A multi-sensor quartz stone high-temperature water quenching process multi-dimensional parameter optimization system

Abstract

The present application relates to the technical field of quartz water quenching, and particularly relates to a multi-sensor quartzite high-temperature water quenching process multi-dimensional parameter optimization system; the system comprises a calcination monitoring module, a calcination analysis module, a water quenching monitoring module and a water quenching analysis module. The present application fuses multi-source sensing data such as images and acoustic emission, and constructs an intelligent closed-loop control from raw material pretreatment, calcination to water quenching; optimization is sought between crack development and energy consumption; the risk of over-crushing is judged online in combination with particle size and crack characteristics, and the cause is accurately attributed to overall process over-strength, subsequent crushing over-strength or cooling stress concentration, etc., according to which the corresponding calcination or water quenching parameters are adjusted; the traditional process relying on fixed parameters and artificial experience is changed into a self-adaptive dynamic optimization process with the final product quality and economic benefits as the target, the product consistency and production intelligent level of high-purity quartz sand production are improved, and the comprehensive goal of quality improvement, consumption reduction and stable production is finally achieved.

Description

Technical Field

[0001] This invention relates to the field of quartz water quenching technology, and in particular to a multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz. Background Technology

[0002] Calcination and water quenching is an important pretreatment method for removing impurities and purifying quartz sand. It usually involves first calcining the quartz ore or quartz sand at a temperature of 400–1400℃ or even higher, and then using cold water as a quenching agent to rapidly cool it down. The sudden temperature change causes the quartz to undergo rapid thermal expansion and contraction, generating a large number of microcracks on the surface and inside the quartz block. This can improve the crushing efficiency, promote the release of impurities in the intergranular spaces, and remove gas-liquid inclusions and some encapsulated solid mineral impurities from inside the mineral.

[0003] Chinese Patent Publication No. CN118387886A discloses a quartz particle water quenching system, including a water quenching tank, a conveying device, and a cooling device. The water quenching tank has a discharge port at the bottom. The conveying device includes a conveying cylinder, a filter screen, an auger, and a drive component. The inlet end of the conveying cylinder is connected to the discharge port, and the peripheral wall of the discharge end has a drain port and a discharge outlet. The discharge outlet is located away from the drain port from the water quenching tank. The filter screen is located at the drain port. The auger is rotatably built into the conveying cylinder. The drive component connects the conveying cylinder and the auger and is used to drive the auger to rotate around its axis. The cooling device includes a conveying pump and a cooler. The inlet end of the conveying pump is connected to the drain port, and the inlet end and outlet end of the cooler are respectively connected to the outlet end of the conveying pump and the water quenching tank. This prior art solution relies on fixed process parameters and offline detection, making it difficult to achieve real-time adjustment of the production process, which may affect the stability and consistency of product quality, and has limited ability to prevent risks such as excessive breakage. Summary of the Invention

[0004] To address this issue, the present invention provides a multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone, which overcomes the problem of unstable product quality and difficulty in precise control caused by the lack of real-time sensing and adaptive optimization in the prior art.

[0005] To achieve the above objectives, the present invention provides a multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz, comprising:

[0006] The calcination monitoring module is used to collect images of quartz blocks exiting the furnace at the calcination outlet and to plot calcination temperature curves based on temperature data during the calcination process.

[0007] The calcination analysis module, which is connected to the calcination monitoring module, is used to calculate the real-time crack development index based on the quartz image, and dynamically optimize the calcination process parameters according to the comparison results between the real-time crack development index and the preset standard crack development index. The calcination process parameters include at least calcination time and heating rate.

[0008] A water quenching monitoring module, which is connected to the calcination analysis module, is used to acquire continuous video clips of the particle quenching process in the water quenching tank and synchronous acoustic emission signals.

[0009] The water quenching analysis module is connected to the water quenching monitoring module and the calcination monitoring module respectively. It is used to determine whether there is a risk of excessive breakage based on the calcination temperature curve, particle size and crack characteristics after water quenching, and when there is a risk of excessive breakage, to analyze the cause of the risk and adjust the setting parameters of the water quenching process accordingly.

[0010] The water quenching analysis module obtains crack features based on the continuous video clips and analyzes the acoustic emission signals to obtain the particle size characteristics of the water-quenched particles.

[0011] Furthermore, the calcination analysis module includes:

[0012] The data extraction unit is used to extract quartz parameters based on quartz images;

[0013] The calculation unit is used to calculate the real-time crack development index based on quartz parameters;

[0014] The comparison unit is used to compare the real-time crack development index with the standard crack development index to obtain either a first comparison result or a second comparison result.

[0015] If the real-time crack development index is greater than or equal to the standard crack development index, the first comparison result is obtained;

[0016] If the real-time crack development index is less than the standard crack development index, a second comparison result is obtained;

[0017] The first parameter optimization unit is used to reduce the initial calcination heating rate in response to the first comparison result.

[0018] Furthermore, the calcination analysis module also includes:

[0019] The marginal effect analysis unit is used to plot the marginal effect curve based on the calcination time and impurity removal rate in response to the second comparison result;

[0020] The second parameter optimization unit is used to determine whether to update the initial calcination time based on the marginal effect curve. The calcination time corresponding to the inflection point of diminishing marginal effect is used as the initial calcination time for the next batch.

[0021] Furthermore, the quartz parameters include crack surface density, average crack length, crack fractal dimension, and grain roundness.

[0022] The calculation unit is used to calculate the real-time crack development index based on the quartz parameters using a preset weighted formula.

[0023] Furthermore, the marginal effect analysis unit includes:

[0024] The plotting sub-unit is used to draw a scatter plot with the calcination time in historical production data as the horizontal axis and the impurity removal rate of the corresponding batch as the vertical axis.

[0025] The analysis subunit is used to analyze the scatter plot to determine the inflection point of diminishing marginal returns.

[0026] Furthermore, the analysis subunit includes:

[0027] The curve fitting subunit is used to perform curve fitting on the scatter plot to obtain the functional relationship between the impurity removal rate and the calcination time.

[0028] The curve slope calculation subunit is used to calculate the first derivative of the function relationship in order to analyze the change of the curve slope;

[0029] The inflection point analysis subunit is used to determine that a diminishing marginal effect inflection point has occurred when the slope of the curve drops to a preset threshold.

[0030] Furthermore, the second parameter optimization unit includes:

[0031] The time optimization parameter subunit is used to update the calcination time corresponding to the inflection point of diminishing marginal effect to the initial calcination time of the next production batch in response to the occurrence of the inflection point of diminishing marginal effect.

[0032] The heating rate optimization parameter subunit is used to increase the initial calcination heating rate if no obvious inflection point is found, while keeping the current initial calcination time unchanged.

[0033] Furthermore, the water quenching analysis module includes:

[0034] The over-fragmentation risk analysis unit is used to determine whether there is an over-fragmentation risk based on the proportion of fine powder and cracks in the water-quenched product, and if it exists, to determine the cause of the over-fragmentation risk and obtain the first over-fragmentation risk, the second over-fragmentation risk and the third over-fragmentation risk.

[0035] The parameter mapping unit is used to optimize the corresponding set parameters in the intelligent control process in response to the cause of excessive fragmentation risk.

[0036] Furthermore, the over-fragmentation risk analysis unit includes:

[0037] The comparison sub-unit is used to compare the fine powder ratio with a first preset threshold and the crack ratio with a second preset threshold.

[0038] The analysis subunit is used to determine the risk of excessive breakage based on the proportion of fine powder and cracks in the water-quenched product. The risk of excessive breakage includes a first risk of excessive breakage, a second risk of excessive breakage, and a third risk of excessive breakage.

[0039] Furthermore, the parameter mapping unit includes:

[0040] The first mapping subunit is used to respond to the first risk of excessive crushing by simultaneously lowering the final temperature setpoint of the calcination stage and / or shortening the high-temperature period, and reducing the cooling intensity of the water quenching stage.

[0041] The second mapping subunit is used to adjust the process intensity of the crushing process in response to the second over-crushing risk.

[0042] The third mapping subunit is used to optimize the cooling curve of the water quenching stage in response to the third over-fragmentation risk, making it more gradual.

[0043] Compared with existing technologies, the advantages of this invention lie in its ability to construct a fully intelligent closed-loop control system for the entire process, from raw material pretreatment and calcination to water quenching, by integrating multi-source sensor data such as images and acoustic emissions. In the calcination stage, a comprehensive index characterizing crack development quality is calculated in real time. Based on the comparison between this index and dynamically updated process standard values, intelligent decisions are made on whether to reduce the heating rate to stabilize quality and save energy, or to initiate marginal effect analysis to scientifically extend the calcination time, thereby finding the optimal balance between crack development and energy consumption. In the water quenching stage, the overall particle size and crack characteristics are comprehensively assessed online. The risk of breakage is accurately attributed to factors such as excessive overall process strength, excessive subsequent crushing, or concentrated cooling stress. Based on this, the corresponding calcination or water quenching parameters are adjusted. The traditional process, which relies on fixed parameters and human experience, is transformed into an adaptive dynamic optimization process aimed at improving the quality and economic benefits of the final product. This enhances the product consistency (by stabilizing crack development), resource utilization efficiency (by avoiding ineffective energy consumption through marginal analysis), and the level of intelligent production (by multi-dimensional perception and closed-loop control) of high-purity quartz sand production, ultimately achieving the comprehensive goals of improving quality, reducing consumption, and stabilizing production. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to an embodiment of the present invention;

[0045] Figure 2 This is a schematic diagram of the calcination analysis module according to an embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of the marginal effect analysis unit in an embodiment of the present invention;

[0047] Figure 4 This is a schematic diagram of the water quenching analysis module according to an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0049] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0050] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0051] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0052] Please see Figure 1 As shown, this is a schematic diagram of the multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to an embodiment of the present invention. The present invention provides a multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone, comprising:

[0053] The calcination monitoring module is used to collect images of quartz blocks exiting the furnace at the calcination outlet and to plot calcination temperature curves based on temperature data during the calcination process.

[0054] The calcination analysis module, which is connected to the calcination monitoring module, is used to calculate the real-time crack development index based on the quartz image, and dynamically optimize the calcination process parameters according to the comparison results between the real-time crack development index and the preset standard crack development index. The calcination process parameters include at least calcination time and heating rate.

[0055] A water quenching monitoring module, which is connected to the calcination analysis module, is used to acquire continuous video clips of the particle quenching process in the water quenching tank and synchronous acoustic emission signals.

[0056] The water quenching analysis module is connected to the water quenching monitoring module and the calcination monitoring module respectively. It is used to determine whether there is a risk of excessive breakage based on the calcination temperature curve, the particle size and crack characteristics after water quenching, and to analyze the causes of the risk when there is a risk of excessive breakage and adjust the setting parameters of the water quenching process accordingly.

[0057] The water quenching analysis module obtains crack features based on the continuous video clips and analyzes the acoustic emission signals to obtain the particle size characteristics of the water-quenched particles.

[0058] This embodiment presents a multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz, used to optimize the quartz purification process including calcination and water quenching. The process includes: calcining the quartz particles to be calcined at a set temperature for a set time to induce a crystal transformation; then immersing the calcined high-temperature quartz particles in a quenching medium for rapid cooling, using thermal stress to induce cracks inside the quartz.

[0059] By integrating multi-source sensor data such as images and acoustic emissions, a fully intelligent closed-loop control system was constructed, encompassing raw material pretreatment, calcination, and water quenching. In the calcination stage, a comprehensive index characterizing crack development quality is calculated in real time. Based on the comparison between this index and dynamically updated process standard values, intelligent decisions are made: whether to reduce the heating rate to stabilize quality and save energy, or to initiate marginal effect analysis to scientifically extend the calcination time, thus finding the optimal balance between crack development and energy consumption. In the water quenching stage, the risk of excessive crushing is assessed online based on particle size and crack characteristics, accurately attributing it to factors such as excessive overall process strength, excessive subsequent crushing, or concentrated cooling stress. Corresponding calcination or water quenching parameters are then adjusted accordingly. This transforms the traditional process, which relies on fixed parameters and human experience, into an adaptive dynamic optimization process aimed at improving final product quality and economic benefits. This enhances the consistency of high-purity quartz sand production (through stable crack development), resource utilization efficiency (through marginal analysis to avoid ineffective energy consumption), and the level of production intelligence (through multi-dimensional perception and closed-loop control), ultimately achieving the comprehensive goals of improved quality, reduced consumption, and stable production.

[0060] See Figure 2 As shown, it is a schematic diagram of the calcination analysis module in an embodiment of the present invention;

[0061] Specifically, the calcination analysis module includes:

[0062] The data extraction unit is used to extract quartz parameters based on quartz images;

[0063] The calculation unit is used to calculate the real-time crack development index based on quartz parameters;

[0064] The comparison unit is used to compare the real-time crack development index with the standard crack development index to obtain either a first comparison result or a second comparison result.

[0065] If the real-time crack development index is greater than or equal to the standard crack development index, the first comparison result is obtained;

[0066] If the real-time crack development index is less than the standard crack development index, a second comparison result is obtained;

[0067] The first parameter optimization unit is used to reduce the initial calcination heating rate in response to the first comparison result.

[0068] In this embodiment, the standard crack development index represents a comprehensive score of the ideal crack development state that quartz particles should possess at the calcination discharge point under current production conditions in order to achieve the best final purification effect and particle integrity. The standard crack development index is set to 7.85, based on historical data. The specific process is as follows: data from the most recent 100 production batches are obtained, including process data and result data. Process data is the real-time crack development index calculated at the calcination discharge point, and result data is the final key indicators of the batch of quartz sand, including the Fe impurity removal rate and the proportion of fine powder after water quenching. A result screening threshold is set: Fe removal rate > 92%, fine powder proportion < 5%. 20 batches simultaneously meet both conditions and are marked as high-quality batches. The real-time crack development index of these 20 high-quality batches is extracted, and their average value is calculated as the standard crack development index. The crack development index is calculated by comparing the real-time crack development index with the standard crack development index. If the real-time crack development index is greater than or equal to the standard crack development index, it indicates that the cracks generated by the current calcination process have reached a high level of development in terms of quantity, quality, and particle morphology. Continuing to maintain or increase the heating rate will not only fail to bring about a linear improvement in purification effect, but may also lead to the formation of large through-cracks on the quartz surface due to excessive thermal stress concentration, or cause excessive embrittlement of particles, increasing the risk of excessive breakage during subsequent water quenching. In this case, the initial calcination heating rate should be reduced to decrease the energy consumption per unit product and prevent over-quality. If the real-time crack development index is less than the standard crack development index, it indicates that the cracks generated by the current calcination are not sufficiently developed and have not reached the historical high-quality level. In this case, the calcination time should be extended or the initial calcination heating rate should be increased. That is, marginal effect analysis should be introduced to determine whether it is worthwhile to extend the calcination time.

[0069] Specifically, the quartz parameters include crack surface density, average crack length, crack fractal dimension, and grain roundness.

[0070] The calculation unit calculates the real-time crack development index based on the quartz parameters using a preset weighting formula.

[0071] The preset weighting formula in this embodiment is:

[0072] ;

[0073] CDI stands for Real-Time Crack Development Index.

[0074] Nd is the crack surface density;

[0075] Lavg is the average crack length;

[0076] Fdim is the crack fractal dimension;

[0077] Rcirc represents the particle roundness;

[0078] For the corresponding weight parameters, ;

[0079] The above calculation process is illustrated below through a specific numerical example, but the present invention is not limited to this set of specific values: Through image analysis, the crack surface density of a certain batch of furnace-produced material is 15 cracks / mm², the average crack length is 0.12mm, the crack fractal dimension is 1.25, and the particle roundness is 0.85. Then, the real-time crack development index = [(0.4×15)+(0.3×0.12)+(0.3×1.25)]×(1 / 0.85) = (6.0+0.036+0.375)×1.176 = 6.411×1.176≈7.54.

[0080] In this embodiment, the determination of the crack development index weights is obtained through statistical analysis of historical high-quality production batches. A large amount of batch data accumulated from past production is collected. Each data point includes process parameters: crack surface density Nd, average length Lavg, fractal dimension Fdim, particle roundness Rcirc, and result indicators such as the final product's impurity removal rate, particle size qualification rate, and over-fragmentation rate. Multiple regression analysis or principal component analysis, known in the art, is used to quantify the contribution or correlation strength of each crack parameter to the final product quality, i.e., the target variables, such as high purity and low over-fragmentation. The analysis results will provide the standardized coefficients or importance ranking of each parameter. Based on this result, weights are proportionally allocated to each parameter; for example, the parameter with the largest contribution is given the highest weight, and the sum of the weights is 1. This embodiment provides... The specific values ​​such as 0.4 are merely illustrative results derived from the analysis of historical data of a particular production line. For different raw material characteristics or equipment conditions, the same analysis process can be followed to determine the optimal weight combination applicable to its own production line using its own production data.

[0081] Specifically, the calcination analysis module also includes:

[0082] The marginal effect analysis unit is used to plot the marginal effect curve based on the calcination time and impurity removal rate in response to the second comparison result;

[0083] The second parameter optimization unit is used to determine whether to update the initial calcination time based on the marginal effect curve. The calcination time corresponding to the inflection point of diminishing marginal effect is used as the initial calcination time for the next batch.

[0084] See Figure 3 As shown, it is a schematic diagram of the marginal effect analysis unit in an embodiment of the present invention;

[0085] Specifically, the marginal effect analysis unit includes:

[0086] The plotting sub-unit is used to draw a scatter plot with the calcination time in historical production data as the horizontal axis and the impurity removal rate of the corresponding batch as the vertical axis.

[0087] The analysis subunit is used to analyze the scatter plot to determine the inflection point of diminishing marginal returns.

[0088] Specifically, the analysis subunit includes:

[0089] The curve fitting subunit is used to perform curve fitting on the scatter plot to obtain the functional relationship between the impurity removal rate and the calcination time.

[0090] The curve slope calculation subunit is used to calculate the first derivative of the function relationship in order to analyze the change of the curve slope;

[0091] The inflection point analysis subunit is used to determine that a diminishing marginal effect inflection point has occurred when the slope of the curve drops to a preset threshold.

[0092] In this embodiment, the slope of the curve represents the improvement in impurity removal rate that can be achieved by increasing the calcination time by one unit, i.e., the marginal benefit. The preset threshold is a preset threshold for the decline of marginal benefit. This threshold is dynamically set according to the economic model of the production process. When the improvement in impurity removal rate brought about by extending the calcination time by one unit decreases to a certain percentage of the historical highest benefit, i.e., the peak slope, it is determined to be the inflection point of diminishing marginal benefit. As a preferred embodiment, this percentage can be set between 20% and 50%, preferably 40% of the peak slope. The preset threshold represents an acceptable lower limit of the "benefit-cost ratio". When net profit (represented by a percentage increase in removal rate) falls to a certain percentage of its historical peak benefit, it is considered that the cost-effectiveness of continuing to extend the time is too low. The initial value of this threshold can be preset according to the industry's general economic principles or the company's cost accounting model. It should be set within a reasonable range of 20% to 50%. Moreover, it can be dynamically defined based on real-time energy prices, product value, and other economic factors. This can be done by inputting the threshold through a simple management interface or by the system automatically fine-tuning it according to the cost model. Therefore, this threshold is not something that needs to be obtained through repeated experiments, but rather an engineering parameter that can be directly set according to clear economic objectives.

[0093] Specifically, a concrete data example is provided to illustrate the process of determining the inflection point of the marginal effect. The curve fitting subunit obtains a curve with gradually flattening growth. The curve slope calculation subunit analysis shows that increasing the calcination time from 2.5 hours to 3.0 hours increases the removal rate by 1.0 percentage point; while increasing it from 3.0 hours to 3.5 hours only increases the removal rate by 0.5 percentage points. The marginal benefit of the latter segment (0.5% / 0.5h) has decreased to 50% of that of the former segment (1.0% / 0.5h). The preset judgment threshold of the analysis subunit is that the marginal benefit decreases to 40% of the peak benefit. In this embodiment... The peak benefit is approximately 1.2% / 0.5h, which is in the earlier range. Its 40% is 0.48% / 0.5h. When the time increases from 3.0 hours to 3.5 hours, the actual marginal benefit of 0.5% / 0.5h is close to and below this threshold. Therefore, it is determined that the calcination time of 3.0 hours is the inflection point of diminishing marginal effect. Therefore, the initial calcination time of the next batch is set to 3.0 hours instead of continuing to use 3.5 hours. The small benefit brought by the extra 0.5 hours of calcination is automatically abandoned, which only increases the removal rate by 0.5%, in order to save a lot of energy and time costs, thereby maximizing the input-output ratio.

[0094] Specifically, the second parameter optimization unit includes:

[0095] The time optimization parameter subunit is used to update the calcination time corresponding to the inflection point of diminishing marginal effect to the initial calcination time of the next production batch in response to the occurrence of the inflection point of diminishing marginal effect.

[0096] The heating rate optimization parameter subunit is used to increase the initial calcination heating rate if no obvious inflection point is found, while keeping the current initial calcination time unchanged.

[0097] Among them, the current marginal benefit, represented by the slope, has decreased to below "peak marginal benefit × preset ratio", indicating that the inflection point of diminishing marginal effect has appeared.

[0098] In this embodiment, the corrected calcination heating rate is the sum of the initial calcination heating rate and the total adjustment. The total adjustment is the sum of the proportional term and the integral term. The proportional term is the product of the proportionality coefficient and the crack development index deviation. The crack development index deviation is the difference between the standard crack development index and the real-time crack development index of the current batch, with the proportionality coefficient set to 2. The integral term is the product of the integral coefficient and the cumulative deviation of the crack development index, with the cumulative deviation of the crack development index being the sum of the deviations of several past production batches, and the integral coefficient being 0.5. For example, if the standard crack development index is 7.85, when... The real-time crack development index of the previous batch was 7.0, and the crack development index deviation was 0.85. Deviations also existed in the past two batches, with a cumulative crack development index deviation of 1.0. The current initial calcination heating rate is 5℃ / min. The calculated proportional term is 2.0 × 0.85 = 1.7℃ / min; the calculated integral term is 0.5 × 1.0 = 0.5℃ / min; the calculated total adjustment is 1.7 + 0.5 = 2.2℃ / min; the corrected calcination heating rate is the initial calcination heating rate plus the total adjustment, which is 5 + 2.2 = 7.2℃ / min.

[0099] In this embodiment, extending the calcination time provides more time for crystal transformation and crack development without changing the thermal stress intensity. This almost eliminates the risk of thermal shock cracks and excessive fragmentation caused by rapid heating, ensuring the safety of the process. However, simply extending the time is inefficient, and the marginal effect must be considered. When the analysis reveals that the purity improvement brought by extending the time per unit time is lower than the energy cost, i.e., the output is lower than the input, it indicates low marginal benefit. It is necessary to switch to increasing the heating rate to promote crack development more directly by increasing thermal stress, thereby achieving the goal in a shorter time cost.

[0100] See Figure 4 As shown, it is a structural schematic diagram of the water quenching analysis module in an embodiment of the present invention;

[0101] Specifically, the water quenching analysis module includes:

[0102] The over-fragmentation risk analysis unit is used to determine whether there is an over-fragmentation risk based on the proportion of fine powder and cracks in the water-quenched product, and if it exists, to determine the cause of the over-fragmentation risk and obtain the first over-fragmentation risk, the second over-fragmentation risk and the third over-fragmentation risk.

[0103] The parameter mapping unit is used to optimize the corresponding set parameters in the intelligent control process in response to the cause of excessive fragmentation risk.

[0104] In this embodiment, the product sample after water quenching is sieved and analyzed to calculate the proportion of particles with a diameter smaller than the lower limit of the target particle size to the total mass, thus obtaining the fine powder ratio. The lower limit of the target particle size is 150 micrometers. The crack ratio is the proportion of penetrating large cracks. The particle image is analyzed by the vision system at the water quenching outlet. Using an image recognition algorithm, i.e., feature extraction based on aspect ratio and continuity, the number of particles with obvious, single, long straight cracks is counted, and the proportion of these particles to the total number of particles in the field of view is calculated as the crack ratio. The first preset threshold is the safe upper limit of the fine powder ratio, which is set to 5%. The second preset threshold is the safe upper limit of the proportion of penetrating large cracks, which is set to 10%.

[0105] Specifically, the over-fragmentation risk analysis unit includes:

[0106] The comparison sub-unit is used to compare the fine powder ratio with a first preset threshold and the crack ratio with a second preset threshold.

[0107] The analysis subunit is used to determine the first risk of excessive breakage when the proportion of fine powder in the water-quenched product is greater than the first preset threshold and the proportion of cracks is greater than the second preset threshold.

[0108] When the proportion of fine powder is greater than the first preset threshold, but the proportion of cracks is less than or equal to the second preset threshold, it is judged as the second over-crushing risk that focuses on the excessive strength of the subsequent crushing stage.

[0109] When the proportion of fine powder is less than or equal to the first preset threshold, but the proportion of cracks is greater than the second preset threshold, it is judged as the third risk of excessive crushing due to excessive concentration of cooling stress.

[0110] In this embodiment, when the fine powder ratio is >5% and the crack ratio is >10%, it indicates that both the calcination thermal stress and the water quenching cooling stress are too high, causing the particles to break macroscopically from the inside and be completely crushed on the outside. When the fine powder ratio is >5% but the crack ratio is ≤10%, it indicates that the crack development is normal, but too much fine powder indicates that the particles have been subjected to excessive mechanical force in the conveying, crushing or screening process after water quenching. When the fine powder ratio is ≤5% but the crack ratio is >10%, it indicates that the particles remain intact as a whole, that is, there is little fine powder, but harmful large cracks have been generated inside. This is because the water quenching cooling rate is too fast and uneven, resulting in excessive and concentrated release of thermal stress. It is necessary to optimize the cooling curve of the water quenching stage to make it more gradual and controllable.

[0111] Specifically, the parameter mapping unit includes:

[0112] The first mapping subunit is used to respond to the first risk of excessive crushing by simultaneously lowering the final temperature setpoint of the calcination stage and / or shortening the high-temperature period, and reducing the cooling intensity of the water quenching stage.

[0113] The second mapping subunit is used to adjust the process intensity of the crushing process in response to the second over-crushing risk.

[0114] The third mapping subunit is used to optimize the cooling curve of the water quenching stage in response to the third over-fragmentation risk, making it more gradual.

[0115] In this embodiment, optimizing the cooling curve of the water quenching stage means controlling the cooling rate of quartz particles over time by adjusting at least one of the following: the temperature, flow rate, spray pressure of the quenching medium, and the contact method between the particles and the medium, so that the cooling process from high temperature to low temperature tends to be gradual.

[0116] In this embodiment, in response to the first risk of over-crushing, the final calcination temperature is lowered by 40°C, the high-temperature period is shortened by 20 minutes, and the cooling intensity of the water quenching stage is reduced by increasing the water temperature by 10°C and decreasing the flow rate by 30% to allow for a more gentle and uniform release of thermal stress and avoid impact cracks. For example, if a batch of water-quenched products is found by online system detection to have a fine powder ratio of 7% and a penetrating large crack ratio of 15%, it is determined to be the first risk of over-crushing. The final calcination temperature is lowered from 920°C to 880°C, and the high-temperature period is simultaneously shortened from 120 minutes to 100 minutes. The cooling stage water temperature is increased from 20°C to 30°C, and the flow rate is reduced from 10 m³ / h to 7 m³ / h. In response to the second risk of over-crushing, the process intensity of the crushing stage is adjusted specifically including: for every 1 percentage point increase in the fine powder ratio, the discharge port size is increased by 3% of the current value, and... The feed rate is reduced by 5% of the current value. For example, if the current batch shows a fine powder ratio of 7% and a large through-crack ratio of 8%, and the current crusher (jaw crusher) operating parameters are a feed rate of 50 tons / hour and a discharge port setting of 15 mm, then the adjustment amount is calculated as follows: Discharge port adjustment: Adjustment increment = 15mm × (3% × 2) = 15mm × 6% = 0.9mm, then the new discharge port setting value = 15mm + 0.9mm = 15.9mm, which can be approximately set to 16mm; Feed rate adjustment: Adjustment reduction = 50t / h × (5% × 2) = 50t / h × 10% = 5t / h, then the new feed rate setting value = 50t / h - 5t / h = 45t / h; that is, the second mapping subunit sends the instruction to adjust the discharge port to 16mm and the feed rate to 45 tons / hour to the crusher control system of the pretreatment module.

[0117] In this embodiment, the specific process of optimizing the cooling curve during the water quenching stage is as follows: the current cooling method is switched to a three-stage gradual cooling curve. The first stage is gentle pre-cooling, the second stage is main cooling, and the third stage is stress relaxation. The gentle pre-cooling in the first stage prevents the surface from rapidly cooling and forming a hard shell, establishing a gentle initial temperature gradient. The cooling medium is set to 60°C warm water, with medium-speed stirring, for 3 seconds. The main cooling in the second stage, which is the critical temperature range where quartz is prone to cracking, provides strong but controllable cooling to promote the formation of effective microcracks. The cooling medium is set to 40°C water, with high-speed spraying for 5 seconds. The stress relaxation in the third stage stabilizes existing cracks by reducing the cooling rate in the low-temperature stage, preventing new macroscopic cracks from forming due to uneven shrinkage. For the cracks, the cooling medium is set to 60°C warm water, circulated at a low speed until it approaches the water temperature. In the first stage, 60°C water is used with an initial temperature difference of 740°C. The intensity is slightly reduced, but the key is to form a gradient with the subsequent stages. In the second stage, the particles have dropped to 600°C, and then 40°C water (temperature difference of 560°C) is used for the main cooling. At this time, the cooling intensity is much lower than that of the original process where 800°C is directly introduced into 20°C water. In the third stage, even gentler 60°C water is used to make the cooling process end smoothly. Through this optimization, the maximum cooling rate and the average cooling rate of the cooling curve are reduced, and the temperature drop process is smoother. This allows the thermal stress inside the quartz to be released more evenly and in a more controllable manner, thereby ensuring the formation of the required microcracks while effectively suppressing the generation of large through-cracks that lead to excessive fragmentation.

[0118] Specifically, a three-month comparative test was conducted on a production line with an annual output of 50,000 tons of high-purity quartz sand. The test was divided into two phases: the first phase (1 month) used the original fixed-parameter process; the second phase (2 months) implemented the multi-dimensional parameter optimization system described in this embodiment. The original fixed-parameter process consisted of key process parameters used on the production line, set based on historical experience and not automatically adjusted during production. This process did not have automatic parameter adjustments based on real-time sensor data and relied on fixed parameter settings and manual offline sampling for control. Specifically, the calcination stage used a fixed final temperature of 920℃, a heating rate of 5℃ / min, and a holding time of 120 minutes; the water quenching stage used a one-step drastic cooling method by directly immersing the high-temperature material in 20℃ cold water; the feeding rate of the pretreatment crushing stage was fixed at 50 tons / hour, and the discharge port size was 15 mm. The key comparisons between the two phases are shown in Table 1, which presents the comparative test results of the first and second phases.

[0119] Table 1 Comparison of test results between Phase 1 and Phase 2

[0120] ;

[0121] The results in Table 1 show that the system described in this embodiment maintains [its performance] through multi-sensor fusion and closed-loop optimization. While maintaining the removal rate, it improves the consistency of product particle size composition and reduces excessive fragmentation losses and energy consumption.

[0122] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz, characterized in that, include: The calcination monitoring module is used to collect images of quartz blocks exiting the furnace at the calcination outlet and to plot calcination temperature curves based on temperature data during the calcination process. The calcination analysis module, which is connected to the calcination monitoring module, is used to calculate the real-time crack development index based on the quartz image, and dynamically optimize the calcination process parameters according to the comparison results between the real-time crack development index and the preset standard crack development index. The calcination process parameters include at least calcination time and heating rate. A water quenching monitoring module, which is connected to the calcination analysis module, is used to acquire continuous video clips of the particle quenching process in the water quenching tank and synchronous acoustic emission signals. The water quenching analysis module is connected to the water quenching monitoring module and the calcination monitoring module respectively. It is used to determine whether there is a risk of excessive breakage based on the calcination temperature curve, the particle size and crack characteristics after water quenching, and to analyze the causes of the risk when there is a risk of excessive breakage and adjust the setting parameters of the water quenching process accordingly. The water quenching analysis module obtains crack features based on the continuous video clips and analyzes the acoustic emission signal to obtain the particle size characteristics of the water-quenched particles. The calcination analysis module includes: The data extraction unit is used to extract quartz parameters based on quartz images; The calculation unit is used to calculate the real-time crack development index based on quartz parameters; The comparison unit is used to compare the real-time crack development index with the standard crack development index to obtain either a first comparison result or a second comparison result. If the real-time crack development index is greater than or equal to the standard crack development index, the first comparison result is obtained; If the real-time crack development index is less than the standard crack development index, a second comparison result is obtained; The first parameter optimization unit is used to reduce the initial calcination heating rate in response to the first comparison result. The calcination analysis module also includes: The marginal effect analysis unit is used to plot the marginal effect curve based on the calcination time and impurity removal rate in response to the second comparison result; The second parameter optimization unit is used to determine whether to update the initial calcination time based on the marginal effect curve. The calcination time corresponding to the inflection point of diminishing marginal effect is used as the initial calcination time for the next batch.

2. The multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to claim 1, characterized in that, The quartz parameters include crack surface density, average crack length, crack fractal dimension, and grain roundness. The calculation unit is used to calculate the real-time crack development index based on the quartz parameters using a preset weighted formula.

3. The multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to claim 2, characterized in that, The marginal effect analysis unit includes: The plotting sub-unit is used to draw a scatter plot with the calcination time in historical production data as the horizontal axis and the impurity removal rate of the corresponding batch as the vertical axis. The analysis subunit is used to analyze the scatter plot to determine the inflection point of diminishing marginal returns.

4. The multi-sensor multi-dimensional parameter optimization system for high-temperature water quenching process of quartz stone according to claim 3, characterized in that, The analysis subunit includes: The curve fitting subunit is used to perform curve fitting on the scatter plot to obtain the functional relationship between the impurity removal rate and the calcination time. The curve slope calculation subunit is used to calculate the first derivative of the function relationship in order to analyze the change of the curve slope; The inflection point analysis subunit is used to determine that a diminishing marginal effect inflection point has occurred when the slope of the curve drops to a preset threshold.

5. The multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to claim 1, characterized in that, The second parameter optimization unit includes: The time optimization parameter subunit is used to update the calcination time corresponding to the diminishing marginal effect inflection point to the initial calcination time of the next production batch in response to the occurrence of the diminishing marginal effect inflection point. The heating rate optimization parameter subunit is used to increase the initial calcination heating rate if no obvious inflection point is found, while keeping the current initial calcination time unchanged.

6. The multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to claim 1, characterized in that, The water quenching analysis module includes: The over-fragmentation risk analysis unit is used to determine whether there is an over-fragmentation risk based on the proportion of fine powder and cracks in the water-quenched product, and if it exists, to determine the cause of the over-fragmentation risk and obtain the first over-fragmentation risk, the second over-fragmentation risk and the third over-fragmentation risk. The parameter mapping unit is used to optimize the corresponding set parameters in the intelligent control process in response to the cause of excessive fragmentation risk.

7. The multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to claim 6, characterized in that, The over-fragmentation risk analysis unit includes: The comparison sub-unit is used to compare the fine powder ratio with a first preset threshold and the crack ratio with a second preset threshold. The analysis subunit is used to determine the risk of excessive breakage based on the proportion of fine powder and cracks in the water-quenched product. The risk of excessive breakage includes a first risk of excessive breakage, a second risk of excessive breakage, and a third risk of excessive breakage.

8. The multi-sensor multi-dimensional parameter optimization system for the high-temperature water quenching process of quartz stone according to claim 7, characterized in that, The parameter mapping unit includes: The first mapping subunit is used to respond to the first risk of excessive crushing by simultaneously lowering the final temperature setpoint of the calcination stage and / or shortening the high-temperature period, and reducing the cooling intensity of the water quenching stage. The second mapping subunit is used to adjust the process intensity of the crushing process in response to the second over-crushing risk. The third mapping subunit is used to optimize the cooling curve of the water quenching stage in response to the third over-fragmentation risk, making it more gradual.

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