An intelligent management and control system for high-throughput screening equipment for small nucleic acid drugs

Abstract

The present invention discloses an intelligent management and control system for high-throughput screening equipment for small nucleic acid drugs, comprising: an equipment information collection module for real-time collection of operating status data of the high-throughput screening equipment; an equipment environment collection module for real-time collection of physical parameters of the microenvironment in which the equipment is located; a user collection module for collecting operator identity and operating behavior data; and a data processing module, comprising: an equipment health analysis unit for calculating the equipment health index H based on the operating status data and generating equipment status management and control information including the calculated equipment health index H and maintenance recommendations. The present invention can integrate equipment operating status, microenvironmental parameters, and personnel operating behavior data to achieve comprehensive risk assessment, generate control instructions in real time through quantitative models, improve the robustness of the equipment in dealing with complex scenarios, train decision models based on historical data, identify potential risks in advance, and trigger joint optimization solutions to ensure the efficiency and accuracy of small nucleic acid drug screening.

Description

Technical Field

[0001] The present invention relates to the field of management and control systems, and in particular to an intelligent management and control system for a high-throughput screening device for small nucleic acid drugs. Background Art

[0002] The development of small nucleic acid drugs relies on high-throughput screening technology, which rapidly identifies effective drug targets by processing massive amounts of samples in parallel. This type of screening equipment must meet the following core requirements:

[0003] High-precision operating environment: Physical parameters such as temperature, humidity, and liquid flow pressure during equipment operation directly affect the activity and reaction specificity of nucleic acid molecules. Minor fluctuations may lead to deviations in screening results.

[0004] Complex operation process: The screening process involves multiple steps such as reagent preparation, sample addition, temperature control reaction, etc., which requires extremely high standardization of personnel operation;

[0005] Equipment stability requirements: Long-term high-throughput operation requires ensuring the reliability of key components (such as pipetting pumps and temperature control modules) to avoid experimental interruptions due to equipment failure.

[0006] The management and control of traditional high-throughput screening equipment has the following limitations:

[0007] Insufficient single-dimensional monitoring: Only equipment operating status or environmental parameters can be monitored independently, lacking multi-source data fusion analysis (such as the coordinated assessment of equipment health, environmental adaptability, and operational compliance);

[0008] Passive response mode: Usually intervenes after a fault occurs and cannot reduce risks through early warning;

[0009] Extensive environmental and operational management: poor adaptability to microenvironmental fluctuations, and difficulty in quantifying the impact of human operations on experimental results, resulting in low repeatability of screening data. Therefore, an intelligent management and control system for high-throughput screening equipment for small nucleic acid drugs is proposed. Summary of the Invention

[0010] The present invention solves the problems existing in the prior art through the following technical solutions, which include:

[0011] Equipment information collection module, used to collect the operating status data of high-throughput screening equipment in real time;

[0012] The device environment acquisition module is used to collect the physical parameters of the device's microenvironment in real time;

[0013] Use the personnel collection module to collect operator identity and operation behavior data;

[0014] Data processing module, including:

[0015] Equipment health analysis unit: Calculates the equipment health index H based on operating status data and generates equipment status control information including the calculated equipment health index H and maintenance recommendations;

[0016] Environmental adaptation assessment unit: compares physical parameters with preset ideal environmental values ​​to generate environmental deviation E, and generates environmental adaptation control information including environmental deviation E and adjustment plan;

[0017] Personnel Operation Compliance Unit: Generates an operation compliance score U by comparing operation behavior data with preset standard operation procedures, and generates personnel operation control information including the operation compliance score U and abnormal records;

[0018] Dynamic feedback control module, including:

[0019] Multi-source decision fusion submodule: input H, E and U into the fusion model to calculate the comprehensive risk level;

[0020] Equipment control instruction generation submodule: generates control instructions based on the comprehensive risk level;

[0021] The information sending module sends the environmental adaptation control information and personnel operation control information to the preset receiving terminal.

[0022] Furthermore, the data processing module includes:

[0023] The equipment health analysis unit calculates the equipment health index H based on the operating status data. The specific process is as follows:

[0024] ;

[0025] In the formula, S actual S is the operational stability score calculated in real time based on equipment vibration, temperature drift, and fluid pressure data. max is the preset theoretical maximum stability score, T remain is the remaining life of key components calculated based on historical equipment data, T total is the design life of key components, α and β are preset weight coefficients;

[0026] The device status control information includes device health index and maintenance recommendations.

[0027] Furthermore, the data processing module further includes:

[0028] Environmental adaptation evaluation unit compares physical parameters with preset environmental ideal values ​​P i_ideal Compare and calculate the environmental deviation E. The specific process is:

[0029] ;

[0030] Where Pi is the measured value of the i-th physical parameter, and wi is the preset parameter weight;

[0031] The environmental adaptation control information includes environmental deviation and environmental adjustment plan.

[0032] Furthermore, the personnel operation compliance unit generates an operation compliance score U by comparing the operation behavior data with the preset standard operation process. The specific process is as follows:

[0033] ;

[0034] where N correct N is the number of steps in accordance with the standard operating procedure. total is the total number of operation steps;

[0035] The personnel operation control information includes operation compliance scores and abnormal operation records.

[0036] Furthermore, the multi-source decision fusion unit inputs the equipment health index H, environmental deviation E, and operation compliance score U into the dynamic decision model to calculate the comprehensive risk level:

[0037] ;

[0038] Among them, k1, k2 and k3 are the preset risk weight coefficients;

[0039] When the comprehensive risk level is greater than the preset threshold R threshold When the device control instruction generation submodule executes:

[0040] Generate equipment speed reduction instruction;

[0041] Trigger the joint optimization solution generation module to output equipment maintenance, environmental adjustment, and personnel training measures.

[0042] Furthermore, the dynamic feedback control module further includes an adaptive parameter optimization submodule;

[0043] The adaptive parameter optimization submodule is based on the equipment health index H and the initial temperature control accuracy ΔT0 and maximum pipetting speed V of the high-throughput screening equipment. max , dynamically adjust the operating parameters, the specific process is:

[0044] ;

[0045] Where λ is the temperature control accuracy attenuation coefficient, γ is the pipetting speed attenuation coefficient, is the initial temperature control accuracy parameter of the equipment, The maximum pipetting speed allowed by the device.

[0046] Furthermore, when the environmental deviation E exceeds the safety threshold, the parameter adaptive optimization unit executes:

[0047] Override the speed adjustment formula and force V=V safe , V safe For safe speed;

[0048] Improve temperature control accuracy to .

[0049] Furthermore, the information sending module is configured to send information when the comprehensive risk level reaches a preset high-risk threshold R high hour:

[0050] Send equipment health index H and maintenance suggestions to the equipment maintenance terminal;

[0051] Send the environmental deviation E and adjustment plan to the environmental monitoring terminal;

[0052] Send the operation compliance score U and training plan to the personnel management terminal.

[0053] Furthermore, the information sending module sorts the control information according to the comprehensive risk level;

[0054] The fusion model trains weight coefficients k1, k2, k3 through historical fault data, satisfying k1+k2+k3=1 and k1>k2>k3.

[0055] Compared with the existing technology, the present invention has the following advantages: the intelligent management and control system of the small nucleic acid drug high-throughput screening equipment calculates the health index by collecting operating status data, discovers potential equipment failures in advance, generates maintenance suggestions, reduces the risk of equipment downtime, and extends the service life. It monitors the physical parameters of the microenvironment in real time, generates deviations and adjustment plans by comparing them with ideal values, ensures the stability of the equipment operating environment, and improves the accuracy and repeatability of the screening experiment. By comparing operating behaviors with standard processes, compliance scores and abnormal records are generated, operator behavior is standardized, and the impact of human errors on screening results is reduced. It integrates equipment health, environmental deviation and operating compliance data, calculates the comprehensive risk level and generates control instructions, realizes active response to system risks, and ensures safe operation of equipment. It dynamically adjusts temperature control accuracy and pipetting speed according to equipment health status and environmental risks, optimizes equipment performance while ensuring screening efficiency, and improves the stability of high-throughput screening. It sorts control information by risk level and sends it to the corresponding terminal to achieve rapid positioning and response of faults and improve management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0057] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process. However, the protection scope of the present invention is not limited to the following embodiment.

[0058] like Figure 1 As shown, this embodiment provides a technical solution: an intelligent management and control system for a high-throughput screening device for small nucleic acid drugs, comprising:

[0059] Equipment information collection module, used to collect the operating status data of high-throughput screening equipment in real time;

[0060] The device environment acquisition module is used to collect the physical parameters of the device's microenvironment in real time;

[0061] Use the personnel collection module to collect operator identity and operation behavior data;

[0062] Data processing module, including:

[0063] Equipment health analysis unit: Calculates the equipment health index H based on operating status data and generates equipment status control information including the calculated equipment health index H and maintenance recommendations;

[0064] Environmental adaptation assessment unit: compares physical parameters with preset ideal environmental values ​​to generate environmental deviation E, and generates environmental adaptation control information including environmental deviation E and adjustment plan;

[0065] Personnel Operation Compliance Unit: Generates an operation compliance score U by comparing operation behavior data with preset standard operation procedures, and generates personnel operation control information including the operation compliance score U and abnormal records;

[0066] Dynamic feedback control module, including:

[0067] Multi-source decision fusion submodule: input H, E and U into the fusion model to calculate the comprehensive risk level;

[0068] Equipment control instruction generation submodule: generates control instructions based on the comprehensive risk level;

[0069] The information sending module sends the environmental adaptation control information and personnel operation control information to the preset receiving terminal.

[0070] The data processing module includes:

[0071] The equipment health analysis unit calculates the equipment health index H based on the operating status data. The specific process is as follows:

[0072] ;

[0073] In the formula, S actualS is the operational stability score calculated in real time based on equipment vibration, temperature drift, and fluid pressure data. max is the preset theoretical maximum stability score, T remain is the remaining life of key components calculated based on historical equipment data, T total is the design life of key components, α and β are preset weight coefficients;

[0074] The equipment status control information includes equipment health index and maintenance suggestions;

[0075] By integrating operational stability and remaining component life, the one-sidedness of single-dimensional evaluation is avoided and the true health status of the equipment is more comprehensively reflected.

[0076] The health index H is calculated in real time. When equipment is operating abnormally or components are aging, the H value drops and triggers maintenance recommendations, enabling preventive maintenance and reducing the risk of sudden downtime.

[0077] The weight coefficients α and β can be used to flexibly adjust the priority of stability and lifespan. For example, high-precision equipment focuses on stability, while high-loss equipment focuses on lifespan, adapting to the maintenance needs of different equipment.

[0078] For example, when a small nucleic acid drug screening device is running, the liquid flow pressure fluctuation leads to the operation stability score S actual From the theoretical maximum S max The remaining life of key components (such as pipetting pumps) is reduced from 90% to 70%. remain From the design life T total The 50% is reduced to 30%, with the preset weights α=0.6 and β=0.4;

[0079] ;

[0080] If the health index (H) is 0.54, which is lower than the preset threshold (e.g., 0.7), the system generates a maintenance advisory: abnormal flow pressure, insufficient remaining life for the pipette pump, and a recommendation to check the tubing seal and schedule a pump replacement. This proactive intervention prevents flow errors or pump failures caused by abnormal pressure, ensuring the continuity of drug screening experiments and data accuracy.

[0081] The data processing module also includes:

[0082] Environmental adaptation evaluation unit, physical parameters and preset environmental ideal values ​​P i_ideal Compare and calculate the environmental deviation E. The specific process is:

[0083] ;

[0084] Where Pi is the measured value of the i-th physical parameter, and wi is the preset parameter weight;

[0085] The environmental adaptation control information includes environmental deviation and environmental adjustment plan;

[0086] By calculating the environmental deviation E through weighted summation, the deviation degree of multi-dimensional physical parameters such as temperature, humidity, and air pressure is converted into quantifiable values, accurately locating the source of environmental risks. If a parameter has a high weight, it will have a greater impact on the system, facilitating targeted adjustments.

[0087] Environmental parameters are monitored in real time and compared with ideal values. When E exceeds the threshold, adjustment plans are automatically triggered, such as starting temperature control equipment and humidification / dehumidification, to prevent environmental fluctuations from interfering with equipment accuracy and experimental results.

[0088] By presetting parameter weights wi, for example, if nucleic acid screening is highly sensitive to temperature, the temperature parameter is given a higher weight, and the priority of different environmental factors is flexibly adjusted to meet the precise environmental control needs of diverse experimental scenarios.

[0089] For example, a small nucleic acid drug screening experiment requires the microenvironment temperature to be maintained at 25±0.5℃, and the ideal value P i_ideal =25℃, humidity 40±5%, P i_ideal =40%, preset temperature weight w1=0.6, humidity weight w2=0.4. The actual measured temperature during operation is 26.5℃, P1=26.5, humidity is 30%, P2=30;

[0090] Temperature deviation: ;

[0091] Humidity deviation: ;

[0092] Environmental deviation: ;

[0093] System Response:

[0094] E=0.136 exceeds the preset threshold, and the system generates an environmental adjustment plan:

[0095] If the temperature is 1.5°C higher and the humidity is 10% lower, it is recommended to turn on the air conditioner to cool down to 25°C and use a humidifier to 40% humidity. This real-time adjustment can prevent high temperatures from causing nucleic acid denaturation or low humidity from causing droplet evaporation, ensuring stable reaction conditions for screening experiments and improving data reliability.

[0096] The personnel operation compliance unit generates an operation compliance score U by comparing the operation behavior data with the preset standard operation process. The specific process is as follows:

[0097] ;

[0098] where N correct N is the number of steps that comply with the standard operating procedure.total is the total number of operation steps;

[0099] The personnel operation control information includes operation compliance scores and abnormal operation records;

[0100] By comparing operating behaviors with standard procedures and calculating the compliance score U, the standardization of personnel operations is converted into quantifiable values, avoiding subjective judgments, achieving standardized management of operating procedures, and reducing the interference of human operations on experimental results.

[0101] Generate abnormal operation records to locate the specific steps of operational errors in real time, such as missed steps, wrong sequence, etc., so that operators can trace the root cause of the problem, make targeted improvements, and reduce repetitive errors.

[0102] Mandatory standardized operating procedures ensure consistency in steps when different operators perform the same experiment, avoiding fluctuations in experimental results due to operational differences. This is especially suitable for small nucleic acid drug screening scenarios that require high operational precision.

[0103] For example, the standard operating procedure for a small nucleic acid drug screening experiment includes 10 steps, including reagent preparation, sample addition, temperature control reaction, etc. The operator omitted the fifth step of adding reverse transcriptase during the execution;

[0104] Calculation process:

[0105] Total number of operation steps N total =10;

[0106] The number of steps N that conform to the standard process correct =9, step 5 is omitted;

[0107] Operational compliance score: U=9 / 10×100%=90%;

[0108] Generate personnel operation control information: Operation compliance score U=90%, exception record: Step 5 of adding reverse transcriptase was not executed.

[0109] The system automatically sends a notification to the personnel management terminal: If a key reagent is omitted, the operator is advised to review step 5 of the standard process and participate in targeted operation training. Through timely reminders and records, experimental failures or data deviations caused by reagent omissions are avoided, ensuring the accuracy and reproducibility of screening results.

[0110] The multi-source decision fusion unit inputs the equipment health index H, environmental deviation E, and operation compliance score U into the dynamic decision model to calculate the comprehensive risk level:

[0111] ;

[0112] Among them, k1, k2 and k3 are the preset risk weight coefficients;

[0113] When the comprehensive risk level is greater than the preset threshold R threshold When the device control instruction generation submodule executes:

[0114] Generate equipment speed reduction instruction;

[0115] Trigger the joint optimization solution generation module to output equipment maintenance, environmental adjustment, and personnel training measures;

[0116] By integrating the equipment health index H, environmental deviation E, and operational compliance score U, a comprehensive risk level model is constructed to avoid the one-sidedness of single-dimensional assessment, achieve a comprehensive quantitative analysis of equipment operation risks, and identify potential hidden dangers in advance (such as the combined effects of equipment aging, environmental fluctuations, and operational errors).

[0117] When the comprehensive risk level exceeds the threshold, the system automatically triggers equipment slowdown and maintenance, and a joint optimization plan for the environment and personnel to achieve a graded response to risks. For example, when the risk is high, equipment parameters are adjusted, the environment is improved, and personnel are trained to improve system robustness.

[0118] The weight coefficients k1, k2, and k3 (k1>k2>k3) can be used to flexibly adjust the risk priorities of equipment health, environment, and operation (for example, k1 is given a higher weight when high equipment precision requirements are required) to adapt to the risk management needs of different screening experiments.

[0119] For example, when a small nucleic acid drug screening device is running, the device health index H = 0.6, which is low, the environmental deviation E = 0.2, which is medium, the operation compliance score U = 0.8, which is good, the preset weights k1 = 0.5, k2 = 0.3, k3 = 0.2, and the risk threshold R threshold =0.4.

[0120] Calculation process: comprehensive risk level

[0121] Because 0.3 < 0.4 (not exceeding the threshold), the system does not trigger a speed reduction for now, but generates an alert: the device health status is low, and it is recommended to pay attention to changes in the H value.

[0122] Risk escalation scenario: If H=0.4, E=0.3, U=0.7, the weights remain unchanged:

[0123] ;

[0124] At this time, the device generates a speed reduction instruction to reduce the pipetting speed to 80% of the maximum speed;

[0125] Triggering a joint optimization plan: Low equipment health index (recommend inspection of key components), moderate environmental deviation (initiate temperature and humidity adjustment), and operational compliance needs improvement (distribute standard process review materials). This multi-dimensional intervention prevents screening experiment failures caused by equipment failure, environmental fluctuations, or operational oversights, ensuring continuity and data reliability in drug screening.

[0126] The dynamic feedback control module also includes an adaptive parameter optimization submodule;

[0127] The adaptive parameter optimization submodule is based on the equipment health index H and the initial temperature control accuracy ΔT0 and maximum pipetting speed V of the high-throughput screening equipment. max , dynamically adjust the operating parameters, the specific process is:

[0128] ;

[0129] Where λ is the temperature control accuracy attenuation coefficient, γ is the pipetting speed attenuation coefficient, is the initial temperature control accuracy parameter of the equipment, is the maximum pipetting speed allowed by the device;

[0130] Adaptive optimization of equipment performance and extension of life:

[0131] The temperature control accuracy and pipetting speed are dynamically adjusted through the equipment health index H. When the equipment health status declines, the H value decreases, and the operating load is automatically reduced, such as reducing the pipetting speed and relaxing the temperature control accuracy. This avoids the exacerbation of faults caused by operating with defects, and achieves a balanced optimization of equipment performance and lifespan.

[0132] When the health status is good, the H value is high, and high-precision operation is maintained, such as strict temperature control and high-speed pipetting, to ensure experimental efficiency. When the health status deteriorates, the parameters are adaptively adjusted to reduce experimental errors caused by equipment abnormalities, such as unstable liquid flow and temperature control deviation, to ensure the reliability of the screening data.

[0133] Utilizes exponential decay models and nonlinear speed adjustment to achieve smooth transition of parameter adjustments, avoid the impact of sudden speed reduction on the experimental process, and dynamically find the optimal balance between equipment health and screening efficiency;

[0134] For example, the initial temperature control accuracy of a small nucleic acid drug screening device is ΔT0 = ±0.5°C, and the maximum pipetting speed is V max =100μL / s, temperature control accuracy attenuation coefficient λ = 0.5, and pipetting speed attenuation coefficient γ = 0.3. After the device has been running for a period of time, the health index H drops from the initial 1.0 to 0.6.

[0135] Temperature control accuracy after adjustment: ;

[0136] Adjusted pipetting speed:

[0137] ;

[0138] At this time, the temperature control accuracy is improved from ±0.5℃ to ±0.37℃, because when H decreases, the formula The exponent is negative, and the smaller H is, the smaller ΔT is, that is, the accuracy is improved, and the pipetting speed is reduced from 100 μL / s to 95.2 μL / s.

[0139] This adjustment not only reduces the equipment load by reducing the speed and extending the life of key components, but also ensures the temperature sensitivity requirements of nucleic acid reactions by improving temperature control accuracy, avoiding deviations in experimental results due to deterioration in equipment health, and achieving intelligent control that prioritizes the stability of key indicators when performance degrades.

[0140] When the environmental deviation E exceeds the safety threshold, the parameter adaptive optimization unit performs:

[0141] Override the speed adjustment formula and force V=V safe , V safe For safe speed;

[0142] Improve temperature control accuracy to ;

[0143] Environmental risk emergency intervention and safety guarantee:

[0144] When the environmental deviation E exceeds the safety threshold, the normal parameter adjustment logic is forcibly overwritten and the system operates at a safe speed Vsafe and with enhanced temperature control accuracy to avoid equipment failure or experimental errors caused by drastic environmental fluctuations, such as sudden temperature changes and excessive humidity, and to achieve emergency risk prevention.

[0145] By improving temperature control accuracy, such as doubling the attenuation coefficient, the impact of environmental fluctuations on temperature-sensitive experiments such as nucleic acid amplification and enzymatic reactions can be offset. At the same time, limiting the pipetting speed can prevent changes in the physical properties of the liquid due to environmental changes, such as sample addition errors caused by viscosity and evaporation rate, thereby ensuring the reliability of experimental data.

[0146] It automatically switches to safe mode in the event of an environmental crisis, temporarily sacrificing some operating efficiency to ensure core functions, reflecting the system's adaptive fault tolerance to environmental risks. It is especially suitable for small nucleic acid drug screening scenarios that are sensitive to the environment.

[0147] For example, the microenvironment temperature of a small nucleic acid drug screening experiment is required to be maintained at 37±0.5℃, and the safety threshold is set to the environmental deviation E≥0.2. During operation, due to an air conditioning failure, the measured temperature suddenly rose to 40℃, corresponding to the ideal value of the environmental parameter P i_ideal =37℃, and E=|(40-37) / 37|=0.081. Assuming that only temperature is a parameter, the weight w1=1, which exceeds the safety threshold of 0.2.

[0148] ;

[0149] That is, the temperature control accuracy is improved from ±0.5℃ to ±0.27℃. By strengthening the temperature control to compensate for the high temperature of the environment, the temperature of the reaction system is maintained stable.

[0150] The information sending module is activated when the comprehensive risk level reaches the preset high-risk threshold R high hour:

[0151] Send equipment health index H and maintenance suggestions to the equipment maintenance terminal;

[0152] Send the environmental deviation E and adjustment plan to the environmental monitoring terminal;

[0153] Send the operation compliance score U and training plan to the personnel management terminal.

[0154] Entering the information sending module to sort the control information according to the comprehensive risk level;

[0155] The fusion model trains weight coefficients k1, k2, k3 through historical fault data, satisfying k1+k2+k3=1 and k1>k2>k3.

[0156] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0157] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0158] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. An intelligent management and control system for a high-throughput screening device for small nucleic acid drugs, characterized in that: include: Equipment information collection module, used to collect the operating status data of high-throughput screening equipment in real time; The device environment acquisition module is used to collect the physical parameters of the device's microenvironment in real time; Use the personnel collection module to collect operator identity and operation behavior data; Data processing module, including: Equipment health analysis unit: Calculates the equipment health index H based on operating status data and generates equipment status control information including the calculated equipment health index H and maintenance recommendations; Environmental adaptation assessment unit: compares physical parameters with preset ideal environmental values ​​to generate environmental deviation E, and generates environmental adaptation control information including environmental deviation E and adjustment plan; Personnel Operation Compliance Unit: Generates an operation compliance score U by comparing operation behavior data with preset standard operation procedures, and generates personnel operation control information including the operation compliance score U and abnormal records; Dynamic feedback control module, including: Multi-source decision fusion submodule: input H, E and U into the fusion model to calculate the comprehensive risk level; Equipment control instruction generation submodule: generates control instructions based on the comprehensive risk level; Information sending module, which sends environmental adaptation control information and personnel operation control information to the preset receiving terminal; The data processing module includes: The equipment health analysis unit calculates the equipment health index H based on the operating status data. The specific process is as follows: In the formula, S actual S is the operational stability score calculated in real time based on equipment vibration, temperature drift, and fluid pressure data. max is the preset theoretical maximum stability score, T remain is the remaining life of key components calculated based on historical equipment data, T total is the design life of key components, α and β are preset weight coefficients; The equipment status control information includes equipment health index and maintenance suggestions; The data processing module also includes: Environmental adaptation evaluation unit compares physical parameters with preset environmental ideal values ​​P i_ideal Compare and calculate the environmental deviation E. The specific process is: Where Pi is the measured value of the i-th physical parameter, and wi is the preset parameter weight; The environmental adaptation control information includes environmental deviation and environmental adjustment plan; The personnel operation compliance unit generates an operation compliance score U by comparing the operation behavior data with the preset standard operation process. The specific process is as follows: where N correct N is the number of steps in accordance with the standard operating procedure. total is the total number of operation steps; The personnel operation control information includes operation compliance scores and abnormal operation records.

2. The intelligent management and control system for a high-throughput screening device for small nucleic acid drugs according to claim 1, characterized in that: The multi-source decision fusion unit inputs the equipment health index H, environmental deviation E, and operation compliance score U into the dynamic decision model to calculate the comprehensive risk level: Comprehensive risk level = k1·(1-H)+k2·E+k3·(1-U); Among them, k1, k2 and k3 are the preset risk weight coefficients; When the comprehensive risk level is greater than the preset threshold R threshold When the device control instruction generation submodule executes: Generate equipment speed reduction instruction; Trigger the joint optimization solution generation module to output equipment maintenance, environmental adjustment, and personnel training measures.

3. The intelligent management and control system for a high-throughput screening device for small nucleic acid drugs according to claim 2, characterized in that: The dynamic feedback control module also includes an adaptive parameter optimization submodule; The adaptive parameter optimization submodule is based on the equipment health index H and the initial temperature control accuracy ΔT0 and maximum pipetting speed V of the high-throughput screening equipment. max , dynamically adjust the operating parameters, the specific process is: Where λ is the temperature control accuracy attenuation coefficient, γ is the pipetting speed attenuation coefficient, ΔT0 is the initial temperature control accuracy parameter of the device, V max The maximum pipetting speed allowed by the device.

4. The intelligent management and control system for a high-throughput screening device for small nucleic acid drugs according to claim 3, characterized in that: When the environmental deviation E exceeds the safety threshold, the parameter adaptive optimization unit performs: Override the speed adjustment formula and force V=V safe , V safe For safe speed; Improve temperature control accuracy to ΔT=ΔT0·e -2λ .

5. The intelligent management and control system for a high-throughput screening device for small nucleic acid drugs according to claim 4, characterized in that: The information sending module is activated when the comprehensive risk level reaches the preset high-risk threshold R high hour: Send equipment health index H and maintenance suggestions to the equipment maintenance terminal; Send the environmental deviation E and adjustment plan to the environmental monitoring terminal; Send the operation compliance score U and training plan to the personnel management terminal.

6. An intelligent management and control system for a high-throughput screening device for small nucleic acid drugs according to any one of claims 1 to 5, characterized in that: The information sending module sorts the control information according to the comprehensive risk level; The fusion model trains weight coefficients k1, k2, k3 through historical fault data, satisfying k1+k2+k3=1 and k1>k2>k3.

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