temperature distribution type; Use the associated description factors of each temperature distribution type to set the characteristic quantification index, and use the characteristic quantification index to calculate the maximum temperature difference and thermal stress at each detection point; The thermal stress at each detection point is corrected by multiple constraints, the characteristic interval of the thermal stress after the multi-constraint correction is identified, and the temperature-stress relationship curve is generated according to the characteristic interval.

3. The intelligent control system for a sintering trolley based on industrial automation technology according to claim 2 is characterized in that: The implementation method of determining the associated description factor of each temperature distribution type also includes: Identify the color code corresponding to each temperature classification type, convert the position corresponding to each temperature distribution type into a corresponding color area, perform linear gradient on each color area, and determine the intersection area of ​​each color area; The area and boundary length of the intersection region of each color region are used as the associated description factors of each temperature distribution type.

4. The intelligent control system for a sintering trolley based on industrial automation technology according to claim 2 is characterized in that: The implementation method of identifying the characteristic interval of thermal stress after multi-constraint correction and generating a temperature-stress relationship curve according to the characteristic interval includes: Obtain a stress relationship curve corresponding to the corrected thermal stress, and identify the yield point, creep limit point and slope value on the stress relationship curve in turn; Determine the slope value adjacent to the yield point, and calculate the yield similarity coefficient between the yield point and the historical data; If the yield similarity coefficient is greater than the expected yield coefficient, the relative distance between the current yield point and the creep limit point is recorded, and the characteristic interval of the current thermal stress is divided into a linear elastic zone, a plastic transition zone, and a nonlinear creep zone using the yield point and the creep limit point; If the yield similarity coefficient is smaller than the expected yield coefficient, the relative distance between the current yield point and the creep limit point is added to the database as a new mapping relationship.

5. The intelligent control system for sintering trolley based on industrial automation technology according to claim 1 is characterized in that: The implementation methods of deformation analysis module include: According to the obtained temperature-stress relationship curve, the stress change area existing in the temperature-stress change curve is identified; Compare the thermal stress magnitude of the sintering pallet in the stress change area under different cycles, identify and record the occurrence positions of residual stress and residual stress cumulative effect, and obtain stress analysis data according to the occurrence position of cumulative effect. The stress analysis data includes stress magnitude and distribution range. Identify the variation range and distribution range of stress values ​​in stress analysis data, record the relative distance between the center points of each range under the corresponding variation range and distribution range, and use the frequency difference of the corresponding values ​​of the center points of each range in the historical data as the relative distance between the center points of each range; The relative distances of the center points of each range are checked. If the relative distances of the center points of each range are not within the processing range, the relative distances with the largest difference are eliminated, and the standard time for residual stress to be generated by the center points of the remaining ranges is recorded. The standard time for residual stress to be generated at the center point of each remaining range is used to find the relative co-occurrence probability of the standard time under different cycles, and when the relative co-occurrence probability is greater than the preset threshold, the area where the center point of the corresponding range is located is set as the deformation concentration area.

6. The intelligent control system for sintering trolley based on industrial automation technology according to claim 1 is characterized in that: The implementation of stress accumulation curve includes: Based on the obtained deformation concentration area, the strain energy density coefficient and stress distribution similarity index of the corresponding deformation concentration area under different sintering layer thickness distribution and temperature are compared; Data are screened based on the stress distribution similarity index, the screened data are combined into a stress accumulation model, and the output of the stress accumulation model is used as a stress accumulation curve.

7. The intelligent control system for a sintering trolley based on industrial automation technology according to claim 1 is characterized in that: The implementation methods of the combination analysis module include: A mapping relationship is constructed between the temperature-stress relationship curve and the stress accumulation curve to form a relationship mapping table; the relationship mapping table is used to perform finite element difference on the residual stress when the sintering trolley is working to obtain the difference coefficient; According to the obtained differential coefficient, the relative error corresponding to the residual stress is determined, and the relative error is used as the change trend of the sintering trolley.

8. The intelligent control system for a sintering trolley based on industrial automation technology according to claim 1 is characterized in that: The implementation methods of the stability adjustment module include: Record the deformation influence range under the change trend, and determine the event information of deformation and the preset trigger conditions of each event information according to the deformation influence range; verify the overall status of each component in the current sintering trolley based on the preset trigger conditions of each event information; Construct each strategy sub-model corresponding to each event information, and combine each strategy sub-model with the overall status of each component in the sintering trolley to generate a strategy control model corresponding to the change trend; The strategic control model is used to predict the next event information under the changing trend, and the overall state of the next event information is compared with the overall state of each component in the current sintering trolley to select the coordinated adjustment plan in the strategic control model.

9. The intelligent control system for sintering trolley based on industrial automation technology according to claim 8 is characterized in that: The implementation of the coordinated adjustment scheme in the selection strategy control model also includes: Focusing on temperature and thermal stress, the event information is used as the input vector to construct the event vector matrix corresponding to the event information; Calculate the state transition probability of each element in the event vector matrix, and determine the next event information based on the state transition probability; The differential metric between the event vector matrix of the next event information and the current event vector matrix is ​​calculated, and a collaborative adjustment scheme is selected according to the differential metric.

10. An intelligent control method for a sintering trolley based on industrial automation technology, characterized in that: include: S1, obtaining the equipment working information of the sintering trolley through the sensor equipment; S2, generating a temperature cloud map based on the equipment working information, identifying the temperature distribution form under the temperature cloud map, calculating the maximum temperature difference and thermal stress, and setting the temperature-stress relationship curve; Setting the temperature-stress relationship curve includes: Multiple detection points are set at equal intervals on the trolley's travel path, the temperature value and coordinate value of each detection point are obtained, and a temperature cloud map matrix is ​​set according to the temperature value and coordinate value of each monitoring point; Compare the temperature cloud map matrix under different sintering layer thickness distributions, identify the temperature distribution type of the temperature distribution form, and determine the associated description factors of each temperature distribution type; Use the associated description factors of each temperature distribution type to set the characteristic quantification index, and use the characteristic quantification index to calculate the maximum temperature difference and thermal stress at each detection point; Perform multi-constraint correction on the thermal stress at each detection point, identify the characteristic interval of the thermal stress after multi-constraint correction, and generate a temperature-stress relationship curve according to the characteristic interval; S3, identifying the deformation concentration area under the corresponding thermal stress and establishing the stress accumulation curve; S4, construct the mapping relationship between temperature and stress accumulation curve, identify the residual stress when the sintering trolley is working, and predict the change trend of the sintering trolley; A mapping relationship is constructed between the temperature-stress relationship curve and the stress accumulation curve to form a relationship mapping table; a finite element difference is performed on the residual stress when the sintering trolley is working using the relationship mapping table to obtain a difference coefficient; According to the obtained differential coefficient, the relative error corresponding to the residual stress is determined, and the relative error is used as the change trend of the sintering trolley; S5, adjust the working mode according to the changing trend of the sintering trolley and set up a coordinated adjustment plan.

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