Sintering pallet intelligent control system and method based on industrial automation technology

Abstract

The invention relates to the technical field of sintering machine control, in particular to a sintering pallet intelligent control system and method based on the industrial automation technology, and the system comprises a data collection module, a temperature detection module, a deformation analysis module, a combination analysis module and a stability adjustment module. The method comprises the following steps: obtaining sintering layer thickness distribution, temperature and thermal stress when a sintering pallet works; according to the temperature of the sintering trolley, generating a temperature cloud picture of a trolley advancing path, comparing temperature cloud picture characteristics under different sintering layer thickness distributions, and setting a temperature-stress relation curve; identifying a deformation concentration area on the sintering trolley, comparing thermal stress distribution of the deformation concentration area, and establishing a stress accumulation curve; predicting the variation trend of the sintering pallet according to the temperature-stress relation curve and the stress accumulation curve; according to the change trend of the sintering pallet, a cooperative adjustment scheme is set; the stability and efficiency of the sintering process are achieved, and the safety of equipment work is improved.

Description

Technical Field

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

[0002] In the existing industrial automation field, sintering carts, as key production equipment, play a vital role in many industries such as metallurgy and ceramics. The traditional sintering cart 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 production requirements, this traditional control method has gradually exposed many shortcomings.

[0003] For example, Chinese patent publication number CN114383423A discloses an online greasing method and system for sintering trolley wheel axles, including the following steps: S10, calculating the number of theoretical position acquisition times for each trolley wheel; S20, obtaining the vertical actual minimum distance Lz1 between the vertical sensor and the circumferential wall of the trolley wheel actually measured by the vertical sensor within the theoretical position acquisition times; S30, obtaining the horizontal actual distance Lx between the horizontal sensor and the side wall of the trolley wheel actually measured by the horizontal sensor; S40, if the difference between the vertical actual minimum distance Lz1 and the theoretical standard distance Lz0 is within the preset vertical distance range, and the horizontal actual distance Lx is within the preset horizontal distance range, the greasing unit injects grease into the axle of the corresponding trolley wheel.

[0004] For example, Chinese patent publication No. CN115218670A discloses a method for assisting sintering by intermittent injection of gas and water vapor, in which gas and water vapor are periodically injected onto the surface of the sintered mixture, the gas enters the sintering material layer to burn and provide heat, and the water vapor enters the sintering material layer to react with the carbon in the solid fuel to produce water gas, thereby accelerating the combustion of the solid fuel; during the gas injection process, the duration of the gas injection in a single cycle is adjusted to control the temperature of the sintering ore zone and the combustion zone in the sintering material layer.

[0005] The existing technology shows that the current sintering trolley can be controlled according to the height difference under the actual number of collection times, and the temperature on the sintering trolley can be controlled by adjusting the number of gas cycles and duration; however, under these control methods, it is also necessary to verify the stress and strain received by the corresponding components on the current sintering trolley, and identify whether the adjustment of the temperature control method has caused excessive deformation of some components and structures, resulting in structural damage, thereby reducing the service life of some components on the sintering trolley. Summary of the invention

[0006] In order 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 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] The temperature detection module is used to generate a temperature cloud map of the sintering 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.

[0008] 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.

[0009] The combined analysis module is 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 to predict the change trend of the sintering trolley.

[0010] 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.

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

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

[0013] S3, identify the deformation concentration area under the corresponding thermal stress and establish the stress accumulation curve.

[0014] S4, construct the mapping relationship between temperature and stress accumulation curves to predict the change trend of the sintering trolley.

[0015] S5, adjust the working mode according to the changing trend of the sintering trolley and set up a coordinated adjustment plan.

[0016] The beneficial effects of the present invention are as follows: 1. The present invention obtains the equipment working information of the sintering trolley in all working cycles, and identifies the relevant temperatures according to the trolley's travel path to obtain the temperature distribution form of the sintering trolley when it is working. Then, a temperature and stress relationship curve is set, which can identify whether the material expansion caused by different temperature differences exceeds the limit of normal deformation, and link the temperature and stress, so as to realize real-time and accurate monitoring of the working state of the sintering trolley, thereby improving the accuracy and reliability of monitoring.

[0017] 2. The present invention identifies the deformation concentration area on the sintering trolley and the thermal stress distribution therein, accumulates the stress accumulation curve, and timely identifies the stress accumulation of the corresponding components on the sintering trolley, which can reduce the structural damage caused by excessive deformation accumulation. While considering its related stress accumulation, the lunar value in the corresponding range is identified at the same time, the center point of each range is identified, and the corresponding stress concentration area is found according to the time when the residual stress appears at the center point of each range, which can reduce the failure caused by excessive material deformation and improve the life of the equipment.

[0018] 3. The present invention identifies the change trend of the sintering trolley by mapping the temperature-stress relationship curve and the stress accumulation curve, and can timely discover equipment failures in the sintering trolley; based on the impact range under the change trend and the triggering conditions of the failure, a strategy control model for subsequent use is constructed, which can adaptively adjust the control method used according to the specific state of the sintering trolley, thereby improving the production efficiency and safety of the sintering trolley. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0021] Figure 2 The present invention is a flow chart of the temperature detection module of the sintering trolley intelligent control system based on industrial automation technology.

[0022] Figure 3 The present invention is a flow chart of a deformation analysis module of an intelligent control system of a sintering trolley based on industrial automation technology.

[0023] Figure 4 The invention is a flow chart of a stable adjustment module of an intelligent control system of a sintering trolley based on industrial automation technology.

[0024] Figure 5 The invention is a flow chart of an intelligent control method of a sintering trolley based on industrial automation technology. DETAILED DESCRIPTION

[0025] The embodiments of the present invention are 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 limiting the present invention. If no specific techniques or conditions are specified in the embodiments, the techniques or conditions described in the literature in the art or the product specifications are used.

[0026] See also 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 combination 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 combination analysis module, and the output end of the combination 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. The equipment working information includes the sintering layer thickness distribution, temperature and thermal stress when the sintering trolley is working.

[0028] The temperature detection module is used to generate a temperature cloud map of the sintering 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.

[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 distribution and temperature, and establish the stress accumulation curve.

[0030] The combined analysis module is 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 to predict the change trend of the sintering trolley.

[0031] 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.

[0032] When measuring the temperature related to the sintering car, infrared thermal imagers arranged in an array are used to detect the travel path of the trolley in real time. Infrared thermal imagers are set at the head, middle section and tail of the sintering trolley, and according to the continuous movement of the trolley, the temperature changes on the travel path of the trolley are converted into a temperature cloud map; the core of the temperature cloud map is the data value, which will represent the value at different positions at relative time points. This value can be the instantaneous value at the time point or the average value and maximum value at the position within a certain period of time. It is mainly used to show whether the temperature at this time will cause the structures such as the guardrails and grates on the sintering car to change the curvature radius of the guardrails and the accumulated strain of the grates under the corresponding thermal force, resulting in parts of these structures that exceed the maximum elastic change, resulting in excessive deformation damage to the structure on the sintering trolley, which is not conducive to subsequent normal work.

[0033] The thermal stress generated is mainly measured by using a device including a laser displacement sensor array and a strain gauge network to detect the deformation of the relevant structure at the position where the sintering trolley does not have a covering sintering layer, and identify the corresponding thermal stress generated. The thermal stress described at this time indicates the thermal expansion of the structure due to the temperature difference. These structures will have a certain degree of bending or deformation when expanding. 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 after identifying the thermal stress generated by the expansion at this time based on the temperature difference, these data are combined to facilitate the subsequent analysis of the cumulative distribution of temperature and relative thermal stress, to find out whether the currently set parameters such as the blowing time and temperature will affect the structure of the sintering trolley itself.

[0034] For the thickness distribution of the sintered layer, a 3D line laser scanner and a thermal radiation meter can be used to realize the spatial mapping of the thickness distribution and temperature gradient of the sintered layer; to obtain the temperature gradient of the sintered layer when it is working at the set thickness of the sintered layer, so as to facilitate the subsequent verification of the relevant thermal stress and the impact on the operation of the sintering trolley.

[0035] In one embodiment of the present invention, when producing a temperature cloud map of the trolley's travel path, it is necessary to mark the temperatures collected on the trolley's travel path, and identify the temperature cloud map generated under different operating time conditions according to the specific conditions of the trolley's travel, and identify the features of the temperature cloud map at different positions and times according to the expression form of the temperature cloud map, and use these features in the form of an image layer.

[0036] For the temperature cloud map, the collected two-dimensional temperature field will be interpolated to obtain the used temperature cloud map. For example, the currently collected temperature value and the coordinates corresponding to the temperature value are input, and after the coordinates and temperature are generated into a grid, the value is output to obtain a temperature cloud map containing the temperature value and coordinates.

[0037] like Figure 2 As shown, the implementation method of the temperature detection module includes: setting multiple detection points at equal intervals on the trolley's travel path, obtaining the temperature value and coordinate value of each detection point, and setting a temperature cloud map matrix according to the temperature value and coordinate value of each monitoring point. The temperature cloud map matrix described at this time indicates that the temperature cloud map uses a matrix form.

[0038] At the same time, the detection points set up at equal intervals are deployed with an infrared thermal imager array in the direction of the trolley's travel, and multiple layers of detection positions are set in the vertical direction to cover the sintering layer from the bottom to the top; for the detection points set up at equal intervals in the direction of the trolley's travel, one detection point can be set every 20CM, or a larger or smaller interval can be used to identify the working condition of the sintering trolley.

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

[0040] At this time, the description of different sintering layer thicknesses and temperature distributions will divide the sintering layer into multiple intervals according to its thickness, and identify the temperature distribution form on the sintering vehicle path in each interval. For example, the temperature distribution types include annular distribution, band distribution, and gradient distribution. Then, according to the occurrence of this temperature distribution type in sintering layers of different thicknesses in historical data, and combined with the temperature at the corresponding position of the current temperature cloud map matrix, the temperature distribution type at this time is selected, and then the associated description factor with the temperature distribution type is set. The associated description factor is mainly used to explain the current temperature distribution type and the temperature conditions at the corresponding position. Then, based on this associated description factor, the uniformity and unevenness of the temperature that needs 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 factor of each temperature distribution type may also include: identifying the color code corresponding to each temperature classification type, converting the position corresponding to each temperature distribution type into a corresponding color area, performing linear gradient on each color area, and determining the intersection area of ​​each color area; for linear gradient, interpolation is performed between adjacent color areas to describe the boundaries between different current color areas.

[0042] 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.

[0043] At this time, the current temperature distribution described by the associated descriptive factor is further described to understand the relative situation of the actual distribution under the current temperature distribution type, to identify the corresponding temperature range of the current sintering trolley when moving under different sintering layer thicknesses, and finally to obtain more comprehensive description information, which is convenient for the staff to timely control the working status of the sintering trolley.

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

[0045] Table 1. Schematic diagram of temperature distribution types

[0046]

[0047] Table 1 shows the possible distribution of the current temperature distribution type and the corresponding sintering layer thickness. After describing the contents represented, the corresponding characteristic values ​​are displayed for subsequent related calculations. The contents shown here do not represent all the situations in the actual identification of the sintering table machine, but only explain the main situations and types that may exist at present.

[0048] The associated descriptive factors of each temperature distribution type are used to set the characteristic quantification index, and the characteristic quantification index is used to calculate the maximum temperature difference and thermal stress at each detection point.

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

[0050] Thermal stress is expressed as: ;in, represents thermal stress, represents the thermal expansion coefficient of the material, represents the elastic modulus, represents Poisson's ratio, It represents the geometric shape factor, which is set according to the currently recognized structure. For example, the fence on the sintering trolley is set to 1.2, and the grate is set to 0.8. Representing the temperature difference, it can be directly found that the temperature difference existing in the corresponding structure affects the distribution of thermal stress. Then, by identifying the temperature difference, the part of the structure with excessive thermal stress can be found to verify whether the corresponding structure is prone to excessive deformation.

[0051] 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.

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

[0053] For example, thermal stress after multi-constraint correction It is expressed as: ;in, represents the thickness of the sintered layer, Indicates the standard thickness of the sintered layer. It represents the empirical proportionality coefficient, which indicates the weight of the influence of the sintered layer thickness on the thermal stress. The value of 0.15 can be used to represent the relative weight between the sintered layer thickness and the thermal stress. It represents the correction coefficient, which is used to describe the nonlinear relationship between the change of sintered layer thickness and thermal stress. In order to fit the error under multi-constraint correction of thermal stress, this coefficient can adopt a value of 0.6 to describe the situation of using the sintered layer thickness to correct the thermal stress. At this time, we can know how the value of thermal stress under different sintered layer thicknesses will be represented.

[0054] As shown in Table 2, the characteristic interval of thermal stress after multi-constraint correction can be expressed in the following way.

[0055] Table 2. Schematic table of characteristic intervals

[0056]

[0057] That is, after obtaining the change of the corrected thermal stress in the corresponding area and the corresponding temperature, the thermal stress-related conditions are characterized and classified, and then the data in each characteristic interval are displayed to obtain the temperature-stress relationship curve. In the temperature-stress relationship curve, when describing any of the linear elastic zone, plastic transition zone and nonlinear creep zone, the slope expressed by the curve will show different results.

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

[0059] The slope of the plastic transition zone begins to deform gradually, which means that the corresponding structure on the trolley begins to deform plastically and its stiffness gradually decreases. In this case, the rate of stress increase begins to slow down. At the same time, after the work is completed, some strains cannot be recovered, resulting in residual deformation.

[0060] The slope of the nonlinear creep zone will change over time, and will gradually decrease as the stress changes, and then slowly tend to a stable form. This area is generally used to evaluate the long-term stability and creep performance of the trolley structure.

[0061] Then, according to the different forms of these three expressions, relevant characteristic points are extracted from the temperature-stress relationship curve, such as turning points, breaking points, and points where the corresponding hysteresis effect causes differences in the displayed values. The conditions of these points are analyzed to obtain the characteristic interval of the current temperature-stress relationship curve to complete the analysis of the corresponding curve. In the temperature-stress relationship curve, temperature can be used as the curve identifier, and the thermal stress and strain corresponding to the curve can be used as the coordinates of the curve representation. Temperature and stress can also be used as the coordinates of the curve representation to reflect the thermal stress distribution on the current sintering trolley under different temperature distributions.

[0062] Therefore, the method of identifying the characteristic interval of 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 identifying the yield point, creep limit point and slope value on the stress relationship curve in turn; the yield point refers to the critical point where the material enters plastic deformation from elastic deformation. After this point, even if the stress no longer increases, the material will continue to deform permanently. 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 stress changes, so as to determine whether there is a corresponding structural change on the current sintering trolley. The calculation formula for the corresponding strain is to divide the thermal stress calculation content by the elastic modulus; and the stress change curve is used to identify whether the corresponding structure belongs to the linear elastic zone, plastic transition zone and nonlinear creep zone under the current temperature change.

[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 of the stress that represents 0.2% on the ordinate, and then the intersection of this straight line and the stress relationship curve is the identified yield point.

[0065] The direct observation method is to find the inflection point or area in the stress relationship curve, which usually indicates the beginning of yielding, and regard the inflection point as the yield point.

[0066] The numerical analysis rule is to differentiate the slope value on the stress relationship curve and find the position where the slope changes significantly. When a position with obvious changes appears, 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 under given temperature and time conditions without causing excessive creep strain. The creep limit point identified here is set by testing the material of the corresponding structure on the current sintering trolley to find the point corresponding to the maximum stress value that the material can accept under normal use. This limit point can be represented by the maximum stress value of the current sintering trolley in the historical data under long-term work. 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 adjacent to the yield point, and calculate the yield similarity coefficient between the yield point and the historical data; the yield similarity coefficient is calculated using the slope value of the data point adjacent to the yield point and the slope value adjacent to the yield point in the historical data using the Pearson correlation coefficient to obtain the yield similarity coefficient. This coefficient indicates whether the adjacent points are consistent with the historical data when the yield point is currently generated. If the final value of the yield similarity coefficient is small, it means that the linear relationship between the current yield point adjacent slope value 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, which may mean that the material properties have changed, or the conditions of the two comparisons are different. At this time, the coefficient will be recorded and a new data mapping will be established. If the yield similarity coefficient is large, it means that the slope value adjacent to the yield point of the current experiment has a strong linear relationship with the slope value in the historical data.

[0069] 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. According to the divided characteristic intervals, a temperature-stress relationship curve can be generated to obtain the direct relationship between the current temperature difference and the thermal stress under different characteristics, and to adjust the relevant data accordingly.

[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 to the database as a new mapping relationship. The expected yield coefficient will take into account the existence of positively correlated yield points. For example, a value of 0.3 can be used to use yield points greater than this value. In general, the yield similarity coefficient ranges from -1 to 1. The closer the value is to 1, the more obvious the positive correlation is. If it is close to -1, it shows a negative correlation or no direct correlation. As for the way to divide the characteristic interval of the current thermal stress into a linear elastic zone, a plastic transition zone, and a nonlinear creep zone, the yield point is used as a dividing point to identify the linear elastic zone and the plastic transition zone, and the plastic transition zone and the nonlinear creep zone are obtained based on the stable curve with a value close to the creep limit point. For recording the relative distance, it can be intuitively seen how much stress range the material has available before entering dangerous creep deformation. A larger distance means a higher safety margin, allowing more room for operation without immediately causing structural failure.

[0071] The temperature-stress relationship curve finally obtained can represent the conditions of the guardrails and grates under different working conditions, thereby preventing excessive structural damage that would affect the operation of the sintering trolley itself.

[0072] The temperature-stress relationship curve will show the stress change at a certain position on the trolley's path when its temperature changes, and the generated curves will be separately represented according to the three types represented by the characteristic intervals, that is, the value of the temperature change over time at a certain position is used as the horizontal axis, and the value of the thermal stress change over time is used as the vertical axis for display; or the temperature is used as the label of the relationship, time is used as the horizontal axis, and the thermal stress is used as the vertical axis for display, to set curves under multiple temperatures or temperature differences, and use them as the temperature-stress relationship curve at this time; or the temperature values ​​of all position points on the trolley's path are used as the horizontal axis, and the thermal stress of all position points are used as the vertical axis to describe the distribution relationship in relative space, and the values ​​at these position points are taken as the average value per unit time, and multiple curves annotated with time are generated to show the expression of the temperature-stress relationship curve at the corresponding position.

[0073] In one embodiment of the present invention, the equipment condition of the sintering trolley represents the specific equipment composition of the current sintering trolley, and the equivalent force identification processes the situation where the thermal stress distribution and the corresponding deformation of the thermal stress appear superimposed, that is, whether there is a corresponding area on the current sintering trolley for any type of stress change in the linear elastic zone, the plastic transition zone and the nonlinear creep zone, and the deformation concentration parts and stress concentration accumulation places that can be generated in these areas are identified to find the position most likely to cause excessive deformation.

[0074] like Figure 3As shown, the implementation method of the deformation analysis module includes: identifying the stress change area in the temperature-stress change curve according to the acquired temperature-stress relationship curve, and finding out the parts where deformation will appear concentratedly and the parts where stress will accumulate concentratedly in these change areas.

[0075] Compare the thermal stress 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.

[0076] The cumulative effect means that after the thermal stress generates strain, residual stress appears and accumulates at these locations. These locations will be identified through the curve data on the plastic transition zone in the temperature-stress relationship curve. The nonlinear creep zone belongs to the changes after the plastic transition zone. Residual stress will also appear at this location. At this time, the residual stress accumulation will be identified and processed to find the deformation concentration area under the premise of the same equipment working, so as to identify the changes in stress accumulation.

[0077] Identify the range of changes and distribution ranges of stress values ​​in stress analysis data; at this time, identify the distribution of stress values ​​and positions under a specific operating range, such as the difference between the maximum and minimum values ​​of the stress value under the corresponding temperature range. This range can directly show the stress conditions received by the structure on the sintering trolley, and whether the stress conditions can cause structural fatigue damage, resulting in premature damage to the equipment, etc.; as for the distribution range, it is to evaluate the area distributed on the current sintering trolley with the same range of stress values, which is used to express the distribution of stress values ​​in space. Record the relative distance between the center points of each range under the corresponding range of changes and distribution ranges, 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 corresponding values ​​of the center points of each range are expressed as the frequency of the stress value at that point in the historical data, and these frequencies are subtracted to obtain the relative distance between the centers of different ranges.

[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] For example, the implementation method of the stress accumulation curve includes: based on the obtained deformation concentration area, comparing the strain energy density coefficient and stress distribution similarity index of the corresponding deformation concentration area under different sintering layer thickness distribution and temperature.

[0084] 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.

[0085] The strain energy density coefficient can be expressed as: ;in, It represents strain, that is, the degree to which the material deforms in the presence of thermal stress; represents the strain energy density coefficient, It indicates the critical strain energy density when the material yields, which can be measured by material tensile test experiments. This value can be used to determine the risk of plastic deformation in the current deformation concentration area. When half of the thermal stress or strain exceeds 80% of the material's own limit, plastic deformation is likely to occur. Generally, a 10%-20% safety margin is selected for the limit that the material itself can withstand. At this time, a 20% safety margin is selected to determine 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] The stress distribution similarity index can be calculated by using the Pearson correlation coefficient to calculate the deformation concentration area and the corresponding value in the historical data. When the stress distribution similarity index is greater than 0.85, the area is considered to be screened data.

[0087] Then, according to the existing data points, a stress accumulation model is established. ;in, represents the output of the stress accumulation model, Indicates the number of time periods, i ranges from 1 to n; represents the average thermal stress in time period i, It represents the reference stress, which is 80% of the fatigue limit of the material and can be taken as 120MPa; represents the duration of thermal stress in time period i, Represents the material sensitivity index, and the value here is 3.2.

[0088] Then, according to the content of these data outputs, a curve representing the accumulation of stress over time is obtained, as shown in Table 3. The following results exist in the deformation concentration area under positioning.

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

[0090]

[0091] It is found in Table 3 that the railing weld and the bearing seat are areas of concentrated deformation, and the cooling strategy needs to be optimized first, and the stress level in the middle of the grate is within a safe range; this part of the data will indicate whether these areas need to be repaired and related treatment in areas where obvious deformation accumulation occurs, so as to improve the judgment and treatment of the specific work content of the sintering trolley by the entire system.

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

[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 when the sintering trolley is working to obtain the differential 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 stress-related error, and regard the error as the differential coefficient.

[0094] If the temperature deviates, the thermal stress under the deviation is calculated, and the covariance of the thermal stress in space is obtained. The residual stress under the corresponding covariance is calculated to obtain the relative error of the output.

[0095] 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. 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 shown in Table 4.

[0097] Table 4. Examples of residual stress distribution

[0098]

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

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

[0101] The deformation impact range refers to the components within the spatial range surrounding the current deformed part, as well as a list of these components; for example, if the middle of the guardrail is deformed, then its impact range includes at least three adjacent grates. At this time, the guardrail will be used as the center point to obtain a list of its surrounding components and related test data to identify whether the guardrail will affect the thickness of the local sintering layer, or cause large changes in thermal stress in other components, resulting in a reduced service life.

[0102] Each event information represents the temperature, thermal stress, strain energy density, temperature distribution and characteristic interval corresponding to the temperature measured in the temperature-stress relationship curve and stress accumulation curve. The preset trigger condition of each event information is to find out whether the current measured data can have some content that triggers the alarm. If so, the corresponding content that triggers the alarm will be used as the overall status of each component.

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

[0104] Table 5. Typical events

[0105]

[0106] The table shows the impact range and trigger conditions of the impact situation of 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, so as to facilitate the subsequent selection of how to adjust and control the sintering trolley according to the state of each component.

[0107] Each strategy sub-model corresponding to each event information is constructed, and each strategy sub-model is combined with the overall state of each component in the sintering trolley to generate a strategy 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, and the policy control model is a method for overall control of multiple components.

[0109] 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 collaborative adjustment plan in the strategic control model.

[0110] For the policy sub-model, each component will be described according to the component corresponding to the event information, and then these contents will be combined to obtain the policy control model.

[0111] That is, for the policy sub-model, according to the corresponding event information, the weight of the event information in the current policy sub-model is obtained, and according to the weight corresponding to the event information, the policy sub-model is combined into a policy control model.

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

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

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

[0115]

[0116] T used in Table 6 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, a relevant recommended combination plan will be generated for these parts that need to be adjusted. This combination plan will be regarded as the strategic control model used at this time to make corresponding adjustments to the subsequent control of the overall sintering trolley.

[0117] The implementation method of the collaborative adjustment scheme in the selection strategy control model also includes: taking temperature and thermal stress as the main factor, taking event information as the input vector, and constructing an event vector matrix corresponding to the event information; the event vector matrix represents combining the currently input event information in the form of a matrix 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 collaborative adjustment schemes.

[0118] 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; at this time, the part with the largest value in the state transition probability will be used as the predicted next event information.

[0119] Calculate the differential metric between the event vector matrix of the next event information and the current event vector matrix, and select the coordinated adjustment scheme according to the differential metric. The differential metric means that after calculating the proportional square value of the difference between each element in the event vector matrix, the proportional square value is summed according to the number of elements in the event vector matrix to obtain the comparison result between the overall state of the next event information and the overall state of each component in the current sintering trolley; finally, select the corresponding coordinated adjustment scheme from the database according to this differential metric. The selection is to select the differential metric and the corresponding scheme in the database to calculate the correlation coefficient according to the comprehensive value of the differential metric, such as the calculation method of the Pearson correlation coefficient, and use the scheme content with the largest value of the correlation coefficient as the coordinated adjustment scheme to be used.

[0120] like Figure 5 As shown, the present invention also provides a sintering trolley intelligent control method based on industrial automation technology, comprising: S1, obtaining equipment working information of the sintering trolley through sensors and other equipment.

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

[0122] S3, identify the deformation concentration area under the corresponding thermal stress and establish the stress accumulation curve.

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

[0124] S5, adjust the working mode according to the changing trend of the sintering trolley and set up a coordinated adjustment plan.

[0125] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still 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 may also include: 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 sensors and other equipment; 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; 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 curves to predict 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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