Self-adaptive control method for lead clothes disinfection

Abstract

The invention discloses a self-adaptive control method for lead clothes disinfection, and relates to the technical field of intelligent control. The method comprises the following steps: constructing a lead clothes management library, obtaining a lead clothes demand condition, obtaining lead clothes use parameters and material parameters, obtaining a self-adaptive control instruction through a self-adaptive disinfection control model, monitoring the lead clothes disinfection process in real time, adaptively adjusting disinfection parameters, and optimizing the self-adaptive disinfection control model by using a disinfection historical record. According to the method, the self-adaptive disinfection control model is used for matching the first batch of recommended disinfection modes according to the lead garment material parameters, the demand index and the bacterial pollution index are calculated, the optimal second batch of disinfection modes are dynamically selected from the recommended disinfection modes, and the disinfection parameters are adjusted by using real-time monitoring data.

Description

Technical Field

[0001] The invention relates to the field of intelligent control technology, and in particular to an adaptive control method for lead clothing disinfection. Background Art

[0002] Lead aprons are widely used in the fields of radiology and nuclear medicine as medical protective equipment to shield the human body from the harm of ionizing radiation. However, during high-frequency use, the surface of lead aprons is easily invaded by bacteria, viruses and other contaminants. If they are not properly cleaned and disinfected, it may not only cause cross infection, but also affect the protective performance and service life of the lead aprons due to improper operation during the disinfection process.

[0003] Existing methods for disinfecting lead clothing include manual wiping, ultraviolet irradiation, chemical reagent treatment, etc., but these methods are mostly fixed modes and lack the ability to dynamically adjust to actual conditions. Due to differences in lead clothing materials, protection levels, and usage scenarios, different lead clothing have different adaptability to disinfection methods. Fixed disinfection parameters may lead to waste of resources or insufficient disinfection, and it is difficult to meet diverse needs. Therefore, a method that can adaptively adjust the disinfection scheme according to the actual situation of the lead clothing is needed to achieve a more efficient and accurate disinfection effect.

[0004] Based on this, an adaptive control method is proposed. Through comprehensive analysis of data such as lead suit material parameters, usage records, and demand forecasts, combined with real-time monitoring and feedback mechanisms, the optimal disinfection scheme is dynamically matched and disinfection parameters are adjusted. This method can not only improve the efficiency and accuracy of the disinfection process, but also provide personalized solutions according to different actual needs, thereby overcoming the shortcomings of existing technologies and providing technical support for the scientific management and efficient disinfection of lead suits. Summary of the invention

[0005] An adaptive control method for lead clothing disinfection comprises the following steps: Step S1: construct a lead clothing management library containing all digital samples of lead clothing; classify the digital samples of lead clothing into types according to the type parameters of lead clothing in the lead clothing management library, and count the number of lead clothing; the type parameters include style, protection and portability, wherein the style is represented by letters and numbers, and the protection and portability are represented by grades; construct a replacement table for the lead clothing type, and the replacement table serves as a reference for the replacement of different types of lead clothing; Step S2: Counting the usage records of lead vests by time, training a lead vest demand prediction model based on the usage records of lead vests, obtaining the lead vest inventory based on the lead vest management database, and inputting the lead vest inventory into the lead vest demand prediction model to obtain the demand for lead vests in the current period, wherein the demand is specifically the demand for each type of lead vest; Step S3: Obtain the lead suit label by manual input or image scanning, obtain the lead suit digital sample in the lead suit management library through the lead suit label, and extract the material parameters of the lead suit from the lead suit digital sample; obtain the use record of the lead suit, and extract the use parameters of the lead suit through the use record, wherein the use parameters include the use scene, the use duration and the contact object information; Step S4: inputting the material parameters, usage parameters and demand conditions of the lead suit into the adaptive disinfection control model for calculation to obtain an adaptive control instruction, wherein the adaptive control instruction includes a disinfection control instruction and a recovery control instruction; the disinfection control instruction is used to control the disinfection of the lead suit; the adaptive disinfection control model outputs and limits the disinfection control instruction according to the available disinfection method before use; the recovery control instruction is used to control the recovery of the disinfected lead suit to restore the lead suit to a state to be used, the recovery operation includes drying and removing residual disinfectant, and the recovery control instruction is obtained based on the matching of the disinfection control instruction outputted finally; Step S5: disinfecting and restoring the lead suit according to the adaptive control instructions, performing real-time monitoring during the disinfection process, and adaptively adjusting the disinfection parameters according to the monitoring results; Step S6: Record the disinfection of the lead suit, obtain the disinfection history record, and optimize the calculation parameters of the adaptive disinfection control model.

[0006] As a preferred technical solution of the present invention, the step of obtaining the disinfection control instruction through the adaptive disinfection control model includes: Classifying the first disinfection method according to the material parameter, wherein the first disinfection method includes recommended, available and prohibited disinfection methods; Calculate the demand index according to the demand situation, and select the second disinfection method from the recommended first disinfection method and available disinfection methods according to the demand index and the estimated time of the disinfection method; Predict the bacterial contamination situation based on the usage parameters and calculate the bacterial contamination index; adjust the parameters of all second disinfection methods based on the bacterial contamination index, calculate the fitness value of the second disinfection method after the adjustment of the parameters, normalize the fitness values ​​of all second disinfection methods, and select the second disinfection method whose fitness value after normalization is greater than the set value to output as the disinfection control instruction.

[0007] As a preferred technical solution of the present invention, the adaptive disinfection control model is an integrated model, comprising the following units: A data configuration unit, used for performing output limitation, and obtaining adaptive control instructions in an instruction database according to the disinfection method owned; A data input unit, used to receive material parameters, usage parameters and demand conditions of the lead vest; A disinfection method selection unit is used to match the first disinfection method according to the material parameters of the lead suit, calculate the demand index according to the demand situation, and match the second disinfection method according to the demand index and the estimated time of the disinfection method; A contamination prediction unit, used to predict the bacterial contamination of the lead suit according to the usage parameters, calculate the bacterial contamination index, and adjust the disinfection parameters according to the contamination index; A disinfection mode determination unit, used to calculate the fitness value of the second disinfection mode after adjusting the parameters, normalize the fitness value, and output a final disinfection control instruction; A restoration matching unit matches the restoration control instruction according to the final disinfection control instruction; The adaptive optimization module is used to automatically adjust the weight coefficients of each module through a machine learning algorithm, optimize the disinfection method based on historical disinfection records, and improve the disinfection effect and accuracy.

[0008] As a preferred technical solution of the present invention, the method for matching the second disinfection method includes: The replacement table is used to obtain the lead clothing types that can be replaced by the current type of lead clothing, and the corresponding demand situation is obtained. The demand situation is quantified into the demand value D. The step summation algorithm is used to first weight the demand value of the current lead clothing type. If the current lead clothing demand value is small, the demand value of the replacement lead clothing type is added. The calculation formula of the demand index DI is: ; Where w1 is the weight of the current lead armor type demand value, w2 is the weight of the replacement lead armor type demand value, D m is the demand value of the current lead clothing type, D si is the demand value of the i-th replacement lead armor type, w si is the weight coefficient of the i-th replacement lead armor type, and n is the number of replaceable lead armor types; where, =1, and D m Less than the main demand threshold U m When , the value of w2 is larger; Match the second disinfection method based on the demand index DI and the estimated time T t Demand score K m To carry out, the xth first disinfection method demand score K mx The calculation formula is as follows: , where θ represents the standardized parameter, TIME(DI) represents the function of disinfection time of the quantitative demand index, T tx Represents the estimated time of the xth first disinfection method; all first disinfection methods with positive demand scores are used as the second disinfection method.

[0009] As a preferred technical solution of the present invention, the method for determining the disinfection method includes: After the second disinfection method is selected, the bacterial contamination of the lead suit is predicted according to the use parameters of the lead suit, so as to calculate the bacterial contamination index BPI, the formula is as follows: , where S is the pollution level of the usage scenario, T is the usage time of the lead suit, C is the pollution degree of the contact object, and f() is the calculation function of the bacterial pollution situation; According to the calculated bacterial contamination index BPI, the disinfection parameters of the second disinfection method are adjusted, including but not limited to the disinfection intensity, disinfection time and dosage of the disinfection method, and the adjustment method is as follows: , P ai is the adjusted disinfection parameter, P bi is the initial disinfection parameter, g(BPI) is the adjustment function based on the bacterial contamination index; The fitness value of the second disinfection method after adjusting the disinfection parameters is calculated, and the second disinfection method is selected according to the fitness value, and the output is used as a disinfection control instruction to perform disinfection of the lead suit. The calculation formula of the fitness value AS is: , where NOR() represents the normalization function, α represents the type weight of the first disinfection method, represents the demand score of the second disinfection method after the parameter update, β represents the adjustment parameter of the disinfection effect evaluation value, SE x Represents the disinfection effect evaluation value of the x-th second disinfection method after the parameters are updated.

[0010] As a preferred technical solution of the present invention, the lead clothing management library includes: The lead clothing management library includes the inventory quantity and usage records of each type of lead clothing; the replacement table records the replacement relationship between different types of lead clothing. When the demand for a lead clothing type is low, other types of lead clothing can be referenced for disinfection through the replacement table; the lead clothing management library dynamically updates the usage of each lead clothing and provides real-time data support.

[0011] As a preferred technical solution of the present invention, the lead clothing demand prediction model is generated by the following steps: The use records of lead vests are counted according to time periods, including the use frequency, duration and use scenarios of lead vests; by analyzing historical data, a lead vest demand forecasting model is trained to forecast the demand for various types of lead vests in the future; the demand forecasting model is constructed based on long- and short-time neural networks; The output of the lead vest demand forecasting model is the estimated demand quantity of each type of lead vest in the future. The demand situation specifically refers to the demand situation and demand change trend of each type of lead vest.

[0012] As a preferred technical solution of the present invention, the real-time monitoring and control of the disinfection process includes the following steps: During the lead suit disinfection process, data is obtained through sensors, the disinfection status of the lead suit is monitored in real time, and the parameters of the disinfection process are dynamically adjusted. The sensor data include disinfection time, disinfection intensity, disinfection environment temperature and humidity, and disinfectant concentration; the disinfection process parameters include but are not limited to ultraviolet intensity, ozone concentration, disinfection dosage, temperature, humidity, and air circulation speed.

[0013] As a preferred technical solution of the present invention, the content of the optimized adaptive disinfection control model includes: The optimization model adopts a machine learning algorithm to optimize the weight coefficient of the adaptive disinfection control model according to the historical records of lead clothing disinfection and the evaluation value of the disinfection effect; the optimization method includes but is not limited to reinforcement learning algorithms, deep learning algorithms and other algorithms.

[0014] The present invention has the following advantages: The present invention matches the first batch of recommended disinfection methods according to the material parameters of the lead clothing through an adaptive disinfection control model, calculates the demand index and the bacterial contamination index, dynamically selects the optimal second batch of disinfection methods from the recommended disinfection methods, and uses real-time monitoring data to adjust the disinfection parameters to ensure the efficiency, accuracy and dynamic controllability of the disinfection process; according to the demand priority and contamination degree of different types of lead clothing, the most suitable disinfection plan is intelligently matched to avoid resource waste or insufficient disinfection caused by fixed disinfection modes, and meet diverse actual needs.

[0015] The present invention optimizes the resource allocation strategy through the demand index and the estimated time of the disinfection method in combination with the adaptive control model to improve the execution efficiency of the disinfection method; by adjusting the disinfection parameters such as intensity, time, dosage, etc., the disinfection effect is improved to ensure that the bacterial contamination index meets the set standards.

[0016] The present invention classifies disinfection methods through an adaptive disinfection control model, including recommended, available and prohibited disinfection methods, to avoid selecting disinfection schemes that may damage the material of the lead suit, and dries the disinfected lead suit and removes residual disinfectant through recovery control instructions to ensure that the lead suit is restored to a state ready for use and extend its service life.

[0017] The present invention records historical disinfection data, and the adaptive control model uses a machine learning algorithm to dynamically adjust the model weight parameters, continuously optimize the disinfection plan, improve the disinfection efficiency and accuracy in long-term use, and enhance the intelligence level of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flowchart of an adaptive control method for lead clothing disinfection adopted in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable persons skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0020] Example 1, an adaptive control method for lead clothing disinfection, see Figure 1 As shown, the following steps are included: Step S1: construct a lead clothing management library containing all digital samples of lead clothing; classify the digital samples of lead clothing into types according to the type parameters of lead clothing in the lead clothing management library, and count the number of lead clothing; the type parameters include style, protection and portability, wherein the style is represented by letters and numbers, and the protection and portability are represented by grades; construct a replacement table for the lead clothing type, and the replacement table serves as a reference for the replacement of different types of lead clothing; The lead clothing management library includes the inventory quantity and usage records of each type of lead clothing; the replacement table records the replacement relationship between different types of lead clothing to ensure that when the current demand for lead clothing is low, other types of lead clothing can be referenced through the replacement table for disinfection to optimize resource allocation; the replacement relationship is obtained through pre-setting, and the replacement reference complies with the following rules: lead clothing with a high protection level replaces lead clothing with a low protection level, and lead clothing with high portability replaces lead clothing with low portability; For example: when the demand for type A1 lead clothing is low, it can be known from the replacement table that type A1 lead clothing can replace type B1 lead clothing and type B2 lead clothing for use. At this time, the demand for type B1 and B2 lead clothing is obtained and used as a reference to guide the selection of lead clothing disinfection methods. If the demand for type B1 and type B2 lead clothing is high, the demand index for type A1 lead clothing is calculated to be high, and a shorter disinfection method needs to be selected to disinfect type A1 lead clothing; to ensure that when the inventory of type B1 lead clothing is zero, the inventory quantity of replacement type A1 lead clothing can be replenished in time.

[0021] The lead suit management library dynamically updates the usage of each lead suit and provides real-time data support.

[0022] Step S2: Counting the usage records of lead vests by time, training a lead vest demand prediction model based on the usage records of lead vests, obtaining the lead vest inventory based on the lead vest management database, and inputting the lead vest inventory into the lead vest demand prediction model to obtain the demand for lead vests in the current period, wherein the demand is specifically the demand for each type of lead vest; The lead clothing demand forecasting model is generated by the following steps: The use records of lead vests are counted by time period, including the frequency, duration and usage scenarios of lead vests; by analyzing historical data, a lead vest demand forecasting model is trained, which can predict the demand for various types of lead vests in the future; the model training is based on long- and short-term neural networks, taking into account multiple factors such as the inventory status, usage scenarios, and frequency of use of lead vests, and dynamically predicts the demand for lead vests in the future period; The output of the lead vest demand forecasting model is the estimated demand quantity of each type of lead vest in the future. The demand situation specifically refers to the demand situation and demand change trend of each type of lead vest.

[0023] Step S3: Obtain the lead suit label by manual input or image scanning, obtain the lead suit digital sample in the lead suit management library through the lead suit label, and extract the material parameters of the lead suit from the lead suit digital sample; obtain the use record of the lead suit, and extract the use parameters of the lead suit through the use record, wherein the use parameters include the use scene, the use duration and the contact object information; Step S4: inputting the material parameters, usage parameters and demand conditions of the lead suit into the adaptive disinfection control model for calculation to obtain an adaptive control instruction, wherein the adaptive control instruction includes a disinfection control instruction and a recovery control instruction; the disinfection control instruction is used to control the disinfection of the lead suit, and the disinfection method corresponding to the disinfection control instruction includes but is not limited to wiping disinfection, ultraviolet disinfection, ozone disinfection, hydrogen peroxide disinfection and a combination of the above disinfection methods; the adaptive disinfection control model outputs and limits the disinfection control instruction according to the disinfection method before use; the recovery control instruction is used to control the recovery of the disinfected lead suit to restore the lead suit to a state to be used, and the recovery operation includes drying and removing residual disinfectant, and the recovery control instruction is obtained based on the matching of the disinfection control instruction outputted finally; The adaptive disinfection control model divides the first disinfection method according to the material parameters, and the first disinfection method is divided into recommended, available and prohibited disinfection methods; the demand index is calculated according to the demand situation, and the second disinfection method is selected from the recommended and available disinfection methods of the first disinfection method through the demand index and the estimated time of the disinfection method; the bacterial contamination situation is predicted according to the usage parameters, and the bacterial contamination index is calculated; the parameters of all the second disinfection methods are adjusted according to the bacterial contamination index, and the fitness value of the second disinfection method after the adjustment of the parameters is calculated, the fitness values ​​of all the second disinfection methods are normalized, and the second disinfection method whose fitness value after normalization is greater than the set value is selected and output as the disinfection control instruction; The adaptive disinfection control model is an integrated model, comprising the following units: A data configuration unit, used for performing output limitation, and obtaining adaptive control instructions in an instruction database according to the disinfection method owned; A data input unit, used to receive material parameters, usage parameters and demand conditions of the lead vest; A disinfection method selection unit is used to match the first disinfection method according to the material parameters of the lead suit, calculate the demand index according to the demand situation, and match the second disinfection method according to the demand index and the estimated time of the disinfection method; A contamination prediction unit, used to predict the bacterial contamination of the lead suit according to the usage parameters, calculate the bacterial contamination index, and adjust the disinfection parameters according to the contamination index; A disinfection mode determination unit, used to calculate the fitness value of the second disinfection mode after adjusting the parameters, normalize the fitness value, and output a final disinfection control instruction; A restoration matching unit matches the restoration control instruction according to the final disinfection control instruction; The adaptive optimization module is used to automatically adjust the weight coefficients of each module through a machine learning algorithm, optimize the disinfection method based on historical disinfection records, and improve the disinfection effect and accuracy.

[0024] The method for matching the second disinfection method includes: The replacement table is used to obtain the lead clothing types that can be replaced by the current type of lead clothing, and the corresponding demand situation is obtained. The demand situation is quantified into the demand value D. The step summation algorithm is used to first weight the demand value of the current lead clothing type. If the current lead clothing demand value is small, the demand value of the replacement lead clothing type is added. The calculation formula of the demand index DI is: ; Where w1 is the weight of the current lead armor type demand value, w2 is the weight of the replacement lead armor type demand value, D m is the demand value of the current lead clothing type, D si is the demand value of the i-th replacement lead armor type, w si is the weight coefficient of the i-th replacement lead armor type, and n is the number of replaceable lead armor types; where, =1, and D m Less than the main demand threshold U m When , the value of w2 is larger; Match the second disinfection method based on the demand index DI and the estimated time T t Demand score K m To carry out, the xth first disinfection method demand score K mx The calculation formula is as follows: , where θ represents the standardized parameter, TIME(DI) represents the function of disinfection time of the quantitative demand index, T tx Represents the estimated time of the xth first disinfection method; all first disinfection methods with positive demand scores are used as the second disinfection method.

[0025] The method for determining the disinfection method includes: After the second disinfection method is selected, the bacterial contamination of the lead suit is predicted according to the use parameters of the lead suit, so as to calculate the bacterial contamination index BPI, the formula is as follows: , where S is the pollution level of the usage scenario, T is the usage time of the lead suit, C is the pollution degree of the contact object, and f() is the calculation function of the bacterial pollution situation; According to the calculated bacterial contamination index BPI, the disinfection parameters of the second disinfection method are adjusted, including but not limited to the disinfection intensity, disinfection time and dosage of the disinfection method, and the adjustment method is as follows: , P ai is the adjusted disinfection parameter, P bi is the initial disinfection parameter, g(BPI) is the adjustment function based on the bacterial contamination index; The fitness value of the second disinfection method after adjusting the disinfection parameters is calculated, and the second disinfection method is selected according to the fitness value, and the output is used as a disinfection control instruction to perform disinfection of the lead suit. The calculation formula of the fitness value AS is: , where NOR() represents the normalization function, α represents the type weight of the first disinfection method, represents the demand score of the second disinfection method after the parameter update, β represents the adjustment parameter of the disinfection effect evaluation value, SE x Represents the disinfection effect evaluation value of the x-th second disinfection method after the parameters are updated.

[0026] Step S5: disinfecting and restoring the lead suit according to the adaptive control instructions, performing real-time monitoring during the disinfection process, and adaptively adjusting the disinfection parameters according to the monitoring results to ensure the dynamic controllability of the disinfection process; During the disinfection process of the lead suit, the disinfection status of the lead suit is monitored in real time, including the disinfection time, disinfection intensity, disinfection environment temperature and humidity, and other disinfectant concentrations; during the monitoring process, data is obtained through sensors, and the parameters of the disinfection process are dynamically adjusted to ensure that the disinfection process meets the set standards; Specifically, based on real-time sensor data, including but not limited to temperature, humidity, air circulation speed and disinfectant concentration, the ultraviolet intensity, ozone concentration and disinfection dosage are adjusted; if real-time monitoring finds that certain disinfection parameters do not meet the set standards, an alarm will be issued and the disinfection parameters will be automatically adjusted to ensure the disinfection effect.

[0027] Step S6: Record the disinfection of the lead suit, obtain the disinfection history record, and optimize the calculation parameters of the adaptive disinfection control model.

[0028] The optimization model adopts a machine learning algorithm to continuously optimize the weight coefficient of the adaptive disinfection control model based on the historical records of lead clothing disinfection and the evaluation value of the disinfection effect; specific optimization methods include but are not limited to reinforcement learning algorithms, deep learning algorithms and other algorithms. The optimization model continuously updates its parameters based on past disinfection records and real-time monitoring data, so that the disinfection control instructions become gradually more accurate during long-term use.

[0029] Embodiment 2, the lead suit adaptive disinfection process is achieved by the following steps: 1. Construction of the lead clothing management database. Enter the hospital's existing lead clothing information into the lead clothing management database, including material, protection level, portability and inventory information.

[0030] For example: Style parameters: Model A1 (heavy lead clothing, protection level 5, lightness level 2), inventory quantity 20 pieces. Material parameters: Lead rubber composite material, recommended disinfection method is ultraviolet + ozone, prohibited disinfection method is hydrogen peroxide.

[0031] 2. Training of demand forecasting model and demand calculation: Based on the usage records of lead clothing in the past 6 months, the long short-term memory neural network (LSTM) model is used for training to predict the demand for various types of lead clothing in the next week: In the current period, the demand index of A1 type lead clothing is 0.8 (the main demand threshold is 0.6), and the demand index of replacement lead clothing type B1 (light lead clothing, protection level 3) is 0.4.

[0032] Use the step summation algorithm and weight to calculate the comprehensive demand index of A1 lead clothing: ; 3. Selection of disinfection schemes by the adaptive disinfection control model. Based on material parameters and demand index, the recommended disinfection methods include UV + ozone and wiping disinfection. Hydrogen peroxide disinfection is prohibited, combined with bacterial contamination index (BPI) prediction; Pollution scenario: used in the radiology department, pollution level is level 3; usage time: 8 hours; contact object contamination level: moderate pollution (level 2).

[0033] The bacterial contamination index was determined to be 13 through a calculation formula. Based on the BPI, the UV intensity was adjusted to 75% power, the ozone concentration was 50 ppm, and the disinfection time was set to 15 minutes.

[0034] 4. Real-time monitoring and dynamic adjustment: During the disinfection process, the temperature, humidity and ozone concentration of the disinfection environment are monitored by sensors: The real-time temperature is 23°C, the humidity is 50%, and the ozone concentration is 52ppm (exceeding the set value); When the ozone concentration is detected to be too high, it is automatically adjusted to 50ppm and an alarm is sounded. The UV intensity remains unchanged to ensure a stable disinfection effect.

[0035] 5. Restoration operation and record optimization: after disinfection is completed, start the restoration control command: set the drying time to 10 minutes; use the fan to remove residual ozone on the surface.

[0036] After the disinfection is completed, the disinfection parameters, usage records and adjustment data are stored in the historical record library for further optimization of the parameters of the adaptive disinfection control model.

[0037] Example 3, scenario application of rapid disinfection of light lead clothing; For model B1 lightweight lead clothing (protection level 3, lightness level 5): the recommended disinfection method for the material is ultraviolet disinfection alone; the current demand index is 0.5, which is lower than the main demand threshold; the bacterial contamination index is 7 (usage time 4 hours, pollution scene level 2, contact objects are slightly contaminated).

[0038] According to the demand index and BPI, ultraviolet disinfection was selected, the intensity was set to 50% power, and the disinfection time was 10 minutes. During the monitoring process, the ultraviolet intensity was detected to be low (45% power), and it was adjusted to the set value in real time to ensure the disinfection effect. After disinfection, it was directly restored to the state for use without the need for additional removal of residual disinfectant.

[0039] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention. Parts not described in detail in this specification belong to the prior art known to those skilled in the art.

Claims

1. An adaptive control method for lead clothing disinfection, characterized in that: The following steps are involved: Step S1: construct a lead clothing management library containing all digital samples of lead clothing; classify the digital samples of lead clothing into types according to the type parameters of lead clothing in the lead clothing management library, and count the number of lead clothing; the type parameters include style, protection and portability, wherein the style is represented by letters and numbers, and the protection and portability are represented by grades; construct a replacement table for the lead clothing type, and the replacement table serves as a reference for the replacement of different types of lead clothing; Step S2: Counting the usage records of lead vests by time, training a lead vest demand prediction model based on the usage records of lead vests, obtaining the lead vest inventory based on the lead vest management database, and inputting the lead vest inventory into the lead vest demand prediction model to obtain the demand for lead vests in the current period, wherein the demand is specifically the demand for each type of lead vest; Step S3: Obtain the lead suit label by manual input or image scanning, obtain the lead suit digital sample in the lead suit management library through the lead suit label, and extract the material parameters of the lead suit from the lead suit digital sample; obtain the use record of the lead suit, and extract the use parameters of the lead suit through the use record, wherein the use parameters include the use scene, the use duration and the contact object information; Step S4: inputting the material parameters, usage parameters and demand conditions of the lead suit into the adaptive disinfection control model for calculation to obtain an adaptive control instruction, wherein the adaptive control instruction includes a disinfection control instruction and a recovery control instruction; the disinfection control instruction is used to control the disinfection of the lead suit; the adaptive disinfection control model outputs and limits the disinfection control instruction according to the available disinfection method before use; the recovery control instruction is used to control the recovery of the disinfected lead suit to restore the lead suit to a state to be used, the recovery operation includes drying and removing residual disinfectant, and the recovery control instruction is obtained based on the matching of the disinfection control instruction outputted finally; Step S5: disinfecting and restoring the lead suit according to the adaptive control instructions, performing real-time monitoring during the disinfection process, and adaptively adjusting the disinfection parameters according to the monitoring results; Step S6: Record the disinfection of the lead suit to obtain a disinfection history record, which is used to optimize the calculation parameters of the adaptive disinfection control model.

2. The adaptive control method for lead clothing disinfection according to claim 1, characterized in that: The steps of obtaining disinfection control instructions through the adaptive disinfection control model include: Classifying the first disinfection method according to the material parameter, wherein the first disinfection method includes recommended, available and prohibited disinfection methods; Calculate the demand index according to the demand situation, and select the second disinfection method from the recommended first disinfection method and available disinfection methods according to the demand index and the estimated time of the disinfection method; Predict the bacterial contamination situation based on the usage parameters and calculate the bacterial contamination index; adjust the parameters of all second disinfection methods based on the bacterial contamination index, calculate the fitness value of the second disinfection method after the adjustment of the parameters, normalize the fitness values ​​of all second disinfection methods, and select the second disinfection method whose fitness value after normalization is greater than the set value to output as the disinfection control instruction.

3. The adaptive control method for lead clothing disinfection according to claim 1, characterized in that: The adaptive disinfection control model is an integrated model, comprising the following units: A data configuration unit, used for performing output limitation, and obtaining adaptive control instructions in an instruction database according to the disinfection method owned; A data input unit, used to receive material parameters, usage parameters and demand conditions of the lead vest; A disinfection method selection unit is used to match the first disinfection method according to the material parameters of the lead suit, calculate the demand index according to the demand situation, and match the second disinfection method according to the demand index and the estimated time of the disinfection method; A contamination prediction unit, used to predict the bacterial contamination of the lead suit according to the usage parameters, calculate the bacterial contamination index, and adjust the disinfection parameters according to the contamination index; A disinfection mode determination unit, used to calculate the fitness value of the second disinfection mode after adjusting the parameters, normalize the fitness value, and output a final disinfection control instruction; A restoration matching unit matches the restoration control instruction according to the final disinfection control instruction; The adaptive optimization module is used to automatically adjust the weight coefficients of each module through a machine learning algorithm, optimize the disinfection method based on historical disinfection records, and improve the disinfection effect and accuracy.

4. An adaptive control method for lead clothing disinfection according to claim 3, characterized in that: The method for matching the second disinfection method includes: The replacement table is used to obtain the lead clothing types that can be replaced by the current type of lead clothing, and the corresponding demand situation is obtained. The demand situation is quantified into the demand value D. The step summation algorithm is used to first weight the demand value of the current lead clothing type. If the current lead clothing demand value is small, the demand value of the replacement lead clothing type is added. The calculation formula of the demand index DI is: ； Where w1 is the weight of the current lead armor type demand value, w2 is the weight of the replacement lead armor type demand value, D m is the demand value of the current lead clothing type, D si is the demand value of the i-th replacement lead armor type, w si is the weight coefficient of the i-th replacement lead armor type, and n is the number of replaceable lead armor types; where, =1, and D m Less than the main demand threshold U m When , the value of w2 is larger; Match the second disinfection method based on the demand index DI and the estimated time T t Demand score K m To carry out, the xth first disinfection method demand score K mx The calculation formula is as follows: , where θ represents the standardized parameter, TIME(DI) represents the function of disinfection time of the quantitative demand index, T tx Represents the estimated time of the xth first disinfection method; all first disinfection methods with positive demand scores are used as the second disinfection method.

5. An adaptive control method for lead clothing disinfection according to claim 3, characterized in that: The method for determining the disinfection method includes: After the second disinfection method is selected, the bacterial contamination of the lead suit is predicted according to the use parameters of the lead suit, so as to calculate the bacterial contamination index BPI, the formula is as follows: , where S is the pollution level of the usage scenario, T is the usage time of the lead suit, C is the pollution degree of the contact object, and f() is the calculation function of the bacterial pollution situation; According to the calculated bacterial contamination index BPI, the disinfection parameters of the second disinfection method are adjusted, including but not limited to the disinfection intensity, disinfection time and dosage of the disinfection method, and the adjustment method is as follows: , P ai is the adjusted disinfection parameter, P bi is the initial disinfection parameter, g(BPI) is the adjustment function based on the bacterial contamination index; The fitness value of the second disinfection method after adjusting the disinfection parameters is calculated, and the second disinfection method is selected according to the fitness value, and the output is used as a disinfection control instruction to perform disinfection of the lead suit. The calculation formula of the fitness value AS is: , where NOR() represents the normalization function, α represents the type weight of the first disinfection method, represents the demand score of the second disinfection method after the parameter update, β represents the adjustment parameter of the disinfection effect evaluation value, SE x Represents the disinfection effect evaluation value of the x-th second disinfection method after the parameters are updated.

6. The adaptive control method for lead clothing disinfection according to claim 1, characterized in that: The lead clothing management library includes: The lead clothing management library includes the inventory quantity and usage records of each type of lead clothing; the replacement table records the replacement relationship between different types of lead clothing. When the demand for a lead clothing type is low, other types of lead clothing can be referenced for disinfection through the replacement table; the lead clothing management library dynamically updates the usage of each lead clothing and provides real-time data support.

7. The adaptive control method for lead clothing disinfection according to claim 1, characterized in that: The lead clothing demand forecasting model is generated by the following steps: The use records of lead vests are counted according to time periods, including the use frequency, duration and use scenarios of lead vests; by analyzing historical data, a lead vest demand forecasting model is trained to forecast the demand for various types of lead vests in the future; the demand forecasting model is constructed based on long- and short-time neural networks; The output of the lead vest demand forecasting model is the estimated demand quantity of each type of lead vest in the future. The demand situation specifically refers to the demand situation and demand change trend of each type of lead vest.

8. The adaptive control method for lead clothing disinfection according to claim 1, characterized in that: The real-time monitoring and control of the disinfection process includes the following steps: During the lead suit disinfection process, data is obtained through sensors, the disinfection status of the lead suit is monitored in real time, and the parameters of the disinfection process are dynamically adjusted. The sensor data include disinfection time, disinfection intensity, disinfection environment temperature and humidity, and disinfectant concentration; the disinfection process parameters include but are not limited to ultraviolet intensity, ozone concentration, disinfection dosage, temperature, humidity, and air circulation speed.

9. The adaptive control method for lead clothing disinfection according to claim 1, characterized in that: The content of the optimized adaptive disinfection control model includes: The optimization model adopts a machine learning algorithm to optimize the weight coefficient of the adaptive disinfection control model according to the historical records of lead clothing disinfection and the evaluation value of the disinfection effect; the optimization method includes but is not limited to reinforcement learning algorithms, deep learning algorithms and other algorithms.

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