Donkey hide soaking device for donkey-hide gelatin production

Abstract

The invention relates to the technical field of colla corii asini production, and discloses a donkey hide soaking device for colla corii asini production, the donkey hide soaking device comprises a soaking box, a net support frame and an aeration assembly arranged at the bottom of the box, the core of the device is that an aeration intensity regulation and control system is integrated, and the aeration intensity regulation and control system is integrated through a system potential evaluation module, an environment state evaluation module and a task load evaluation module. Based on multi-source parameters such as aeration head aperture, spacing, soak solution depth, suspended solid concentration, water temperature, donkey hide loading density, softening degree and dicing size, a system potential factor, an environment resistance coefficient and a task load coefficient are output by utilizing a corresponding potential model, an environment model and a load model. According to the method, multi-factor intelligent coordinated regulation and control of the aeration intensity are realized, the problems of donkey hide sinking and adhesion, non-uniform softening and too high energy consumption caused by fixed aeration or single dissolved oxygen feedback in a traditional method are effectively solved, and the uniformity, stability and energy efficiency level of the donkey hide softening effect are remarkably improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of donkey-hide gelatin production, and particularly relates to a donkey-hide soaking device for donkey-hide gelatin production. BACKGROUND

[0002] As a traditional Chinese medicine treasure, the pretreatment of donkey-hide in the production process of donkey-hide gelatin is particularly crucial. Donkey-hide soaking is the first process of donkey-hide gelatin production, which directly affects the purity, yield and quality of the final product. Traditional donkey-hide soaking mostly adopts static pool soaking or simple bubbling method to remove impurities and promote softening through the physical action of water flow and air bubbles. However, such methods generally have the following defects:

[0003] Firstly, the air intake of the traditional aeration system is usually set according to experience or adopts a fixed rate, lacking the response ability to the dynamic changes of multiple variables in the production process. The loading density of donkey-hide, the size of the cut, the temperature of the soaking liquid and the concentration of suspended solids in water will affect the required aeration intensity in real time. Fixed aeration mode is easy to cause energy waste, or insufficient aeration when the load is large and the environmental resistance is strong, causing the donkey-hide to sink to the bottom, stick together and unevenly soften, affecting the subsequent processing and the quality of donkey-hide gelatin.

[0004] Secondly, the regulation of the aeration process in the prior art mostly relies on single dissolved oxygen feedback, which can achieve basic closed-loop control, but the response is lagging and the matching relationship between system hardware potential and production task load is not comprehensively considered. For example, in a high-potential aeration system with small aperture and dense arrangement, a uniform flow field can be achieved without high energy consumption; on the contrary, in the case of low system potential or difficult processing, stronger aeration support is needed. Lack of such systematic evaluation and matching makes it difficult for existing devices to achieve an optimal balance between energy efficiency and effect.

[0005] In addition, the layout of the aeration assembly and the design of the soaking tank structure in the traditional device also have defects, such as uneven distribution of aeration heads, non-adjustable liquid level, etc., which further limit the improvement of donkey-hide soaking effect. SUMMARY

[0006] The purpose of the embodiment of the application is to provide a donkey-hide soaking device for donkey-hide gelatin production, which aims to solve the above problems.

[0007] The application is implemented as follows: a donkey-hide soaking device for donkey-hide gelatin production, comprising a soaking tank and a net rack arranged in the soaking tank, further comprising: an aeration assembly arranged at the bottom of the soaking tank, which is used for aeration in the soaking tank; and an aeration intensity regulation system in communication connection with the control end of the aeration assembly, which is used for real-time adjustment of air intake, the aeration intensity regulation system comprising:

[0008] a system potential evaluation module, which outputs a system potential factor based on the aeration head aperture, the aeration head spacing and the immersion liquid depth through a system potential model;

[0009] an environment state evaluation module, which outputs an environment resistance coefficient based on the suspended solid concentration and the water temperature through an environment model;

[0010] a task load evaluation module, which outputs a task load coefficient based on the hide loading density, the softening degree and the cutting size through a task load model;

[0011] a system-load balance module, which outputs a system-load balance factor based on the system potential factor, the environment resistance coefficient and the task load coefficient through a system matching model;

[0012] a reference air intake amount calculation module, which obtains a reference air intake amount based on the system-load balance factor through a reference air intake amount calculation model;

[0013] an air intake amount regulation module, which outputs a target air intake amount and adjusts the current air intake to the target air intake amount based on the current dissolved oxygen concentration and the reference air intake amount through a regulation model.

[0014] Further technical solutions, the step of outputting a target air intake amount and adjusting the current air intake to the target air intake amount based on the current dissolved oxygen concentration and the reference air intake amount through a regulation model is:

[0015] a ratio processing of the difference between the current dissolved oxygen concentration and the dissolved oxygen set value and the dissolved oxygen set value to obtain a dissolved oxygen concentration index;

[0016] the dissolved oxygen concentration index and the reference air intake amount are introduced into the regulation model to obtain the target air intake amount and adjust the current air intake to the target air intake amount;

[0017] the regulation model is: wherein, the target air intake amount is, the reference air intake amount is, the regulation gain coefficient is, the dissolved oxygen concentration index is.

[0018] Further technical solutions, the reference air intake amount calculation model is: wherein, the reference air intake amount is, the maximum design air intake amount of the equipment is, the system-load balance factor is.

[0019] Further technical solutions, the system matching model is: wherein, the system-load balance factor is, the task load coefficient is, is a system potential factor, is an environmental resistance coefficient, , and are weight coefficients.

[0020] Further technical solutions, the system potential factor is output by the system potential model based on the aeration head aperture, the aeration head spacing and the immersion liquid depth, and the steps are:

[0021] The difference between the aeration head aperture, the aeration head spacing and the immersion liquid depth and the minimum value allowed by the corresponding equipment is processed by ratio, and the aeration head aperture index, the aeration head spacing index and the immersion liquid depth index are obtained;

[0022] The aeration head aperture index, the aeration head spacing index and the immersion liquid depth index are introduced into the system potential model to obtain the system potential factor;

[0023] The system potential model is: wherein, is a system potential factor, is an aeration head aperture index, is an aeration head spacing index, is an immersion liquid depth index, , and are weight coefficients.

[0024] Further technical solutions, the environmental resistance coefficient is output by the environmental model based on the suspended solid concentration and the water temperature, and the steps are:

[0025] The suspended solid concentration index is obtained by processing the current suspended solid concentration by ratio with the maximum suspended solid concentration;

[0026] The water temperature index is obtained by processing the difference between the current water temperature and the minimum temperature allowed by the system by ratio with the difference between the maximum temperature allowed by the system and the minimum temperature allowed by the system;

[0027] The suspended solid concentration index and the water temperature index are introduced into the environmental model to output the environmental resistance coefficient;

[0028] The environmental model is: wherein, is an environmental resistance coefficient, is a suspended solid concentration index, is a water temperature index, and are weight coefficients.

[0029] Further technical solutions, the loading density, softening degree and cutting size based on donkey skin, through the task load model output task load coefficient step is:

[0030] The loading density of donkey skin is compared with the maximum allowed loading density of the equipment, and a loading density index is obtained;

[0031] The soaking time is compared with the standard soaking period, and a softening degree index is obtained;

[0032] The cutting size of donkey skin is compared with the maximum allowed cutting size of the equipment, and a cutting size index is obtained;

[0033] The loading density index, softening degree index and cutting size index are imported into the task load model to output the task load coefficient;

[0034] The task load model is: , The task load coefficient is, The loading density index is, The softening degree index is, The cutting size index is, , And All are weight coefficients.

[0035] Further technical solutions, the aeration assembly includes a main air pipe fixedly arranged at the bottom of the soaking box, a plurality of branch air pipes are uniformly communicated with the main air pipe, a plurality of aeration heads are installed on the plurality of branch air pipes, and one end of the main air pipe extends out of the soaking box and is connected with a blower.

[0036] Further technical solutions, the soaking box is provided with a supporting platform, the supporting platform is fixedly provided with an extension piece at the bottom, the extension piece extends upward into the soaking box and is connected with a net supporting frame, the net supporting frame is slidingly arranged in the soaking box, a sewage pipe is arranged on the side wall of the soaking box, and a check valve is arranged on the sewage pipe.

[0037] Compared with the prior art, the beneficial effects of the present application are:

[0038] 1. By constructing a multi-module collaborative aeration intensity regulation system, the system hardware potential, real-time environmental state and production task load are comprehensively considered, the optimal air intake can be calculated and adjusted in real time according to the dynamic changes of multiple parameters such as donkey skin loading density, cutting size, water temperature, suspended solids concentration, aeration head configuration and liquid depth, which overcomes the hysteresis and one-sidedness of traditional fixed aeration or single dissolved oxygen feedback control, ensures uniform softening of donkey skin and prevents bottom adhesion, and significantly reduces unnecessary energy consumption;

[0039] 2. Based on the quantitative evaluation of the environmental potential (such as the uniformity of bubble distribution and the stability of flow field) by the system potential model, and the accurate characterization of the task load model for the difficulty of donkey skin processing, the aeration intensity can be optimally matched with the current working condition, whether it is high load, large cutting block, or system hardware potential limited, the system can be self-adapted to adjust, to ensure that the donkey skin is evenly heated and fully rolled during the whole soaking process, effectively avoiding local insufficient soaking or physical damage, thereby ensuring the uniformity and stability of the raw material quality of Ejiao batch;

[0040] 3. The system-load balancing factor is introduced as the core control parameter, which can sense, evaluate and respond to complex working condition changes by weighted fusion of multi-dimensional influencing factors, and the weight coefficients in each model can be adjusted according to the actual process requirements, which gives the device good flexibility and adaptability. The intelligent control mode reduces the dependence on the experience of operators, and improves the automation level and process controllability of the Ejiao production pretreatment process. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 A structure diagram of a donkey skin soaking device for Ejiao production is provided.

[0042] Figure 2 An internal structure diagram of the soaking tank is provided. Figure 1

[0043] Figure 3 A flowchart of the aeration intensity control system is provided.

[0044] In the drawings: 1, soaking tank; 2, net support; 3, sewage pipe; 4, main air pipe; 5, branch air pipe; 6, aeration head; 7, telescopic part; 8, support platform. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0046] In the prior art, the donkey skin soaking process in the production of Ejiao is mostly static pool soaking or simple bubbling. The traditional aeration system relies on fixed air intake or single dissolved oxygen feedback regulation, and cannot respond to the dynamic changes of donkey skin loading density, cutting size, water temperature and suspended solids concentration. For example, when the donkey skin loading density increases or the cutting block is large, the fixed aeration mode is easy to cause the donkey skin to stick to the bottom; in low temperature or high suspended solids concentration working condition, the dissolved oxygen feedback regulation has hysteresis, and it is difficult to maintain a uniform flow field.

[0047] ​To solve the above problems, the inventors found that the traditional aeration control only focuses on the dissolved oxygen concentration, ignoring the matching relationship between the system hardware potential and the production task load. Through analysis, it is found that the aeration head arrangement parameters affect the uniformity of bubble distribution, the liquid level depth determines the stability of the flow field, and the hide state directly affects the rolling resistance. Based on this, a multi-dimensional modeling of system potential, environmental state and task load is proposed to build a dynamic balance mechanism. By quantifying the support ability of hardware configuration to aeration efficiency, the degree of restriction of environmental conditions on aeration, and the processing difficulty of hide, a benchmark aeration amount calculation model is established, and then combined with real-time feedback of dissolved oxygen to realize closed-loop regulation.

[0048] The specific implementation of the present application is described in detail below in conjunction with specific embodiments.

[0049] As shown in Figure 1 and Figure 3 , a donkey skin soaking device for producing Ejiao is provided, which includes a soaking box 1 and a supporting net rack 2 arranged in the soaking box 1, and further includes: an aeration assembly arranged at the bottom of the soaking box 1, which is used for aeration in the soaking box 1; and an aeration intensity control system in communication connection with the control end of the aeration assembly, which is used for real-time adjustment of the air intake amount, wherein the aeration intensity control system comprises:

[0050] a system potential evaluation module, which outputs a system potential factor based on the aeration head aperture, the aeration head spacing and the soaking liquid depth through a system potential model;

[0051] an environmental state evaluation module, which outputs an environmental resistance coefficient based on the suspended solid concentration and the water temperature through an environmental model;

[0052] a task load evaluation module, which outputs a task load coefficient based on the loading density of the donkey skin, the softening degree (obtained by soaking time) and the cutting size through a task load model;

[0053] a system-load balance module, which outputs a system-load balance factor based on the system potential factor, the environmental resistance coefficient and the task load coefficient through a system matching model;

[0054] a benchmark air intake amount calculation module, which obtains a benchmark air intake amount based on the system-load balance factor through a benchmark air intake amount calculation model;

[0055] an air intake amount control module, which outputs a target air intake amount and adjusts the current air intake to the target air intake amount based on the current dissolved oxygen concentration and the benchmark air intake amount through a control model.

[0056] The aeration assembly refers to a device connected to the air blower through a pipeline and releasing bubbles to the soaking liquid. The system potential evaluation module refers to a unit for evaluating the support ability of the aeration system hardware configuration to the aeration efficiency. Specifically, the aperture, spacing and liquid depth data can be collected by a sensor, and the normalization processing and weighted calculation are realized to reflect the potential of the system to maintain a uniform flow field under low energy consumption. The environmental state evaluation module refers to a unit for quantifying the influence of environmental conditions on aeration resistance. Specifically, the data can be obtained by a turbidity sensor and a temperature sensor, and the ratio calculation and linear combination are realized to represent the comprehensive effect of suspended solids hindering bubble movement and water temperature affecting oxygen dissolution rate. The task load evaluation module refers to a unit for evaluating the difficulty of hide processing. Specifically, the loading density, soaking time and cut size data can be obtained by a weight sensor, a timer and an image recognition device, and the normalization processing and weighted calculation are realized to reflect the aeration intensity required for hide tumbling. The system-load balancing module refers to a unit for coordinating the system potential and task demand. Specifically, a linear weighted model can be used to integrate the three factors to dynamically balance the hardware support ability and processing difficulty. The reference air intake amount calculation module refers to a unit for determining the initial aeration amount. Specifically, the product of the maximum design air intake amount and the balancing factor can be calculated to generate a reference value suitable for the current working condition. The air intake amount regulation module refers to a unit for real-time adjustment of the aeration amount. Specifically, the current concentration can be monitored by a dissolved oxygen sensor, and the deviation ratio calculation and reference value correction are realized to maintain the dissolved oxygen level and optimize the energy consumption.

[0057] Specifically, when the device is working, the system potential evaluation module first collects the aperture, spacing and liquid depth data of the aeration head, calculates the system potential factor reflecting the uniformity of bubble distribution and the stability of flow field. The environmental state evaluation module synchronously obtains the suspended solids concentration and water temperature data to generate the coefficient representing the environmental resistance. The task load evaluation module outputs the load coefficient reflecting the processing difficulty through the hide weight, soaking time and cut size data. The system-load balancing module integrates the three factors according to the weight to generate the balancing factor to quantify the matching degree of system capacity and task demand. The reference air intake amount calculation module determines the initial aeration amount according to the balancing factor, and the air intake amount regulation module dynamically corrects the real-time monitoring value of dissolved oxygen to finally output the target air intake amount to drive the air blower to run.

[0058] Compared with the prior art, the traditional method only relies on the dissolved oxygen concentration to adjust the aeration amount, without considering the potential influence of hardware configuration on aeration efficiency. For example, when the aeration head spacing is large or the liquid level is shallow, it is difficult to eliminate the flow field dead angle even if the aeration amount is increased. However, the present scheme quantifies the support ability of hardware parameters on aeration effect through the system potential factor, and can more accurately predict the uniformity of the flow field under the same aeration amount. In addition, the traditional method does not establish the correlation between the hide state and the aeration demand, while the present scheme introduces the parameters such as hide loading density and cutting size into the control model through the task load coefficient, actively increases the aeration intensity when the hide processing difficulty increases, and avoids the adhesion of the bottom.

[0059] Through the above technical scheme, the present application realizes the accurate matching of aeration intensity and dynamic production demand. When the hide loading density fluctuates or the environmental temperature changes, the system automatically adjusts the aeration amount, which not only prevents the accumulation of hides due to insufficient aeration, but also avoids the waste of energy caused by excessive aeration. Through the comprehensive evaluation of hardware potential, environmental resistance and task load, it can ensure that a uniform flow field can be maintained under different working conditions, improve the uniformity of hide softening, and provide quality stable pretreated raw materials for subsequent processes.

[0060] Preferably, the step of outputting the target air intake amount through the control model and adjusting the current air intake to the target air intake amount based on the current dissolved oxygen concentration and the reference air intake amount is:

[0061] The difference between the current dissolved oxygen concentration and the dissolved oxygen set value is ratio processed with the dissolved oxygen set value to obtain a dissolved oxygen concentration index;

[0062] The dissolved oxygen concentration index and the reference air intake amount are introduced into the control model to obtain the target air intake amount and adjust the current air intake to the target air intake amount;

[0063] The control model is:

[0064] wherein, is the target air intake amount; is the reference air intake amount, which refers to the theoretically optimal air intake amount calculated by comprehensively considering the system hardware potential, environmental resistance and task load, and can be generated by a multi-parameter fusion model as a basic reference value for aeration intensity; is the control gain coefficient, which refers to the influence degree of dissolved oxygen deviation on air intake adjustment, and can be dynamically adjusted by experiment calibration or self-adaptive algorithm to balance the system response speed and stability; is the dissolved oxygen concentration index, which refers to the relative degree of deviation of the current dissolved oxygen concentration from the set value, and can be realized by real-time detection of the concentration value by the dissolved oxygen sensor, difference calculation with the set value and division by the set value. This index converts the absolute concentration deviation into a dimensionless parameter, eliminating the dimensional differences under different working conditions.

[0065] Specifically, the dissolved oxygen concentration index converts the real-time detected dissolved oxygen deviation into a proportional parameter through normalization processing, so that the regulation under different production batches or environmental conditions is comparable. The regulation model takes the reference air intake as the basic value, and adjusts the air intake according to the dissolved oxygen deviation The item realizes dynamic compensation: when the dissolved oxygen is lower than the set value, the target air intake is increased in proportion; when the dissolved oxygen is higher than the set value, the air intake is correspondingly reduced. The introduction of the regulation gain coefficient makes the system adjust the sensitivity to the dissolved oxygen deviation according to the actual demand, for example, setting a larger value to realize fast response at the beginning of the softening of the rawhide, and reducing the value to maintain stable operation in the later period. The model combines feedforward control and feedback control, the reference air intake provides feedforward based on multi-factor optimization, and the dissolved oxygen index provides closed-loop feedback correction, and the two work together to realize the dynamic balance of aeration intensity.

[0066] Compared with the prior art, the traditional method only relies on the closed-loop control of a single parameter of dissolved oxygen, and has the problems of response lag and ignoring the matching of system hardware potential and production load. The present scheme reflects the balance state of system potential and environmental load in advance through the reference air intake, and then dynamically adjusts in real time combined with the real-time feedback of dissolved oxygen, which not only retains the predictability advantage of feedforward control, but also has the correction ability of closed-loop control. For example, when the system potential decreases due to the blockage of the aeration head, the reference air intake will automatically increase to compensate for the loss of hardware performance, and the dissolved oxygen feedback will further correct the actual air supply, forming a double regulation mechanism.

[0067] Through the above technical scheme, the present application can realize real-time and fine regulation of aeration intensity, quickly respond when the dissolved oxygen concentration deviates from the set value, and at the same time avoid system oscillation caused by single parameter feedback. Through the synergistic effect of the reference air intake and the dissolved oxygen index, the balance relationship between the system hardware potential and the production task load is maintained, and the influence of environmental changes and model errors is effectively compensated, solving the problems of aeration regulation lag, energy consumption and effect difficult to consider in the traditional method.

[0068] Preferably, the reference air intake calculation model is:

[0069] wherein, the reference air intake is the optimal gas input calculated according to the dynamic matching relationship between the system hardware potential, the environmental state and the task load, which can be realized by real-time acquisition of equipment operating parameters and input into the calculation model, and is used to dynamically adjust the aeration intensity within the safe operation range of the equipment; The device maximum design air intake refers to the theoretical maximum gas delivery capacity of the aeration assembly under the rated working condition, which can be obtained through the performance parameters of the air blower or the factory calibration value of the device, and is used to provide a physical upper limit constraint for the reference air intake; The system-load balance factor refers to a comprehensive parameter reflecting the matching degree of the aeration system hardware potential, environmental resistance and horsehide processing task load, which can be generated by a multidimensional data fusion algorithm, and is used to quantify the adaptability of the current state of the system to the load demand.

[0070] Specifically, the reference air intake calculation model generates a reference value dynamically adapted to the current working condition by multiplying the device maximum design air intake and the system-load balance factor. The system-load balance factor is calculated by fusing multiple source data such as aeration head arrangement parameters, liquid level depth, water temperature, suspended solid concentration, horsehide loading density and softness. When the system hardware potential is low or the processing task load is high, the system-load balance factor tends to 1, and the reference air intake approaches the device maximum design value to overcome environmental resistance and meet processing demand; otherwise, the reference air intake is reduced to optimize energy efficiency. The model combines the theoretical capacity of the device with real-time working condition evaluation to ensure that the aeration intensity is always within the safe operating boundary, while providing a reasonable starting point for the subsequent closed-loop regulation of dissolved oxygen concentration.

[0071] Compared with the prior art, the traditional method usually adopts fixed air intake or single-variable adjustment relying only on dissolved oxygen feedback, which cannot dynamically adapt to the matching changes of system hardware potential and load demand. By introducing the system-load balance factor, the present scheme couples the hardware potential indicators such as aeration head arrangement parameters and liquid level depth with dynamic parameters such as water temperature and horsehide state for coupled analysis, so that the reference air intake can be automatically adjusted according to the comprehensive state of the system, solving the problem of excessive or insufficient aeration caused by ignoring the multi-factor coupling effect in the traditional method.

[0072] Through the above technical scheme, the present application generates the optimal reference air intake according to the dynamic matching relationship between the system potential and the load demand within the safe operating range of the device, avoids energy waste caused by not fully utilizing the hardware potential, and prevents the problem of insufficient aeration caused by a surge in load demand, laying a foundation for the subsequent precise regulation of dissolved oxygen concentration.

[0073] Preferably, the system matching model is:

[0074] wherein, The system-load balance factor is a comprehensive index generated by weighted fusion of the task load coefficient, the system potential factor and the environmental resistance coefficient, which is used to quantify the supply-demand matching degree under the current working condition of the aeration system, and can be realized by a linear weighted model. By adjusting the weight coefficient distribution, the contribution proportion of different parameters to the aeration demand is dynamically balanced, , the closer the value to 1, the worse the matching, the greater the intake air volume required, is the task load coefficient, reflecting the difficulty of the task, for example, high loading density or large cutting size will increase the aeration demand; is the system potential factor, indicating the hardware performance of the aeration system, for example, small aperture and dense aeration head can reduce the required aeration intensity; is the environmental resistance coefficient, reflecting the restriction of external conditions on aeration efficiency, for example, high suspended solids concentration will increase the flow resistance; , and are weight coefficients, which can be preset empirical values or dynamically adjusted, , and , and are greater than or equal to 0 and less than or equal to 1.

[0075] Specifically, the system matching model dynamically generates the system-load balancing factor by weighting the task load coefficient, system potential factor and environmental resistance coefficient. The weight coefficients , and are preset or self-adaptively adjusted according to actual working conditions, for example, when the system hardware potential is high, the weight of can be increased to prioritize the use of hardware advantages; when the environmental resistance is significant, the weight of is increased to compensate for external interference. The term in the model indicates that the system potential factor inversely affects the aeration demand, that is, the greater the system potential, the lower the required aeration volume. By calculating the value in real time, the model can comprehensively evaluate the matching relationship between the current system capacity, environmental interference and production task, providing dynamic adjustment basis for subsequent baseline intake air volume calculation, thereby optimizing energy utilization efficiency while ensuring the softening effect of the hide.

[0076] Compared with the prior art, the traditional aeration control method usually only relies on dissolved oxygen concentration or fixed parameter setting, without considering the dynamic influence of system hardware potential and environmental factors. For example, the hardware parameters such as aeration head arrangement density and liquid level depth are not included in the control model in the prior art, resulting in energy waste or insufficient aeration due to differences in system potential under the same dissolved oxygen condition. The present scheme introduces a multi-dimensional parameter fusion model to unify the quantification of hardware performance, environmental state and task load, breaking through the limitations of single parameter feedback and realizing precise adaptation of aeration intensity.

[0077] By the technical solution, the aeration intensity can be dynamically adjusted according to real-time working conditions, energy waste caused by insufficient utilization of hardware potential is avoided, and the aeration amount is automatically increased to maintain the softening effect under high environmental resistance or high task load conditions. For example, when the system adopts a small-diameter aeration head and the liquid level is deep, the model automatically reduces the baseline air intake amount, and when the hide piece is large or the water temperature is low, the air intake amount is increased to compensate for the processing difficulty. This dynamic balance mechanism effectively solves the problem of mismatch between aeration intensity and working conditions in the traditional method, and realizes energy efficiency optimization and quality stability of the hide softening process.

[0078] Preferably, the step of outputting the system potential factor by the system potential model based on the aeration head aperture, the aeration head spacing and the immersion liquid depth is:

[0079] The difference between the aeration head aperture, the aeration head spacing and the immersion liquid depth and the corresponding minimum value allowed by the equipment is processed by ratio to obtain the aeration head aperture index, the aeration head spacing index and the immersion liquid depth index;

[0080] The aeration head aperture index, the aeration head spacing index and the immersion liquid depth index are introduced into the system potential model to obtain the system potential factor;

[0081] The system potential model is:

[0082] wherein, the system potential factor, the value closer to 1 indicates that the system potential is greater, the system can realize uniform flow field distribution, efficient oxygen dissolution rate and gentle hide rubbing with relatively low air intake amount, thereby effectively preventing hide from sticking and adhering to the bottom, and promoting uniform softening, while avoiding physical damage to the hide caused by violent agitation, the aeration head aperture index is obtained by processing the difference between the current aeration head aperture and the minimum aeration head aperture allowed by the equipment by ratio to the difference between the maximum aeration head aperture allowed by the equipment and the minimum aeration head aperture allowed by the equipment, the aeration head aperture can be measured by a measuring tool before the equipment is operated, or the actual value of the aperture can be measured by a pressure sensor and compared and calculated with the allowed range in the equipment parameter database; the aeration head spacing index is obtained by processing the difference between the current aeration head spacing and the minimum aeration head spacing allowed by the equipment by ratio to the difference between the maximum aeration head spacing allowed by the equipment and the minimum aeration head spacing allowed by the equipment, and the adjacent aeration head spacing can be monitored in real time by a laser range finder; The soaking liquid depth index is obtained by ratio processing of the difference between the current soaking liquid depth and the minimum soaking liquid depth allowed by the device and the difference between the maximum soaking liquid depth allowed by the device and the minimum soaking liquid depth allowed by the device, and the soaking liquid depth index can be obtained by real-time acquisition of the liquid depth data by the liquid level sensor. , and are weight coefficients, which can be preset empirical values or dynamically adjusted, , and , and are greater than or equal to 0 and less than or equal to 1.

[0083] Specifically, indicates that the smaller the pore size, the finer and denser the bubbles, the more uniform the stirring effect, the higher the oxygen mass transfer efficiency, and the greater the system potential; indicates that the smaller the distance, the more uniform the bubble coverage, the fewer the dead angle areas, and the greater the system potential; indicates that the greater the depth, the longer the development distance of the "plume" formed by the liquid level and the bubbles, which helps to form a more stable and macroscopic circulating flow field in the pool, which makes it difficult for the hide to accumulate on the bottom and roll more uniformly, avoiding local insufficient soaking or dead zones, ensuring the uniformity of batch quality, and the greater the system potential; the system potential model dynamically evaluates the theoretical performance upper limit of the aeration system under the current hardware configuration by weighted fusion of the three indexes, and the optimization direction of the pore size and the distance is to approach the minimum value, and the optimization direction of the liquid depth is to approach the maximum value. For example, when the system potential factor calculation result is 0.2, it indicates that the current aeration head arrangement is dense, the pore size is small, and the liquid depth is sufficient, and the system has the hardware condition to realize effective stirring with low aeration intensity.

[0084] Compared with the prior art, the traditional soaking device only sets the aeration intensity according to fixed parameters, without considering the influence of distance adjustment caused by equipment modification or liquid depth difference of different batches on system performance. The present scheme dynamically corrects the system potential factor by real-time monitoring of hardware parameter changes, so that the aeration intensity is always matched with the current equipment state.

[0085] Through the above technical scheme, the present application solves the problem of aeration intensity adaptation failure caused by fixed hardware parameters, and realizes automatic adjustment of air intake according to the actual pore size, distance and liquid depth. When the aeration head is worn and the pore size is enlarged, the system automatically increases the air intake to compensate for the loss of oxygen mass transfer efficiency caused by the increase in bubble size; when the equipment is modified to shorten the distance between the aeration heads, the system correspondingly reduces the air intake to avoid energy waste; when the soaking liquid depth changes in different batches, the system automatically optimizes the air intake to maintain a stable fluid circulation path. The technical scheme ensures uniform softening of the hide while effectively reducing energy consumption fluctuations caused by changes in hardware parameters.

[0086] Preferably, the step of outputting the environmental resistance coefficient based on the suspended solid concentration and the water temperature by the environmental model is:

[0087] The current suspended solid concentration is compared with the maximum suspended solid concentration to obtain a suspended solid concentration index;

[0088] The difference between the current water temperature and the minimum temperature allowed by the system is compared with the difference between the maximum temperature allowed by the system and the minimum temperature allowed by the system to obtain a water temperature index;

[0089] The suspended solid concentration index and the water temperature index are input into the environmental model to output the environmental resistance coefficient;

[0090] The environmental model is:

[0091] wherein, is the environmental resistance coefficient, which is a quantitative evaluation value of the comprehensive environmental factors on the operation resistance of the aeration system, and can specifically be obtained by superimposing the suspended solid concentration index and the water temperature index according to a preset weight using a linear weighting algorithm, for dynamically correcting the aeration intensity parameter, , the value closer to 1 indicates that the environmental resistance is greater, and a larger aeration amount is required to drive the horsehide to roll, is the suspended solid concentration index, which is a ratio of the current suspended solid content in the immersion liquid to the maximum concentration allowed by the process, and can specifically be obtained by detecting the suspended solid concentration data in real time using a turbidity sensor, to reflect the influence degree of impurities on the water flow resistance; is the water temperature index, which is a relative position of the current temperature in the system operation temperature interval, and can specifically be obtained by collecting the immersion liquid temperature data using a temperature sensor, and by normalizing to represent the inhibition of the liquid viscosity change on the rising speed of the bubbles; and are weight coefficients, which can specifically be a preset empirical value or dynamically adjusted, , and and are both greater than or equal to 0 and less than or equal to 1.

[0092] Specifically, the technical scheme establishes a mathematical relationship model between the environmental factors and the aeration demand, to realize quantitative evaluation of the environmental resistance. When the turbidity sensor detects that the suspended solid concentration increases, the system automatically calculates the suspended solid concentration index, which is a ratio of the maximum allowed concentration and directly reflects the degree of hindrance of impurities to the water flow. The water temperature data monitored in real time by the temperature sensor is normalized to generate the water temperature index. In a low temperature state, the increase of the liquid viscosity leads to the slowing down of the rising speed of the bubbles, and the water temperature index is used to dynamically correct the aeration intensity parameter, Item reverse correlation aeration demand. After inputting two indexes into a linear weighting model, the output environmental resistance coefficient can comprehensively represent the current environment resistance to the operation of the aeration system, and the weight coefficient can be dynamically configured according to the primary and secondary relationship of environmental factors in different production stages. For example, in the winter low-temperature environment, the regulation effect of the water temperature factor can be improved by increasing the value of the water temperature factor.

[0093] Compared with the prior art, the traditional method only sets fixed aeration parameters according to experience or relies on dissolved oxygen feedback alone, and cannot effectively respond to dynamic changes in environmental factors. The prior art does not establish a combined evaluation model of suspended solid concentration and water temperature, resulting in a lag in the adjustment of aeration intensity when the impurity concentration suddenly increases or the temperature suddenly drops, and easy occurrence of insufficient horsehide rolling or energy waste. The present scheme realizes real-time response to complex environmental conditions by constructing a double-factor environmental resistance model, and solves the technical problem of mismatch between environmental resistance and aeration intensity.

[0094] Through the above technical scheme, the present application can accurately adjust the aeration intensity according to the real-time environmental state, automatically increase the aeration amount when the suspended solid concentration increases to overcome the water flow resistance, and increase the kinetic energy of the rising bubbles in the low-temperature environment to maintain the horsehide rolling effect. The present scheme effectively prevents the phenomenon of horsehide sticking to the bottom due to sudden change of environmental resistance, and avoids excessive energy consumption of the constant aeration mode when the environmental conditions improve, thereby realizing dynamic balance between environmental resistance and aeration intensity.

[0095] Preferably, the loading density, softness (obtained by soaking time) and cutting size of the horsehide are based on the task load model output task load coefficient steps:

[0096] The loading density of the horsehide is compared with the maximum allowed loading density of the equipment to obtain a loading density index;

[0097] The soaking time is compared with the standard soaking period to obtain a softness index;

[0098] The cutting size of the horsehide is compared with the maximum allowed cutting size of the equipment to obtain a cutting size index;

[0099] The loading density index, softness index and cutting size index are input into the task load model to output a task load coefficient;

[0100] The task load model is:

[0101] wherein, the task load coefficient, the value is closer to 1, indicating that the horsehide processing difficulty is greater, and a larger aeration amount is required to drive the horsehide to roll, the loading density index, ​Small, the donkey skin has sufficient space to roll, the water flow resistance is small, the bubbles can smoothly rise, the aeration effect is good, is a softening degree index, The smaller, the softer the donkey skin, the donkey skin becomes flexible, and it is easier to move with the water flow, is a cutting size index, The smaller, the easier the donkey skin rolls, , and are weight coefficients, and the weight coefficients can specifically adopt preset empirical values or dynamic adjustment. , and , and are greater than or equal to 0 and less than or equal to 1.

[0102] Among them, the loading density can be specifically measured by a weighing sensor to measure the total mass and calculated by combining the soaking tank volume, for quantifying the influence of donkey skin accumulation on water flow resistance. The softening degree can be specifically realized by a timer to record the soaking time, for reflecting the reduction of the movement resistance by the flexibility of the donkey skin. The cutting size can be specifically realized by an image recognition technology to measure the surface area of the donkey skin, for representing the restriction of the physical form on the rolling difficulty. The task load model refers to a mathematical relationship formula of weighted fusion of the three indexes, and can be specifically realized by a linear weighted summation algorithm, and the weight coefficients adjust the contribution degrees of various factors according to process requirements.

[0103] Specifically, when the loading density is high, the water flow resistance increases due to the reduced gap between the donkey skins, at this time, the loading density index tends to 1, which promotes the increase of the task load coefficient, and the system automatically increases the aeration intensity to enhance the water flow power. With the extension of soaking time, the softening degree index gradually decreases, the rolling resistance decreases due to the increased flexibility of the donkey skin, the task load coefficient correspondingly decreases, and the aeration amount decreases to avoid energy waste. When processing large-size donkey skin pieces, the cutting size index tends to 1, the model automatically increases the weight proportion of this parameter, and compensates for the increased movement resistance by increasing the aeration intensity. The dynamic cooperative calculation of the three parameters makes the aeration intensity always match the current processing difficulty.

[0104] Compared with the prior art, the traditional method only sets a fixed aeration amount according to experience or relies on single dissolved oxygen parameter feedback, and cannot respond to changes in donkey skin loading, differences in softening process and fluctuations in cutting size. The present scheme realizes the quantitative evaluation of the production task load by establishing a multi-dimensional parameter fusion model, can accurately identify the composite processing difficulty formed by the superposition of high-density loading, low-softening degree and large-size cutting, and dynamically adjusts the aeration intensity.

[0105] By the technical scheme, the application effectively solves the problem of mismatch between the fixed aeration mode and the dynamic treatment demand, avoids the problem of leather skin adhesion caused by insufficient aeration in high-density loading, prevents uneven softening caused by insufficient aeration in the low-softening stage, and eliminates the local rolling failure phenomenon in large-size cutting treatment. Under the premise of ensuring uniform softening of the leather skin, the aeration amount in the completed softening batch or low-density loading is dynamically reduced, and the energy consumption is significantly reduced.

[0106] As shown in Figure 1 and Figure 2 , as a preferred embodiment of the application, the aeration assembly comprises a main air pipe 4 fixedly arranged at the bottom of the soaking tank 1, a plurality of branch air pipes 5 are uniformly communicated with the main air pipe 4, and a plurality of aeration heads 6 are installed on the plurality of branch air pipes 5. One end of the main air pipe 4 extends out of the soaking tank 1 and is connected with a blower.

[0107] In the embodiment of the application, the gas output by the blower enters the soaking tank 1 through the main air pipe 4, is transported to different areas through the plurality of uniformly distributed branch air pipes 5, and is finally released as a dense and small bubble group by the aeration heads 6 on the branch air pipes 5. The bubbles form a uniform flow field during the rising process, drive the leather skin to continuously roll, and avoid adhesion to the bottom. The main air pipe 4 serves as the main gas distribution channel, ensuring that the gas pressures of the branch air pipes 5 are balanced. The uniform arrangement of the branch air pipes 5 extends the bubble coverage range to the entire bottom of the soaking tank 1. The multi-point dispersion design of the aeration heads 6 makes the bubble distribution density consistent, reducing the differences in leather skin treatment caused by bubble aggregation or absence in local areas. The hierarchical gas supply structure realizes the collaborative control of bubble distribution uniformity and aeration intensity through physical layout optimization.

[0108] As shown in Figure 1 and Figure 2 , as a preferred embodiment of the application, the soaking tank 1 is provided with a support platform 8, the support platform 8 is fixedly provided with an extension piece 7 at the bottom, the extension piece 7 extends upward into the soaking tank 1 and is connected with a net supporting frame 2, the net supporting frame 2 is slidingly arranged in the soaking tank 1, a sewage pipe 3 is arranged on the side wall of the soaking tank 1, and a check valve is arranged on the sewage pipe 3.

[0109] In the embodiment of the present application, the telescopic member 7 can be a pneumatic cylinder or an electric telescopic rod, etc. During the soaking stage, the telescopic member 7 drives the net support 2 to descend into the soaking liquid, the hide is placed on the net support 2, the bubbles generated by aeration push the water flow to form a circulation, and the net support 2 blocks the hide from sinking to the bottom of the tank to avoid contact with the sediment impurities. During the sewage stage, the telescopic member 7 lifts the net support 2 above the liquid surface, so that the impurities are exposed to the bottom of the tank, when the sewage pipe 3 is opened, the impurities are automatically discharged, and after the sewage pipe 3 is closed, the check valve is closed. The sliding guide structure of the net support 2 ensures smooth lifting process and avoids hide displacement caused by mechanical vibration. The support platform provides rigid support for the telescopic member to prevent the soaking tank 1 from being deformed due to stress and affecting the lifting accuracy.

[0110] The above merely describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A donkey skin soaking device for producing Ejiao, comprising a soaking box and a supporting net rack arranged in the soaking box, characterized in that, Also comprising: An aeration assembly arranged at the bottom of the soaking tank, the aeration assembly being configured to aerate the soaking tank; An aeration intensity regulation system in communication with the control end of the aeration assembly, configured to adjust the air intake in real time, the aeration intensity regulation system comprising: A system potential evaluation module configured to output a system potential factor based on the aeration head aperture, the aeration head spacing, and the soaking liquid depth through a system potential model; An environmental state evaluation module configured to output an environmental resistance coefficient based on the suspended solid concentration and the water temperature through an environmental model; A task load evaluation module configured to output a task load coefficient based on the hide loading density, the softening degree, and the hide cutting size through a task load model; A system-load balance module configured to output a system-load balance factor based on the system potential factor, the environmental resistance coefficient, and the task load coefficient through a system matching model; A reference air intake amount calculation module configured to obtain a reference air intake amount based on the system-load balance factor through a reference air intake amount calculation model; An air intake amount regulation module configured to output a target air intake amount based on the current dissolved oxygen concentration and the reference air intake amount through a regulation model and adjust the current air intake to the target air intake amount.

2. The donkey skin soaking device for producing donkey-hide gelatin according to claim 1, characterized in that, The step of outputting the target air intake amount based on the current dissolved oxygen concentration and the reference air intake amount through the regulation model and adjusting the current air intake to the target air intake amount comprises: Processing the difference between the current dissolved oxygen concentration and the dissolved oxygen set value and the dissolved oxygen set value by ratio to obtain a dissolved oxygen concentration index; Inputting the dissolved oxygen concentration index and the reference air intake amount into the regulation model to obtain the target air intake amount and adjust the current air intake to the target air intake amount. The control model is: wherein, is a target intake amount, is a reference intake amount, is a control gain coefficient, is a dissolved oxygen concentration index.

3. The donkey skin soaking device for producing donkey-hide gelatin according to claim 2, characterized in that, The reference intake amount calculation model is: wherein, is the reference intake amount, is the maximum design intake amount of the device, is a system-load balancing factor.

4. The donkey skin soaking device for producing donkey-hide gelatin according to claim 3, characterized in that, The system matching model is: wherein, is a system-load balancing factor, is a task load coefficient, is a system potential factor, is an environmental resistance coefficient, , and are weight coefficients.

5. The donkey skin soaking device for producing donkey-hide gelatin according to claim 4, characterized in that, The step of outputting the system potential factor based on the aeration head aperture, the aeration head spacing, and the soaking liquid depth through the system potential model comprises: Processing the difference between the aeration head aperture, the aeration head spacing, and the soaking liquid depth and the corresponding minimum value allowed by the equipment by ratio to the equipment allowed deviation range to obtain an aeration head aperture index, an aeration head spacing index, and a soaking liquid depth index; Inputting the aeration head aperture index, the aeration head spacing index, and the soaking liquid depth index into the system potential model to obtain the system potential factor. The system potential model is: wherein, is the system potential factor, is the aeration head aperture index, is the aeration head spacing index, is the submergence depth index, , and are weighting factors.

6. The donkey skin soaking device for producing donkey-hide gelatin according to claim 4, characterized in that, The step of outputting the environmental resistance coefficient based on the suspended solid concentration and the water temperature through the environmental model comprises: Processing the current suspended solid concentration by ratio to the maximum suspended solid concentration to obtain a suspended solid concentration index; Processing the difference between the current water temperature and the minimum temperature allowed by the system by ratio to the difference between the maximum temperature allowed by the system and the minimum temperature allowed by the system to obtain a water temperature index; Inputting the suspended solid concentration index and the water temperature index into the environmental model to output the environmental resistance coefficient. The environmental model is: wherein, is an environmental resistance coefficient, is a suspended solids concentration index, is a water temperature index, and are weighting coefficients.

7. The donkey skin soaking device for producing donkey-hide gelatin according to claim 4, characterized in that, The step of outputting the task load coefficient based on the hide loading density, the softening degree, and the hide cutting size through the task load model comprises: Processing the hide loading density by ratio to the maximum allowed loading density of the equipment to obtain a loading density index; Processing the soaking time by ratio to the standard soaking period to obtain a softening degree index; Processing the hide cutting size by ratio to the maximum allowed cutting size of the equipment to obtain a cutting size index; Inputting the loading density index, the softening degree index, and the cutting size index into the task load model to output the task load coefficient. The task load model is: wherein, is a task load coefficient, is a loading density index, is a softness index, is a dicing size index, , and are weight coefficients.

8. The donkey skin soaking device for producing donkey-hide gelatin according to claim 1, characterized in that, The aeration assembly comprises a main air pipe fixed on the bottom of the soaking tank, a plurality of branch air pipes connected to the main air pipe, and a plurality of aeration heads installed on the branch air pipes.

9. The donkey skin soaking device for producing donkey-hide gelatin according to claim 1, characterized in that, A supporting platform is installed on the bottom of the soaking tank, a telescopic member is fixed on the bottom of the supporting platform, the telescopic member extends into the soaking tank and is connected to a net supporting frame, the net supporting frame is slidingly arranged in the soaking tank, a sewage pipe is installed on the side wall of the soaking tank, and a check valve is installed on the sewage pipe.

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