High reconfiguration ratio automatic adjustment method and related device

Abstract

This invention discloses a method and related equipment for automatic adjustment of high return ratios, relating to the field of automation control in steel smelting, primarily addressing the problems of low accuracy and poor flexibility in existing high return ratio adjustments. The method includes: calculating the total ratio adjustment magnitude based on a moving average position trend that meets continuity conditions, wherein the moving average position trend characterizes the direction and intensity of position changes after smoothing and confirmation of validity; based on the total ratio adjustment magnitude, determining the ratio adjustment command for each production line according to production line priority and the degree of deviation of each production line's ratio from a preset optimal ratio; and executing the ratio adjustment for each production line if the ratio adjustment command meets safety standards. This invention is used in the automatic adjustment process of high return ratios.

Description

Technical Field

[0001] This invention relates to the field of automated control in iron and steel smelting, and in particular to a method and related equipment for automatic adjustment of high return ratio. Background Technology

[0002] In the sintering process of steel smelting, the control of the blast furnace return ore ratio (i.e., high-return ore) is a crucial link in ensuring smooth production, optimizing energy consumption, and extending equipment life. Currently, the industry still largely relies on operators' manual experience or simple automated rules based on fixed thresholds for adjusting the high-return ore ratio. Manual adjustment is highly dependent on individual experience and judgment, exhibiting significant adjustment lag and failing to respond in real time to rapid fluctuations in ore levels, resulting in poor production stability. Existing automated solutions are mainly based on fixed threshold-based ratio adjustment systems, which trigger adjustments by pre-setting fixed upper and lower limits for ore levels, and their shortcomings are particularly obvious. Therefore, the core problem with existing technical solutions lies in their simple adjustment logic, lag, and weak anti-interference ability, failing to achieve precise, stable, and adaptive closed-loop ratio control, thus hindering the improvement of the level of intelligence in sintering production. Summary of the Invention

[0003] In view of the above problems, the present invention provides a high return ratio automatic adjustment method and related equipment, the main purpose of which is to solve the problems of low accuracy and poor flexibility of existing high return ratio adjustment.

[0004] To solve at least one of the above-mentioned technical problems, in a first aspect, the present invention provides a method for automatically adjusting a high remix ratio, the method comprising: The total allocation adjustment is calculated based on the moving average position trend that meets the persistence condition, wherein the moving average position trend is used to characterize the direction and intensity of position changes that have been smoothed and confirmed to be effective. Based on the total ratio adjustment range, and according to the production line priority and the degree of deviation of each production line's ratio from the preset optimal ratio, the ratio adjustment instruction for each production line is determined; If the ratio adjustment instructions for the production line meet safety standards, the ratio adjustment for each production line shall be executed.

[0005] Optionally, the above methods also include: Collect material level data from the return ore bins of each production line; Based on a preset physical conversion model, the height data of each material level is converted into material weight data; The total high-return warehouse space data is determined based on the material weight data.

[0006] Optionally, the step of calculating the total allocation adjustment based on the moving average position trend that meets the persistence condition includes: The high-return total position data is smoothed to obtain a moving average position. Obtain the comparison result between the moving average position and the preset position midline, wherein the comparison result includes the deviation magnitude and duration; If both the deviation magnitude and duration meet the preset conditions, the moving average position trend that meets the persistence condition is confirmed. If a moving average position trend that meets the persistence condition is confirmed, the position change during the said duration is calculated. The corresponding calculation rule is selected based on the range of the absolute value of the position change, wherein the calculation rule corresponding to different ranges has different response coefficients. The total proportion adjustment range is determined based on the calculation rules.

[0007] Optionally, the step of determining the proportion adjustment instruction for each production line based on the total proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: The set of production lines to be adjusted is determined from all production lines based on production line priority rules; The total adjustment range is taken as the total amount to be allocated; Obtain the current ratio value of each production line to be adjusted in the set of production lines to be adjusted; The absolute value of the difference between the current ratio value and the corresponding preset optimal ratio value of each production line to be adjusted is determined as the ratio deviation degree of each production line to be adjusted. The ratio deviation degree is used to quantify the gap between the current state and the ideal state of each production line.

[0008] Optionally, the step of determining the proportion adjustment instruction for each production line based on the total proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: Performing a single iteration operation, wherein performing a single iteration operation includes: Select the production line with the smallest ratio deviation from the set of production lines to be adjusted as the target iterative adjustment object; Calculate the adjustable space of the target iterative adjustment object in the direction of the total ratio adjustment range, wherein the adjustable space is used to characterize the difference between the current ratio value of the adjustment object and the upper or lower limit of the ratio allowed by the process; The minimum value is selected from the absolute value of the remaining total ratio adjustment range, the preset single-step adjustment range upper limit, and the adjustable space as the single adjustment amount for this iteration, wherein the positive or negative sign of the single adjustment amount is the same as the direction of the total ratio adjustment range. The single adjustment amount is accumulated and added to the current ratio value of the target iterative adjustment object; The single adjustment amount is recorded as the proposed adjustment amount for the target iterative adjustment object, and the single adjustment amount is subtracted from the remaining total ratio adjustment range.

[0009] Optionally, the step of determining the proportion adjustment instruction for each production line based on the total proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: Determine whether the termination condition of the iteration is met, wherein the termination condition of the iteration is: the absolute value of the remaining total ratio adjustment range is less than a preset threshold, or each production line to be adjusted in the set of production lines to be adjusted has no adjustment space in the adjustment direction. If the iteration is not terminated, update the current ratio value and ratio deviation of each production line to be adjusted, and repeat the steps of the single iteration operation. In the event of termination of the iteration, the cumulative amount of adjustment to be made for each production line to be adjusted is determined as the ratio adjustment instruction.

[0010] Optionally, the step of performing proportion adjustments for each production line when the proportion adjustment instruction for the production line meets safety standards includes: If the ratio adjustment command of the production line exceeds the preset range threshold, a second confirmation is required; Based on the ratio adjustment instructions of the aforementioned production line, the ratio adjustment of each production line is executed; Record the operation log during the ratio adjustment process to generate audit trail information.

[0011] Secondly, embodiments of the present invention also provide an automatic adjustment device for high remix ratio, comprising: The calculation unit is used to calculate the total allocation adjustment range based on the moving average position trend that meets the persistence condition, wherein the moving average position trend is used to characterize the direction and intensity of position changes that have been smoothed and confirmed to be effective. The determining unit is used to determine the proportion adjustment instruction for each production line based on the total proportion adjustment range, the production line priority, and the degree of deviation of each production line's proportion from the preset optimal proportion. An execution unit is used to execute the proportion adjustment of each production line when the proportion adjustment instruction of the production line meets the safety standards.

[0012] To achieve the above objectives, according to a third aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium comprising a stored program, wherein, when the program is executed by a processor, the steps of the above-described high return ratio automatic adjustment method are implemented.

[0013] To achieve the above objectives, according to a fourth aspect of the present invention, an electronic device is provided, comprising at least one processor and at least one memory connected to the processor; wherein the processor is configured to invoke program instructions in the memory to execute the steps of the above-described high return ratio automatic adjustment method.

[0014] By employing the above technical solution, the high return ratio automatic adjustment method and related equipment provided by this invention address the problems of low accuracy and poor flexibility in existing high return ratio adjustments. This invention calculates the total ratio adjustment magnitude based on a moving average position trend that meets continuity conditions. The moving average position trend characterizes the smoothed and confirmed effective direction and intensity of position changes. Based on the total ratio adjustment magnitude, and according to production line priority and the degree of deviation of each production line's ratio from the preset optimal ratio, adjustment instructions for each production line are determined. If the adjustment instructions for each production line meet safety standards, the ratio adjustment for each production line is executed. In this solution, the control basis is shifted from responding to instantaneous, isolated signals to responding to a smoothed trend verified over time. By calculating the "moving average position trend that meets continuity conditions," the moving average itself filters out high-frequency instantaneous fluctuation noise, reducing the probability of false triggers. The "continuity condition" requires the trend to remain consistent over time, ensuring that only real and stable changes in production status trigger adjustment decisions, thereby avoiding frequent false adjustments based on short-term disturbances. Furthermore, the total adjustment range is allocated based on production line priority and the degree of deviation of each production line's ratio from the preset optimal ratio. This changes the one-size-fits-all allocation model, dynamically allocating resources according to process importance and the gap between the current state and the ideal state. This guides the ratios of each production line to move towards the optimal setpoint in a coordinated and gradual manner, achieving smooth internal collaborative optimization. Finally, safety verification rules are set in the final execution stage, transforming empirical safety judgments into traceable algorithm verification points. This reduces the risk of directly executing abnormal instructions and enhances fault tolerance. This forms a more robust and adaptive automatic control logic closed loop than manual experience or simple threshold control.

[0015] Correspondingly, the high return ratio automatic adjustment device, equipment, and computer-readable storage medium provided in the embodiments of the present invention also have the above-mentioned technical effects.

[0016] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0017] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart illustrating an automatic adjustment method for high return ratio provided by an embodiment of the present invention is shown; Figure 2 This diagram illustrates the composition of an automatic adjustment device for high rework ratio provided in an embodiment of the present invention. Figure 3 This diagram illustrates the composition of an electronic device for automatic adjustment of high return ratio provided in an embodiment of the present invention. Detailed Implementation

[0018] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0019] To address the problems of low accuracy and poor flexibility in existing high-return-ratio adjustments, embodiments of the present invention provide an automatic high-return-ratio adjustment method, such as... Figure 1 As shown, the method includes: S101. Calculate the total allocation adjustment range based on the moving average position trend that meets the persistence condition, wherein the moving average position trend is used to characterize the direction and intensity of position changes that have been smoothed and confirmed to be effective. In one embodiment, the above method further includes: Collect material level data from the return ore bins of each production line; Based on a preset physical conversion model, the height data of each material level is converted into material weight data; The total high-return warehouse space data is determined based on the material weight data.

[0020] For example, the moving average position trend is not a simple arithmetic mean, but rather the result obtained after smoothing the total high-return position data. Its calculation process is a moving average position calculation, designed to characterize the direction and strength of position changes. The persistence condition is a comprehensive criterion for judging the validity of the above trend, and its confirmation requires meeting preset conditions in both deviation magnitude and duration. The final calculated total allocation adjustment magnitude is a percentage value representing the total amount that needs to be adjusted.

[0021] This application first collects material level data from the return ore bins of each production line and converts it into material weight data based on a preset physical conversion model. This data is then aggregated to determine the total high-return bin position data, providing an accurate data foundation for subsequent calculations. Next, the total high-return bin position data is smoothed to obtain a moving average bin position. This smoothing process specifically uses moving average calculation, the core of which is to assign higher weight to recent data, thereby reducing the impact of instantaneous fluctuations while preserving the overall trend. The system also adaptively adjusts the size of the data window used for calculation based on the volatility of the bin position data to achieve a balance between smoothing effect and response speed. Subsequently, the obtained moving average bin position is compared with a preset bin position midline to obtain comparison results in two dimensions: deviation magnitude and duration. Only when the deviation magnitude exceeds a certain threshold and the deviation persists for a sufficiently long time will the system confirm a moving average bin position trend that meets the persistence condition. This confirmation process is a multi-dimensional verification; the system comprehensively evaluates the trend's duration, magnitude of change, and consistency of direction, assigning a confidence level assessment to the trend. Only trends with high confidence are adopted. After confirming a valid trend, the system calculates the change in position size over that duration and selects the corresponding calculation rule based on the range of the absolute value of the position change. This selection mechanism reflects a dynamic response design; for position changes of different magnitudes, the system matches calculation rules with different response coefficients. For example, a weaker response is used for small changes, while a standard or enhanced response is used for significant changes. Finally, the system determines the total allocation adjustment based on the selected calculation rule, thus completing the transformation from raw data to adjustment decision quantities.

[0022] The preset physical conversion model is established based on the geometry of the silo and the bulk density of the returned ore. Specifically, for each silo, the conversion relationship between its material weight data T and the collected material level height data h can be expressed as: T = ρ·A(h)·h, where ρ is the bulk density of the returned ore, and A(h) is a function of the silo cross-sectional area changing with height h. This model can be simplified according to the actual shape of the silo. The initial values ​​of key parameters in the model (such as bulk density ρ and cross-sectional area parameters) are determined through silo design drawings and actual material measurements. To ensure long-term accuracy, the system also supports online calibration, such as periodically calibrating the silo level using empty silos or using actual data from belt scales to revise the bulk density parameter.

[0023] Furthermore, the system can dynamically adjust the length of the data time window used to calculate the moving average position based on the volatility of the position data. Specifically, the system calculates the standard deviation σ of the position data over a past period (e.g., 6 hours) and sets a volatility threshold (e.g., 50 tons). When the standard deviation σ exceeds this threshold, indicating volatile position fluctuations, the system automatically increases the window length for smoothing calculations (e.g., from the default 3 hours to 5 hours) to enhance the smoothing effect and filter out interference. When the position data stabilizes (i.e., the standard deviation σ is below the threshold and remains so for a certain period, e.g., 2 hours), the system restores the window length to the default value to improve the response speed to the actual trend. The weighting principle used in the calculation remains unchanged when the window changes, still following the principle of giving higher weight to recent data.

[0024] The comprehensive evaluation described above is reflected in the system calculating a confidence score for each identified trend. The confidence score is a composite of three factors: the duration of the trend, the magnitude of change, and the consistency of direction. For example, the duration factor is positively correlated with the length of time the trend has lasted; the magnitude of change factor is positively correlated with the cumulative amount of change in the trend; and the consistency factor is positively correlated with the proportion of periods in which the trend direction is consistent. The system assigns weights to each factor (e.g., duration weight 0.3, magnitude of change weight 0.4, consistency weight 0.3) and performs a weighted summation to obtain the final confidence score. Only when the confidence score exceeds a preset threshold (e.g., 0.8 or 80%) does the system determine that the trend is valid and adopt it, triggering subsequent adjustment decisions.

[0025] By employing the aforementioned technical solution, this step shifts the decision-making basis for portfolio adjustment from responding to raw, easily disturbed instantaneous position signals to responding to stable position trends that have undergone sufficient smoothing and time verification. Through moving average calculation and adaptive window adjustment, the probability of system misjudgment and false triggering of adjustments due to instantaneous fluctuations in the production process or sensor noise can be effectively reduced. Furthermore, the introduction of a comprehensive judgment based on duration, amplitude, and confidence level ensures that only trends reflecting real and stable production status changes trigger subsequent adjustments, avoiding frequent operations based on short-term, minor, or ambiguous fluctuations. Moreover, by dynamically selecting different response coefficient calculation rules according to different ranges of position changes, the system can exhibit adjustment sensitivity matching trends of varying intensities, thus making the calculated total portfolio adjustment range more reasonable and laying a reliable decision-making foundation for ultimately achieving smooth and stable portfolio adjustments.

[0026] In one embodiment, calculating the total allocation adjustment based on the moving average position trend that meets the persistence condition includes: The high-return total position data is smoothed to obtain a moving average position. Obtain the comparison result between the moving average position and the preset position midline, wherein the comparison result includes the deviation magnitude and duration; If both the deviation magnitude and duration meet the preset conditions, the moving average position trend that meets the persistence condition is confirmed. If a moving average position trend that meets the persistence condition is confirmed, the position change during the said duration is calculated. The corresponding calculation rule is selected based on the range of the absolute value of the position change, wherein the calculation rule corresponding to different ranges has different response coefficients. The total proportion adjustment range is determined based on the calculation rules.

[0027] For example, the above scheme involves processing high-return total position data to ultimately determine the total allocation adjustment magnitude. The moving average position is the result of smoothing the high-return total position data, aiming to reflect the position level after removing instantaneous fluctuations. A preset position midline is a benchmark value used to determine whether the position deviates. The deviation magnitude is the difference between the moving average position and this midline, and the duration is the length of time the deviation persists. The position change is the amount of change in the position value within the confirmed trend duration. The calculation rules are a set of specific methods selected based on the magnitude of the position change for calculating the adjustment magnitude. Different calculation rules include different response coefficients, which directly affect the final calculated adjustment magnitude. The total allocation adjustment magnitude is the total amount of allocation change that needs to be applied, ultimately obtained through the calculation rules.

[0028] This application first smooths the high-return total position data to obtain a moving average position. This smoothing is not a simple arithmetic average, but rather uses a calculation method that gives higher weight to recent data, making recent position changes have a greater impact on the trend, thus weakening the impact of short-term fluctuations while preserving the overall trend. The system can also dynamically adjust the length of the data time window used for calculation based on the volatility of the position data itself. When the data volatility is high, the window is automatically extended to enhance the smoothing effect, and when the data is stable, the window is shortened to improve response speed, thereby adapting to different production states. After obtaining the moving average position, it is compared with the preset position midline to obtain two key comparison results: deviation magnitude and duration. The system does not immediately take action on any deviation, but requires that the deviation magnitude must exceed a set threshold, and this deviation state must last for a specified minimum time. Only when both conditions are met simultaneously will a moving average position trend that meets the persistence condition be confirmed. The confirmation process is a comprehensive assessment. The system also examines the continuity of trend direction and the consistency of change magnitude, and calculates a confidence score for the current trend. Only trends with high confidence are adopted, effectively preventing misjudgments caused by accidental fluctuations or data spikes. After confirming a valid trend, the system calculates the specific position changes that occurred during that period. Next, based on the absolute value of these position changes, the system categorizes them into different ranges and matches each range with a pre-defined calculation rule with different response coefficients. For example, for small position changes, the system uses a weaker response rule; for changes of normal magnitude, a standard response rule; and for large, significant changes, an enhanced response rule. This design ensures that the system's sensitivity matches the severity of position changes. Finally, based on the selected specific calculation rule and its inherent response coefficient, the system processes the position changes to determine the total allocation adjustment required for this adjustment.

[0029] By employing the aforementioned technical solutions, a multi-layered decision-making mechanism was constructed, encompassing data smoothing, trend verification, and amplitude calculation. Through weighted smoothing and adaptive windowing of the inventory data, instantaneous spikes caused by mechanical vibration, material impact, or sensor noise during production can be effectively filtered, reducing the probability of unnecessary adjustments triggered by these transient disturbances. By introducing trend judgment logic that simultaneously satisfies amplitude thresholds and duration conditions, and combining multi-dimensional verification and confidence assessment, the system ensures that it only responds to real, stable, and continuous changes in production status, avoiding frequent or erroneous adjustments based on short-lived, weak, or directionally fluctuating pseudo-trends. Furthermore, by dynamically selecting different response coefficient calculation rules based on the magnitude of inventory changes, the system can automatically adjust its adjustment intensity when facing different degrees of inventory deviation, achieving gentle handling of small fluctuations and proactive responses to large trends. This results in a more reasonable final total allocation adjustment instruction, providing a core guarantee for the stability and reliability of the entire allocation adjustment process.

[0030] S102. Based on the total ratio adjustment range, and according to the production line priority and the degree of deviation of each production line ratio from the preset optimal ratio, determine the ratio adjustment instruction for each production line; In one embodiment, determining the proportion adjustment instruction for each production line based on the total proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: The set of production lines to be adjusted is determined from all production lines based on production line priority rules; The total adjustment range is taken as the total amount to be allocated; Obtain the current ratio value of each production line to be adjusted in the set of production lines to be adjusted; The absolute value of the difference between the current ratio value and the corresponding preset optimal ratio value of each production line to be adjusted is determined as the ratio deviation degree of each production line to be adjusted. The ratio deviation degree is used to quantify the gap between the current state and the ideal state of each production line.

[0031] For example, the above scheme involves decomposing the calculated total proportion adjustment range and allocating it to each production line to generate specific proportion adjustment instructions. The set of production lines to be adjusted is a subset of all production lines selected based on production line priority rules, allowing them to participate in the adjustment this time. The current proportion value is the real-time proportion value of each production line before adjustment. The preset optimal proportion value is the ideal proportion value that is expected to be achieved in terms of process, pre-set for each production line. The proportion deviation is obtained by calculating the absolute value of the difference between the current proportion value and the corresponding preset optimal proportion value; this value is used to quantify the degree to which the current actual proportion state of each production line deviates from its ideal state.

[0032] This application first determines the set of production lines to be adjusted based on production line priority rules. Production line priority rules are set to ensure the production stability of critical production lines. For example, in sintering production, critical production lines such as three-stage sintering and two-stage blending might be excluded from the regular adjustment set and only adjusted when there are special needs, thus prioritizing their stable operation. Next, the total proportion adjustment range calculated from the upstream steps is used as the total amount to be allocated this time. Then, the current proportion value of each production line in the set of production lines to be adjusted is obtained. Subsequently, the proportion deviation is calculated for each production line. Specifically, the preset optimal proportion value corresponding to each production line is obtained. This value is preset by the process based on comprehensive factors such as sinter quality and energy consumption. Then, the difference between the current proportion value of the production line and this preset optimal proportion value is calculated, and the absolute value of the difference is taken. The result is the proportion deviation of the production line. This deviation is an important internal state indicator, objectively reflecting the distance between the proportion status of each production line and its optimal process setting point. The larger the value, the further it deviates from the ideal state; the smaller the value, the closer it is to the optimal operating point. Through this calculation, the system quantifies the status of all production lines into comparable deviation values, providing a clear basis for subsequent intelligent allocation and adjustment.

[0033] By employing the aforementioned technical solutions, a mechanism for generating proportioning adjustment instructions based on rules and quantified status was established. By selecting the set of production lines to be adjusted according to production line priority rules, frequent interference with critical production lines can be consciously avoided during automatic adjustment, thereby ensuring the stability of the core production process at the system level and reducing the risk of overall production fluctuations caused by global adjustments. By calculating the proportioning deviation of each production line, the system transforms the originally abstract process objective of "approaching the optimal value" into a concrete and calculable numerical indicator. This ensures that subsequent adjustment allocation decisions are no longer indiscriminate or egalitarian, but based on the precise difference between the real-time status and the ideal state of each production line. This lays the data foundation for achieving guided and gradual optimization allocation, enabling adjustment resources to be guided to the most needed or most suitable production lines, creating the necessary conditions for ultimately achieving collaborative optimization of multi-production line proportions and smoothly approaching the optimal operating point.

[0034] In one embodiment, determining the proportion adjustment instruction for each production line based on the total proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: Performing a single iteration operation, wherein performing a single iteration operation includes: Select the production line with the smallest ratio deviation from the set of production lines to be adjusted as the target iterative adjustment object; Calculate the adjustable space of the target iterative adjustment object in the direction of the total ratio adjustment range, wherein the adjustable space is used to characterize the difference between the current ratio value of the adjustment object and the upper or lower limit of the ratio allowed by the process; The minimum value is selected from the absolute value of the remaining total ratio adjustment range, the preset single-step adjustment range upper limit, and the adjustable space as the single adjustment amount for this iteration, wherein the positive or negative sign of the single adjustment amount is the same as the direction of the total ratio adjustment range. The single adjustment amount is accumulated and added to the current ratio value of the target iterative adjustment object; The single adjustment amount is recorded as the proposed adjustment amount for the target iterative adjustment object, and the single adjustment amount is subtracted from the remaining total ratio adjustment range.

[0035] For example, the above scheme describes a single iteration operation in the process of allocating the total proportion adjustment range to each production line. The target iterative adjustment object is a specific production line selected from the set of production lines to be adjusted, which will be calculated and processed in this iteration. The adjustable space is the difference between the current proportion value of the target production line in the current adjustment direction and the upper or lower limit of the proportion allowed by the process; it limits the maximum adjustment that can be applied to this production line in this iteration. The single adjustment amount is the specific proportion change value calculated in this iteration and about to be applied to the target production line. The proposed adjustment amount is the adjustment amount already accumulated and recorded for the target production line in the current overall allocation process. The remaining total proportion adjustment range is the total amount of adjustment that has not yet been allocated after previous iterations. The preset single-step adjustment range upper limit is a global constraint parameter set to ensure that the adjustment range is controllable each time.

[0036] The upper limit, lower limit, and preset optimal ratio values ​​allowed by the process are key process parameters pre-set for each production line. For example, for a production line named "three-stage sintering and one-stage blending," the upper limit might be set at 35%, the lower limit at 25%, and the preset optimal ratio at 30%. These parameters are determined by the process department based on comprehensive factors such as sinter quality requirements, equipment load, and energy consumption indicators. The initial value of the preset optimal ratio can be derived from the historical best operating data of the production line and can be continuously optimized through a quality feedback closed loop after the system is running.

[0037] This application achieves the allocation of proportions through iterative execution of a single operation. In each iteration, the system first selects the production line with the smallest proportion deviation from the set of production lines to be adjusted as the target adjustment object for this iteration. The purpose of selecting the production line with the smallest deviation, rather than the largest, is to prioritize adjusting those production lines closest to their optimal proportion values. Through multiple iterations, the proportions of all production lines can collaboratively and gradually move towards their respective optimal values, rather than allowing a single production line to adjust independently. After determining the target object, the system calculates its adjustable space. For example, if the total proportion adjustment is in the direction of increase, the system calculates the difference between the current proportion value of the production line and the upper limit of the proportion allowed by the process; if it is in the direction of decrease, the system calculates the difference between the current proportion value and the lower limit of the proportion. This space is a hard boundary determined by the process constraints of the production line itself. Next, the system selects the minimum value from the three values ​​as the single adjustment amount for this iteration: the first is the absolute value of the remaining total ratio adjustment range, which represents the total amount of adjustment needs to be allocated; the second is the preset single-step adjustment range upper limit, which is a system safety parameter used to limit the step size of each adjustment to prevent the single adjustment from being too large; the third is the adjustable space of the target production line that was just calculated.

[0038] Selecting the minimum value means that the adjustment amount is simultaneously constrained by the remaining total demand, the system's single-step safety limits, and the target production line's own process limits, ensuring the feasibility and stability of the adjustment. The sign of this single adjustment amount is consistent with the direction of the total proportion adjustment range. Then, the system adds this single adjustment amount to the current proportion value of the target production line to simulate the adjusted state, and records this single adjustment amount as the proposed adjustment amount for that production line, i.e., the cumulative adjustment record. At the same time, this allocated amount is subtracted from the remaining total proportion adjustment range for the next iteration calculation.

[0039] By employing the aforementioned technical solution, this step achieves precise, safe, and coordinated allocation of proportioning adjustments through the design of a multi-constraint iterative allocation mechanism. Prioritizing the adjustment of the production line with the smallest proportioning deviation ensures that the proportioning status of all production lines converges synchronously and gradually towards the optimal setpoint across multiple iterations. This avoids the potential for abrupt changes in the state of a production line or relative deterioration of other production lines caused by making large adjustments only to those with large deviations, thus facilitating overall coordinated optimization of proportioning across multiple production lines. The single adjustment amount is determined by taking the minimum value from the remaining adjustment amount, the single-step upper limit, and the adjustable space. This ensures that each allocation simultaneously considers the overall adjustment needs, the operational safety of the system, and the technological feasibility of the target production line, automatically limiting the adjustment range within the strictest boundaries. This significantly reduces the risk of excessive single-step adjustments impacting the production process or violating process constraints. Decomposing the total adjustment amount into multiple controlled single adjustment amounts and allocating them gradually makes the entire allocation process smooth and controllable, avoiding the drastic changes that might result from a simple one-time allocation of the total adjustment amount, thus ensuring the stable operation of the production system.

[0040] In one embodiment, determining the proportion adjustment instruction for each production line based on the total proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: Determine whether the termination condition of the iteration is met, wherein the termination condition of the iteration is: the absolute value of the remaining total ratio adjustment range is less than a preset threshold, or each production line to be adjusted in the set of production lines to be adjusted has no adjustment space in the adjustment direction. If the iteration is not terminated, update the current ratio value and ratio deviation of each production line to be adjusted, and repeat the steps of the single iteration operation. In the event of termination of the iteration, the cumulative amount of adjustment to be made for each production line to be adjusted is determined as the ratio adjustment instruction.

[0041] For example, the above scheme controls the entire iterative allocation process and its final output. The termination condition of the iteration is the criterion for determining the end of the control loop, specifically including two scenarios. A preset threshold is a very small value used to determine whether the remaining adjustment needs are negligible. The proposed adjustment amount is the sum of the single adjustment amounts recorded for each production line in each iteration.

[0042] This application manages the allocation process of the proportion adjustment amount through a cyclical judgment mechanism to ensure that it can end in a timely and reliable manner. After each single iteration operation, the system immediately determines whether the termination conditions of the iteration are met. The first condition is that the absolute value of the remaining total proportion adjustment range is less than a preset minimum threshold. This condition means that after several iterations of allocation, the total adjustment amount to be allocated is negligible, thus meeting the requirements for allocation accuracy and allowing the allocation to stop. The second condition is that each production line in the set of production lines to be adjusted has no adjustment space in the current adjustment direction. This means that if the total adjustment range is in the direction of increase, then the current proportion value of all production lines has reached or is very close to the upper limit of their process-allowed proportion; if it is in the direction of decrease, then all production lines have reached or are close to their lower limit of proportion. This condition indicates that although there may still be remaining adjustment amount to be allocated, due to the process constraints of each production line, no further effective allocation can be made. The system continuously checks these two conditions. As long as either condition is met, the system determines that the iteration is terminated. If the iteration has not terminated, it indicates that there is still an adjustment amount to be allocated and at least one production line has adjustment potential. At this point, the system will enter the next iteration. To do this, the system needs to update the current proportion value and proportion deviation of each production line to be adjusted. This update is calculated based on the new state after accumulating the single adjustment amount in the previous iteration, ensuring that the next iteration can continue to select new targets from the set of production lines to be adjusted for adjustment calculations based on the latest state, thus repeating the steps of the single iteration operation. When the iteration finally terminates, the entire allocation cycle ends. At this time, the system summarizes the proposed adjustment amount accumulated by each production line to be adjusted throughout the entire iteration process and formally determines it as the proportion adjustment instruction to be finally issued to each production line. These instructions are the result of multiple rounds of fine calculation and constraint verification.

[0043] By employing the aforementioned technical solution, this step provides a clear exit mechanism and result generation rules for the iterative allocation process. By establishing two parallel termination conditions—minimal remaining adjustment amount and no adjustment space on the production line—the allocation process can automatically stop under two reasonable circumstances: either the adjustment requirements have been fully met and the allocation task is complete, or the allocation has reached its limit due to objective process constraints. This avoids the allocation process from falling into an infinite loop or ending prematurely, ensuring the completeness of the logic. While the loop is not terminated, by actively updating the current proportion values ​​and proportion deviations of each production line, the next iteration can make decisions based on the latest, simulated adjusted state, ensuring the continuity and rationality of the iterative calculation state, and enabling the entire allocation process to proceed dynamically and coherently. Finally, the accumulated proposed adjustment amount is determined as a formal instruction, completing the transformation from a dynamic calculation process to a static executable command. This solidifies and outputs the intermediate results of all the aforementioned iterative calculations, providing a clear and definite input for subsequent safe execution. The entire mechanism ensures that the allocation algorithm can converge and output a clear, reliable proportion adjustment scheme that meets all constraints.

[0044] S103. If the ratio adjustment instructions of the production line meet the safety standards, execute the ratio adjustment of each production line.

[0045] In one embodiment, the step of performing proportion adjustments for each production line when the proportion adjustment instruction for the production line meets safety standards includes: If the ratio adjustment command of the production line exceeds the preset range threshold, a second confirmation is required; Based on the ratio adjustment instructions of the aforementioned production line, the ratio adjustment of each production line is executed; Record the operation log during the ratio adjustment process to generate audit trail information.

[0046] For example, the above scheme involves the management of the verification and execution process of generated proportion adjustment instructions before final execution. The preset magnitude threshold is a critical value used to determine whether an adjustment instruction constitutes a significant adjustment. When the adjustment magnitude exceeds this value, an additional review process is triggered. Secondary confirmation is an additional review and approval step initiated when the instruction exceeds the preset magnitude threshold, designed to provide opportunities for manual review or delayed buffering for significant adjustments. The operation log is a detailed file automatically generated by the system during the proportion adjustment process, recording all relevant operations and events. Audit trail information is a traceable record generated based on the operation log, used to track operation history and accountability.

[0047] This application incorporates a safety verification step before executing proportion adjustment instructions. The system compares the calculated magnitude of proportion adjustment instructions for each production line with a preset magnitude threshold. This threshold is set according to process safety standards; for example, an adjustment exceeding 3% is defined as a major adjustment. When the system detects that any production line's adjustment instruction exceeds this preset magnitude threshold, it automatically triggers a secondary confirmation process. This process can be configured to require manual confirmation by the operator on the control interface, or it can be configured to automatically delay execution for a period of time, thus providing a window for manual intervention and preventing major adjustments from being executed automatically immediately. Only after the instruction passes this secondary confirmation (or does not exceed the threshold and therefore does not require confirmation) will the system issue the final, approved proportion adjustment instruction to the control system of the corresponding production line to execute the actual proportion adjustment. Simultaneously, the system activates a recording function to completely record key information during this proportion adjustment process in the operation log. This information typically includes: the content of the adjustment instruction that triggered the execution, whether secondary confirmation was triggered and the result of the confirmation, the specific time the instruction was actually issued, the production line identifier, and any possible manual intervention operations. Based on these continuously recorded operation logs, the system can generate audit trail information periodically or as needed, clearly showing the ins and outs of each adjustment operation.

[0048] By employing the aforementioned technical solution, this step embeds crucial safety and auditing mechanisms into the final execution stage of the automated control process. By establishing preset threshold values ​​and linking them to a secondary confirmation process, a safety barrier of manual review or buffering is added for significant operations involving large adjustments. This allows operators to conduct final oversight of major changes that may affect production stability, thereby reducing the potential risks arising from the system's unconditional and immediate execution of abnormal instructions generated by the core algorithm in extreme situations. By meticulously recording the entire process of proportioning adjustments in operation logs and generating audit trail information, traceability and transparency of production operations are achieved. This not only facilitates rapid identification of the cause of problems and operational responsibility in the event of anomalies but also provides complete data support for continuous optimization of production processes and improvement of the quality control system, enhancing the reliability and credibility of the entire automated adjustment system.

[0049] The method also includes handling special operating conditions such as planned shutdowns and production restrictions. When the system receives planned shutdown information, the special operating condition handling module is activated. This module predicts the target storage location at the end of the shutdown based on a material balance model. The model calculates based on the shutdown duration, current storage location, normal material consumption rate, and possible output rate during the shutdown. If the predicted target storage location exceeds the process safety range, the system initiates a pre-adjustment. The pre-adjustment process decomposes the total proportion adjustment required to ensure storage location safety into multiple smaller adjustment instructions (e.g., limiting the single-step adjustment range to no more than 1%), and gradually and evenly issues these instructions several hours before the shutdown begins, thereby preventing storage locations from exceeding limits during shutdown or when production resumes, achieving a smooth transition and safety assurance under special operating conditions.

[0050] The method also includes a fault degradation strategy, comprising multiple preset emergency operation modes. For example, when the system detects an anomaly in the data acquisition link that causes real-time warehouse data to fail, it automatically switches to the "maintain last valid value" mode, where the proportions of each production line maintain the valid value confirmed last time before the fault, and automatic adjustment is suspended. When the core trend judgment or proportion allocation algorithm module fails, the system can degrade to a "fixed threshold-based control mode," that is, based on the comparison results between real-time warehouse positions and fixed upper and lower limits, simplified proportion adjustments are performed, thereby providing basic automatic control functions even when the core intelligent algorithm fails, ensuring uninterrupted production.

[0051] Furthermore, as a response to the above Figure 1 In addition to the implementation of the method shown, this embodiment of the invention also provides an automatic adjustment device for high remix ratio, used for adjusting the above-mentioned... Figure 1 The method shown is implemented accordingly. This device embodiment corresponds to the foregoing method embodiment. For ease of reading, this device embodiment will not repeat the details of the foregoing method embodiment, but it should be clear that the device in this embodiment can implement all the contents of the foregoing method embodiment. Figure 2 As shown, the device includes: a calculation unit 21, a determination unit 22, and an execution unit 23, wherein... The calculation unit is used to calculate the total allocation adjustment range based on the moving average position trend that meets the persistence condition, wherein the moving average position trend is used to characterize the direction and intensity of position changes that have been smoothed and confirmed to be effective. The determining unit is used to determine the proportion adjustment instruction for each production line based on the total proportion adjustment range, the production line priority, and the degree of deviation of each production line's proportion from the preset optimal proportion. An execution unit is used to execute the proportion adjustment of each production line when the proportion adjustment instruction of the production line meets the safety standards.

[0052] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and adjusting kernel parameters can achieve a high-return-ratio automatic adjustment method, solving the problems of low accuracy and poor flexibility in existing high-return-ratio adjustments.

[0053] This invention provides a computer-readable storage medium including a stored program that, when executed by a processor, implements the high return ratio automatic adjustment method.

[0054] This invention provides a processor for running a program, wherein the program executes the high return ratio automatic adjustment method during runtime.

[0055] This invention provides an electronic device, which includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the high return ratio automatic adjustment method described above. This invention provides an electronic device 30, such as... Figure 3 As shown, the electronic device includes at least one processor 301, and at least one memory 302 and bus 303 connected to the processor; wherein, the processor 301 and the memory 302 communicate with each other through the bus 303; the processor 301 is used to call program instructions in the memory to execute the above-mentioned high return ratio automatic adjustment method.

[0056] The smart electronic devices mentioned in this article can be PCs, tablets, mobile phones, etc.

[0057] This application also provides a computer program product that, when executed on a process management electronic device, is suitable for executing a program that initializes the above-described high return ratio automatic adjustment method steps.

[0058] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0059] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0061] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0062] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0063] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to perform actions such as... Figure 1 The control flow of the memory in the corresponding embodiment.

[0064] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0065] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0066] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0067] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0068] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0069] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0070] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for automatically adjusting a high return ratio, characterized in that, include: The total allocation adjustment is calculated based on the moving average position trend that meets the persistence condition, wherein the moving average position trend is used to characterize the direction and intensity of position changes that have been smoothed and confirmed to be effective. Based on the total ratio adjustment range, and according to the production line priority and the degree of deviation of each production line's ratio from the preset optimal ratio, the ratio adjustment instruction for each production line is determined; If the ratio adjustment instructions for the production line meet safety standards, the ratio adjustment for each production line shall be executed.

2. The method according to claim 1, characterized in that, Also includes: Collect material level data from the return ore bins of each production line; Based on a preset physical conversion model, the height data of each material level is converted into material weight data; The total high-return warehouse space data is determined based on the material weight data.

3. The method according to claim 2, characterized in that, The calculation of the total allocation adjustment based on the moving average position trend that meets the persistence condition includes: The high-return total position data is smoothed to obtain a moving average position. Obtain the comparison result between the moving average position and the preset position midline, wherein the comparison result includes the deviation magnitude and duration; If both the deviation magnitude and duration meet the preset conditions, the moving average position trend that meets the persistence condition is confirmed. If a moving average position trend that meets the persistence condition is confirmed, the position change during the said duration is calculated. The corresponding calculation rule is selected based on the range of the absolute value of the position change, wherein the calculation rule corresponding to different ranges has different response coefficients. The total proportion adjustment range is determined based on the calculation rules.

4. The method according to claim 1, characterized in that, The step of determining the proportion adjustment instruction for each production line based on the overall proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: The set of production lines to be adjusted is determined from all production lines based on production line priority rules; The total adjustment range is taken as the total amount to be allocated; Obtain the current ratio value of each production line to be adjusted in the set of production lines to be adjusted; The absolute value of the difference between the current ratio value and the corresponding preset optimal ratio value of each production line to be adjusted is determined as the ratio deviation degree of each production line to be adjusted. The ratio deviation degree is used to quantify the gap between the current state and the ideal state of each production line.

5. The method according to claim 4, characterized in that, The step of determining the proportion adjustment instruction for each production line based on the overall proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: Performing a single iteration operation, wherein performing a single iteration operation includes: Select the production line with the smallest ratio deviation from the set of production lines to be adjusted as the target iterative adjustment object; Calculate the adjustable space of the target iterative adjustment object in the direction of the total ratio adjustment range, wherein the adjustable space is used to characterize the difference between the current ratio value of the adjustment object and the upper or lower limit of the ratio allowed by the process; The minimum value is selected from the absolute value of the remaining total ratio adjustment range, the preset single-step adjustment range upper limit, and the adjustable space as the single adjustment amount for this iteration, wherein the positive or negative sign of the single adjustment amount is the same as the direction of the total ratio adjustment range. The single adjustment amount is accumulated and added to the current ratio value of the target iterative adjustment object; The single adjustment amount is recorded as the proposed adjustment amount for the target iterative adjustment object, and the single adjustment amount is subtracted from the remaining total ratio adjustment range.

6. The method according to claim 5, characterized in that, The step of determining the proportion adjustment instruction for each production line based on the overall proportion adjustment range, according to the production line priority and the degree of deviation of each production line's proportion from the preset optimal proportion, includes: Determine whether the termination condition of the iteration is met, wherein the termination condition of the iteration is: the absolute value of the remaining total ratio adjustment range is less than a preset threshold, or each production line to be adjusted in the set of production lines to be adjusted has no adjustment space in the adjustment direction. If the iteration is not terminated, update the current ratio value and ratio deviation of each production line to be adjusted, and repeat the steps of the single iteration operation. In the event of termination of the iteration, the cumulative amount of adjustment to be made for each production line to be adjusted is determined as the ratio adjustment instruction.

7. The method according to claim 1, characterized in that, When the ratio adjustment instructions for the production line meet safety standards, the ratio adjustment for each production line is executed, including: If the ratio adjustment command of the production line exceeds the preset range threshold, a second confirmation is required; Based on the ratio adjustment instructions of the aforementioned production line, the ratio adjustment of each production line is executed; Record the operation log during the ratio adjustment process to generate audit trail information.

8. A high return ratio automatic adjustment device, characterized in that, Also includes: The calculation unit is used to calculate the total allocation adjustment range based on the moving average position trend that meets the persistence condition, wherein the moving average position trend is used to characterize the direction and intensity of position changes that have been smoothed and confirmed to be effective. The determining unit is used to determine the proportion adjustment instruction for each production line based on the total proportion adjustment range, the production line priority, and the degree of deviation of each production line's proportion from the preset optimal proportion. An execution unit is used to execute the proportion adjustment of each production line when the proportion adjustment instruction of the production line meets the safety standards.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed by a processor, it implements the steps of the high remix ratio automatic adjustment method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is configured to call program instructions in the memory to execute the steps of the high return ratio automatic adjustment method as described in any one of claims 1 to 7.

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