Quality monitoring control system for whole disinfectant use process

Abstract

The invention relates to the technical field of data acquisition, in particular to a disinfectant use whole-process quality monitoring control system, which comprises a demand calculation module, an inventory state monitoring module, an electronic tag, an effective inventory batch information screening module, a quality monitoring module and a quality control module, the proportion execution control module calculates the water inflow and the tablet number based on the effective stock batch and the theoretical demand so as to adjust the valve duration and the motor stepping frequency, and the concentration data acquisition module acquires the conductivity voltage and temperature value of the solution and calculates and outputs the actual concentration value through the least square method. According to the method, the theoretical demand quantity is calculated by obtaining disinfection data, effective inventory batches are screened in combination with electronic tags, valves and motors are accurately regulated and controlled to achieve accurate matching, data are processed through the least square method, objective high-precision concentration values are output, personal errors are eliminated, and full-process digital closed-loop management is achieved.

Description

Technical Field

[0001] This invention relates to the field of data acquisition technology, and in particular to a quality monitoring and control system for the entire process of disinfectant use. Background Technology

[0002] Data acquisition technology. Data acquisition technology generally refers to the field of technology that uses sensing devices such as sensors, radio frequency identification devices, and communication modules to automatically acquire, convert, and store the attributes, status, or environmental parameters of a target object. Its aim is to achieve the digitization and real-time monitoring of information in the physical world. In this context, the traditional disinfectant usage process quality monitoring and control system relies primarily on a combination of manual operation and paper records. Medical staff must manually fill out a paper requisition form during the requisition process and visually check the expiration date of the disinfectant on the pharmacy's regular shelves before taking it. During the preparation process, operators estimate the amount based on experience and add water and tablets to the container, then manually stir the mixture using a stirring rod. In the usage and testing phase, medical staff use chemical test strips immersed in the disinfectant solution, visually comparing the concentration range to a standard color chart, and manually record the test results and usage details in the department's logbook.

[0003] Existing technologies heavily rely on manual intervention and paper records for full-process monitoring. Medical staff rely solely on subjective experience to estimate dosages and administer medications during preparation, which can easily lead to imbalances in the ratio of water injection to tablet dosage. The method of verifying concentration by visually comparing standard color cards has low accuracy and is susceptible to human error. Furthermore, manually written records lack real-time data synchronization capabilities, making it difficult to effectively trace historical quality control data or accurately manage the expiration date of inventory. This results in large fluctuations in the concentration of disinfectant preparations and, due to the lack of an early warning mechanism, the misuse of expired medications. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and to propose a whole-process quality monitoring and control system for disinfectant use.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a quality monitoring and control system for the entire process of disinfectant use includes:

[0006] The demand calculation module obtains the disinfection area, disinfection frequency, and unit area consumption coefficient of the ward surface, processes the disinfection area, disinfection frequency, and unit area consumption coefficient to generate the theoretical disinfectant demand, and transmits it to the inventory status monitoring module.

[0007] The inventory status monitoring module reads the electronic tag based on the theoretical disinfectant demand, parses the production date and expiration threshold from the electronic tag to filter valid inventory batch information, and transmits the valid inventory batch information and the theoretical disinfectant demand to the proportioning execution control module.

[0008] The mixing control module calculates the water intake and tablet quantity based on the effective inventory batch information and the theoretical disinfectant requirement. It adjusts the water intake valve duration and motor stepping frequency according to the water intake and tablet quantity, generates a stirring completion command, and transmits it to the concentration data acquisition module.

[0009] The concentration data acquisition module acquires the solution conductivity voltage and solution temperature values ​​based on the stirring completion command, calls the least squares method to process the solution conductivity voltage and solution temperature values ​​to calculate the actual concentration value, and outputs the actual concentration value.

[0010] As a further aspect of the present invention, the theoretical disinfectant demand includes the theoretical usage per task, the cumulative quota per unit period, and the preset consumption deviation threshold; the effective inventory batch information includes the serial number of the available bottle electronic tag, the coordinates of the corresponding storage cabinet, and the batch call priority identifier; the stirring completion instruction includes a mixing status confirmation flag, a preparation process end timestamp, and a draining system activation signal; and the actual concentration value includes the chloride ion concentration reading after temperature compensation, the current detection confidence interval, and the linear regression fitting residual value.

[0011] As a further aspect of the present invention, the demand calculation module includes:

[0012] The task parameter parsing submodule obtains the disinfection area and frequency of the ward surface, performs a multiplication operation on the disinfection area and the disinfection frequency to quantify the basic workload, and calls the preset risk level database to match the corresponding unit area consumption coefficient.

[0013] The consumption simulation calculation submodule uses the unit area consumption coefficient to perform weighted calculations on the basic workload to generate the theoretical consumption of a single task, and retrieves the task records of historical periods for cumulative processing to update the cumulative quota of the unit period.

[0014] The threshold dynamic setting submodule calculates the statistical variance of the theoretical usage of the single task within a preset time window, sets a preset consumption deviation threshold that allows fluctuations based on the statistical variance, and combines these to generate the theoretical disinfectant requirement.

[0015] As a further aspect of the present invention, the inventory status monitoring module includes:

[0016] The label information decoding submodule initiates an RFID scanning procedure in response to the theoretical disinfectant demand, captures the RFID feedback signal in the area and performs demodulation processing, and extracts the production date and expiration date threshold from the demodulated data frame.

[0017] The expiration date screening and verification submodule obtains the current system time and calculates the remaining shelf life by comparing it with the production date, and then removes batches that exceed the expiration date threshold to lock the available bottle electronic label serial number.

[0018] The sorting optimization arbitration submodule performs a weighted score based on the remaining shelf life and the spatial distance to the corresponding storage cabinet coordinates, generates a batch call priority identifier based on the score results, and packages and outputs the valid inventory batch information.

[0019] As a further aspect of the present invention, the proportioning execution control module includes:

[0020] The material allocation and execution submodule analyzes the theoretical disinfectant requirement to determine the target solution concentration and total volume, and calculates the water intake and tablet quantity based on the specification parameters in the effective inventory batch information.

[0021] The hardware-driven mapping submodule maps the water inlet volume to the opening time characteristics of the solenoid valve to adjust the water inlet valve duration, and converts the number of tablets into the rotation angle pulse of the feeding mechanism to adjust the motor stepping number.

[0022] The preparation status feedback submodule monitors the load current change rate of the stirring motor in real time. When the current fluctuation value converges to the stable range, it generates a stirring completion instruction including a mixing status confirmation flag and a preparation process end timestamp, and presets the drainage system activation signal.

[0023] As a further aspect of the present invention, the concentration data acquisition module includes:

[0024] The sensor array acquisition submodule receives the stirring completion command and synchronously triggers the conductivity probe and thermistor to continuously acquire the solution conductivity voltage and solution temperature values ​​during the static stage after stirring stops.

[0025] The compensation algorithm processing submodule uses the least squares algorithm model to linearly fit the solution conductivity voltage, introduces the solution temperature value to perform thermodynamic correction on the fitting result, and calculates the chloride ion concentration reading after temperature compensation.

[0026] The quality confidence assessment submodule analyzes the dispersion of continuously collected data, calculates the linear regression fitting residual value, determines the current detection confidence interval based on the linear regression fitting residual value, and outputs the actual concentration value.

[0027] As a further aspect of the present invention, the process of calculating the theoretical usage of a single task in the consumption simulation calculation submodule includes:

[0028] The disinfection area of ​​the ward surface, the disinfection frequency, and the unit area consumption coefficient are obtained. A consumption calculation model is established in combination with the environmental evaporation loss factor to calculate the theoretical consumption of a single task.

[0029] The calculation of the theoretical usage for a single task follows the following formula:

[0030] ;

[0031] in, This represents the theoretical usage per single task. Represents the total number of functional partitions. The area of ​​surface disinfection in the representative ward is the first The specific area of ​​each functional zone Representing the Disinfection frequency for each functional area, Representing the The unit area consumption coefficient corresponding to each functional zone This represents the environmental evaporation loss factor derived from historical environmental humidity data.

[0032] As a further aspect of the present invention, the process of calculating the temperature-compensated chloride ion concentration reading in the compensation algorithm processing submodule includes:

[0033] The solution conductivity voltage and solution temperature values ​​are obtained, and the parameters are substituted into the pre-calibrated electrochemical response equation to calculate the temperature-compensated chloride ion concentration reading.

[0034] The temperature-compensated chloride ion concentration reading is calculated according to the following formula:

[0035] ;

[0036] in, This represents the chloride ion concentration reading after temperature compensation. Voltage representing solution conductivity The slope of the conductivity-concentration standard curve represents the electrical conductivity-concentration standard curve. The intercept of the conductivity-concentration standard curve represents the value of the standard curve. The temperature compensation coefficient representing chloride ions. Represents the solution temperature value. This represents the standard calibration temperature.

[0037] As a further aspect of the present invention, the process of generating the batch call priority identifier in the sorting optimization arbitration submodule includes:

[0038] Obtain the production date and the corresponding storage cabinet coordinates, calculate the remaining shelf life days of the inventory batch and the robotic arm grasping path length, and generate the batch call priority identifier using dual weight logic;

[0039] Specifically, the batches with earlier production dates are assigned a first high priority weight, and the batches whose corresponding storage cabinet coordinates are closer to the discharge port are assigned a second auxiliary weight. After comprehensive calculation, a sorted list including the batch call priority identifier is generated.

[0040] As a further aspect of the present invention, the process of adjusting the motor step count in the hardware driver mapping submodule includes:

[0041] The number of tablets and the single-step feed constant of the feeding screw mechanism are obtained, the total rotation angle required to complete the feeding is calculated, and the total rotation angle is quantized into discrete drive pulses to determine the number of motor steps.

[0042] During the feeding process, the feedback signal of the motor encoder is read in real time, and the difference between the actual number of steps and the number of motor steps is calculated. If the difference exceeds the preset safety protection zone, a compensation pulse signal is automatically generated.

[0043] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0044] In this invention, the theoretical demand is calculated by acquiring specific disinfection area and frequency data of the ward. Combined with electronic tag analysis technology, valid inventory batches are automatically screened and expired information is removed. Based on the calculated water inlet volume and tablet quantity, the duration of the water inlet valve and the number of motor steps are precisely controlled to achieve automated and precise drug solution ratio execution. The least squares method is used to process the solution conductivity and temperature data, which can output objective and high-precision actual concentration values, eliminating errors caused by human experience ratio and visual observation, and achieving full-process digital closed-loop management of disinfectants from demand calculation to final quality control. Attached Figure Description

[0045] Figure 1 This is a block diagram illustrating the principle of a quality monitoring and control system for the entire process of disinfectant use according to the present invention.

[0046] Figure 2 This is a flowchart of the operation of the requirement calculation module of this invention;

[0047] Figure 3 This is a logical diagram of the inventory status monitoring module of the present invention;

[0048] Figure 4 This is a flowchart of the process of the proportioning and control module of the present invention;

[0049] Figure 5 This is a flowchart of the concentration data acquisition module of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the software-based technical solution is described in detail below with reference to system architecture diagrams and embodiments. It should be understood that the specific embodiments described herein are only for explaining the technical solutions of this invention and do not constitute a limitation on the scope of protection.

[0051] In the description of this invention, the system architecture relationships or data processing flows indicated by terms such as "layer," "module," "interface," "data flow," "client," and "server" are all defined based on the architecture diagram or flowchart corresponding to the embodiments. This way of describing is only used to clearly illustrate the logical relationships between the elements in the technical solution, and not to limit the physical deployment form. The term "multiple" includes two or more technical units, including but not limited to multiple data nodes, processing threads, service instances, or functional components and other scalable elements. The specific number is determined according to the actual business scenario and needs to be specifically specified.

[0052] Please see Figure 1 and Figure 2 This invention provides a technical solution: a quality monitoring and control system for the entire process of disinfectant use, comprising:

[0053] The demand calculation module obtains the disinfection area, disinfection frequency, and consumption coefficient per unit area of ​​the ward surfaces, processes the disinfection area, disinfection frequency, and consumption coefficient per unit area to generate the theoretical disinfectant demand, and transmits it to the inventory status monitoring module.

[0054] The theoretical demand for disinfectant includes the theoretical usage per task, the cumulative quota per unit period, and the preset consumption deviation threshold.

[0055] The demand calculation module includes:

[0056] The task parameter parsing submodule obtains the disinfection area and frequency of the ward surfaces, performs a multiplication operation on the disinfection area and frequency of the ward surfaces to quantify the basic workload, and calls the preset risk level database to match the corresponding unit area consumption coefficient.

[0057] The consumption simulation calculation submodule uses the unit area consumption coefficient to weight the basic workload to generate the theoretical consumption of a single task, and retrieves the task records of historical periods for cumulative processing to update the cumulative quota of the unit period.

[0058] The process of calculating the theoretical usage for a single task in the consumption simulation calculation submodule includes:

[0059] Obtain the disinfection area, disinfection frequency, and consumption coefficient per unit area of ​​the ward surfaces, and establish a consumption calculation model in conjunction with the environmental evaporation loss factor to calculate the theoretical consumption for a single task.

[0060] The theoretical usage per task is calculated using the following formula:

[0061] ;

[0062] in, This represents the theoretical usage per single task. Represents the total number of functional partitions. The area of ​​surface disinfection in the representative ward is the first The specific area of ​​each functional zone Representing the Disinfection frequency for each functional area, Representing the The unit area consumption coefficient corresponding to each functional zone This represents the environmental evaporation loss factor derived from historical environmental humidity data.

[0063] The threshold dynamic setting submodule calculates the statistical variance of the theoretical usage for a single task within a preset time window, sets a preset consumption deviation threshold that allows fluctuations based on the statistical variance, and generates the theoretical disinfectant requirement.

[0064] The demand calculation module includes a task parameter parsing submodule, a consumption simulation calculation submodule, and a threshold dynamic setting submodule. The task parameter parsing submodule executes as follows: The system receives a digital instruction from the ward scheduling system, which contains the spatial identification code of the area to be disinfected. The parsing program retrieves the building floor plan database based on the spatial identification code to locate the physical boundaries within the ward. For the first functional area identified as "Intensive Care Unit," the program reads the area value from its attribute field. The corresponding disinfection frequency was set to 4 times per day; for the second functional area labeled "General Treatment Room", the area value was read. The disinfection frequency is set at twice daily. Subsequently, the submodule accesses a risk level database stored on the local server. This database stores consumption standards for different areas in key-value pairs. The program uses "Intensive Care Unit" as the index key, retrieves the corresponding risk level as "Level I," and then reads the consumption coefficient per unit area. for Using "general treatment room" as the index key, search for risk level "Level II" and retrieve the consumption coefficient per unit area. for .

[0065] The consumption simulation calculation submodule receives the above-mentioned parsed data and reads the current relative humidity data of the ward through the environmental sensor interface. If the current relative humidity reading is 35%RH, which is lower than the standard reference value of 50%RH, the program activates the environmental evaporation loss factor. The calculation logic is as follows: Assuming that for every 5 percentage point decrease in relative humidity, the loss factor increases by 0.02, the calculation yields... The value is 0.06. Subsequently, the theoretical usage for a single task executed by the submodule is... The calculation aims to weight and accumulate the area, frequency, and consumption coefficient of different functional zones, and to add the additional demand caused by environmental losses, thereby obtaining an accurate total liquid dosage. The calculation of the theoretical dosage for a single task follows the formula: ;in, This represents the theoretical usage per single task. Represents the total number of functional partitions. The area of ​​surface disinfection in the representative ward is the first The specific area of ​​each functional zone Representing the Disinfection frequency for each functional area, Representing the The unit area consumption coefficient corresponding to each functional zone This represents the environmental evaporation loss factor derived from historical ambient humidity data. Substituting the aforementioned parameters into the formula: ; Calculate the base load within the parentheses: ; Calculate the final demand: Calculation results show that the theoretical disinfectant requirement for a single task is: .

[0066] The threshold dynamic setting submodule then reads historical data on the theoretical usage of a single task from the past 7 similar shifts: The program calls the variance calculation function to process the array and obtain the statistical variance value. The calculation rule for setting the preset consumption deviation threshold is as follows: (That is, twice the standard deviation). The calculated mean of this data set is... The sample standard deviation is approximately The allowed preset consumption deviation threshold is then set to... (take approximate value) The module will ultimately determine the theoretical usage per single task. and deviation threshold Combine and package the items, then send them to the next stage.

[0067] Please see Figure 1 and Figure 3The inventory status monitoring module reads electronic tags based on the theoretical disinfectant demand, parses the production date and expiration date threshold from the electronic tags to filter valid inventory batch information, and transmits the valid inventory batch information and theoretical disinfectant demand to the mixing execution control module.

[0068] Valid inventory batch information includes the available bottle electronic tag serial number, the corresponding storage cabinet coordinates, and the batch recall priority identifier;

[0069] The inventory status monitoring module includes:

[0070] The label information decoding submodule initiates the radio frequency identification scanning program in response to the theoretical disinfectant demand, captures the radio frequency feedback signal in the area and performs demodulation processing, and extracts the production date and expiration date threshold from the demodulated data frame;

[0071] The expiration date screening and verification submodule obtains the current system time and calculates the remaining shelf life by comparing it with the production date, and removes batches that exceed the expiration date threshold to lock the available electronic label serial numbers on the bottle.

[0072] The sorting optimization arbitration submodule performs weighted scoring based on the remaining shelf life and the spatial distance to the corresponding storage cabinet coordinates, generates batch call priority identifiers based on the scoring results, and packages and outputs valid inventory batch information.

[0073] The process of generating batch call priority identifiers in the sorting optimization arbitration submodule includes:

[0074] Obtain the production date and corresponding storage cabinet coordinates, calculate the remaining shelf life days of the inventory batch and the robotic arm grasping path length, and generate a batch call priority identifier using dual weight logic;

[0075] Specifically, batches with earlier production dates are assigned the highest priority weight, and batches with corresponding storage cabinet coordinates closer to the discharge port are assigned the second auxiliary weight. After comprehensive calculation, a sorted list including batch call priority identifiers is generated.

[0076] The inventory status monitoring module includes a label information decoding submodule, an expiration date screening and verification submodule, and a sorting optimization arbitration submodule. The label information decoding submodule is in standby mode; once it receives a label information decoding submodule, it will automatically start working. Upon receiving the theoretical disinfectant demand request, an activation command is immediately sent to the UHF RFID reader. The reader transmits radio frequency signals to the smart storage cabinet within a 3-meter radius and receives the echo signals reflected from the passive electronic tags. The decoder demodulates the echo signals using Manchester encoding rules, converting the binary bit stream into hexadecimal data frames. Following the ISO / IEC 18000-6C protocol standard, the program locates the fields storing the production date (UserMemory area addresses 0x10-0x1F) and the expiration threshold (addresses 0x20-0x23) within the data frame. For example, from electronic tag A, the production date is parsed as "20251101" and the expiration threshold as "180 days"; from electronic tag B, the production date is parsed as "20251015" and the expiration threshold as "180 days".

[0077] The expiration date screening and verification submodule reads the system's real-time clock; the current time is November 27, 2025. The program performs time difference calculations for each batch: for label A, it calculates the time difference. Days, remaining shelf life is Day; For label B, calculate the time difference. Days, remaining shelf life is The system is configured with the following logic: if the remaining shelf life is greater than 0, the item is marked as "valid" and its EPC serial number is locked; if it is less than or equal to 0, it is marked as "expired" and an alarm is triggered. In this example, both batch A and batch B are determined to be valid inventory batch information.

[0078] The sorting optimization arbitration submodule performs priority scoring based on valid batches. First, it obtains the storage cabinet coordinates corresponding to each batch: Batch A is located at... Batch B is located in Set the outlet coordinates as follows: The program calculates the robotic arm's grasping path length (using Manhattan distance): Batch A distance Unit; Batch B distance Unit. A dual-weighting logic is implemented: production date weighting. (Prefer using older batches), distance weight (Prioritize using close-range data). After normalization, set the scoring formula. .in, Represents batch priority score. Represents the weight of the production date. Represents the remaining shelf life in days. Represents distance weight, This represents the length of the robotic arm's grasping path.

[0079] Calculate the score for batch A:

[0080] ;

[0081] Calculate the score for batch B:

[0082] ;

[0083] because The program determines that batch B has a higher priority, generates a batch call priority identifier containing the batch B sequence code, and packages it out as the main output object. Specific batch information is shown in Table 1.

[0084] Table 1. Inventory Batch Priority Assessment Data Table

[0085] Batch number Production date Remaining shelf life (days) Counter distance (unit) Priority rating Arbitration Result Batch_A 2025-11-01 154 4 4.62 alternatives Batch_B 2025-10-15 137 11 5.136 Preferred

[0086] As shown in Table 1, the system ultimately selects Batch_B for feeding.

[0087] Please see Figure 1 and Figure 4 The mixing control module calculates the water intake and tablet quantity based on the effective inventory batch information and the theoretical disinfectant demand. It adjusts the water intake valve duration and motor step count according to the water intake and tablet quantity, generates a stirring completion command, and transmits it to the concentration data acquisition module.

[0088] The mixing completion instruction includes a mixing status confirmation flag, a preparation process end timestamp, and a drainage system activation signal.

[0089] The proportioning execution control module includes:

[0090] The material allocation and execution submodule analyzes the theoretical disinfectant requirement to determine the target solution concentration and total volume, and calculates the water intake and tablet quantity by combining the specification parameters in the effective inventory batch information.

[0091] The hardware-driven mapping submodule maps the water inlet volume to the opening time characteristics of the solenoid valve to adjust the water inlet valve duration, and converts the tablet quantity into the rotation angle pulse of the feeding mechanism to adjust the motor stepping number.

[0092] The process of adjusting the motor step count in the hardware driver mapping submodule includes:

[0093] Obtain the tablet quantity and the single-step feed constant of the feeding screw mechanism, calculate the total rotation angle required to complete the feeding, and quantize the total rotation angle into discrete drive pulses to determine the number of motor steps;

[0094] During the feeding process, the feedback signal of the motor encoder is read in real time, and the difference between the actual number of steps and the number of motor steps is calculated. If the difference exceeds the preset safety protection zone, a compensation pulse signal is automatically generated.

[0095] The preparation status feedback submodule monitors the load current change rate of the stirring motor in real time. When the current fluctuation value converges to the stable range, it generates a stirring completion instruction including a mixing status confirmation flag and a preparation process end timestamp, and presets the drainage system activation signal.

[0096] The proportioning execution control module includes a material proportioning execution submodule, a hardware driver mapping submodule, and a preparation status feedback submodule. The material proportioning execution submodule receives the theoretical requirement. And the specifications for batch B. The specifications for batch B show: weight per tablet is... The effective chlorine content is Set the target solution concentration as follows: The program first calculates the theoretically required total amount of available chlorine: Next, calculate the required number of tablets: Since the feeding mechanism can only process whole-number tablets, the program performs a round-up operation to determine the number of tablets. Tablets. Based on the adjusted number of tablets, the influent flow rate is reverse-corrected to maintain the target concentration: At this point, the system determines the following execution parameters: inflow rate. Number of tablets piece.

[0097] The hardware driver mapping submodule generates control signals based on the above parameters. For water inlet control, it reads the flow characteristic curve of the solenoid valve, and the flow rate under the current water pressure is... Calculate the inlet valve duration: For feeding control, the single-step feed constant of the feeding screw mechanism is read, and the setting is made for each motor rotation... (One step angle) Discharge powder (This assumes the tablets have been pre-crushed or the mechanism is adapted for tablet dispensing; this example demonstrates the logic based on weight calculation.) The required total weight is... Calculate the number of pulses corresponding to the total rotation angle: (The following needs to be excluded.) Then the total number of steps Step. The program converts "open the solenoid valve for 20 seconds" and "stepper motor executes 64 pulses" into low-level drive level signals. During the feeding process, the motor encoder feedback is read in real time. If the encoder feedback value is 60 steps and the difference is 4 steps, exceeding the preset safety protection zone (2 steps), the submodule automatically generates 4 compensation pulse signals and sends them to the driver.

[0098] The preparation status feedback submodule monitors the load current of the stirring motor with a sampling period of 100ms. In the initial stage, due to the undissolved solid tablets and water flow disturbance, the root mean square value of the current fluctuates significantly. The program sets the stability interval determination criterion as the rate of change of current over 10 consecutive sampling periods. When the detected current value is at If the mixture remains within the specified range for more than 5 seconds, the solution is considered to have reached a homogeneous phase. The submodule then generates a stirring completion command that includes a mixing status confirmation flag (set to 1) and a preparation process end timestamp (current system time), while simultaneously setting the drainage system activation signal to the ready state (to be triggered after the concentration detection is qualified).

[0099] Please see Figure 1 and Figure 5 The concentration data acquisition module acquires the solution conductivity voltage and solution temperature values ​​based on the stirring completion command, calls the least squares method to process the solution conductivity voltage and solution temperature values ​​to calculate the actual concentration value, and outputs the actual concentration value.

[0100] The actual concentration values ​​include the temperature-compensated chloride ion concentration reading, the current detection confidence interval, and the linear regression fitting residual value;

[0101] The concentration data acquisition module includes:

[0102] The sensor array acquisition submodule receives the stirring completion command and synchronously triggers the conductivity probe and thermistor to continuously acquire the solution conductivity voltage and solution temperature values ​​during the static stage after stirring stops.

[0103] The compensation algorithm processing submodule uses the least squares algorithm model to linearly fit the solution conductivity voltage, introduces the solution temperature value to perform thermodynamic correction on the fitting result, and calculates the chloride ion concentration reading after temperature compensation.

[0104] The process of calculating the temperature-compensated chloride ion concentration reading in the compensation algorithm processing submodule includes:

[0105] Obtain the solution conductivity voltage and solution temperature values, call the pre-calibrated electrochemical response equation, substitute the parameters, and calculate the chloride ion concentration reading after temperature compensation;

[0106] The temperature-compensated chloride ion concentration reading is calculated using the following formula:

[0107] ;

[0108] in, This represents the chloride ion concentration reading after temperature compensation. Voltage representing solution conductivity The slope of the conductivity-concentration standard curve represents the electrical conductivity-concentration standard curve. The intercept of the conductivity-concentration standard curve represents the value of the standard curve. The temperature compensation coefficient representing chloride ions. Represents the solution temperature value. Represents the standard calibration temperature;

[0109] The quality confidence assessment submodule analyzes the dispersion of continuously collected data, calculates the linear regression fitting residual value, determines the current detection confidence interval based on the linear regression fitting residual value, and outputs the actual concentration value.

[0110] The concentration data acquisition module includes a sensor array acquisition submodule, a compensation algorithm processing submodule, and a quality confidence assessment submodule. Two seconds after receiving the stirring completion command (during the settling and defoaming time), the sensor array acquisition submodule triggers the conductivity probe and NTC thermistor immersed in the mixing tank. The acquisition card continuously acquires 50 sets of data at a frequency of 1kHz, and the average value is taken after digital filtering. The currently acquired raw data is: solution conductivity voltage. Solution temperature value .

[0111] The compensation algorithm processing submodule retrieves a pre-calibrated parameter set. This parameter set originates from laboratory standard measurements, including the slope of the conductivity-concentration standard curve. ,intercept Chloride ion temperature compensation coefficient Standard calibration temperature The program executes the temperature-compensated chloride ion concentration reading. The calculation of chloride ion concentration is performed using a formula designed to eliminate the effect of temperature on electrolyte conductivity, restoring electrical signals from non-standard temperatures to concentration values ​​at standard temperatures. The temperature-compensated chloride ion concentration reading is calculated using the following formula: ;in, This represents the chloride ion concentration reading after temperature compensation. The slope of the conductivity-concentration standard curve represents the electrical conductivity-concentration standard curve. Voltage representing solution conductivity The intercept of the conductivity-concentration standard curve represents the value of the standard curve. The temperature compensation coefficient representing chloride ions. Represents the solution temperature value. This represents the standard calibration temperature. Substituting the aforementioned parameters into the formula: ; Calculate the basic concentration term: ; Calculate the temperature correction term: ; Calculate the final concentration: The calculation results show that the actual chloride ion concentration reading after temperature compensation is: This result is consistent with the result set in Example 3. The discrepancy in target concentration is mainly due to the downward adjustment effect caused by the temperature correction factor. The system will use this result to assess whether additional addition is needed.

[0112] The quality confidence assessment submodule performs dispersion analysis on the 50 sets of raw voltage data collected. It calculates the standard deviation of the data sets. Based on residual analysis of the linear regression model, the linear regression fit residuals are calculated. .like Less than the preset benchmark value If the measurement system is stable, then the current detection confidence interval is determined. ,Right now The submodule ultimately outputs the actual concentration value: (Confidence interval) This serves as the final basis for quality judgment.

[0113] Table 2. Concentration Detection Calculation Parameters and Results

[0114] Parameters numerical values unit illustrate <![CDATA[Sampling voltage V ec > 2.45 V Sensor raw signal <![CDATA[Collect temperature T meas > 22 ∘C Ambient temperature Baseline concentration (kV+b) 500 mg / L Uncompensated calculation value Temperature correction factor 0.94 - (1+αΔT) <![CDATA[Final concentration C ion > 470 mg / L Compensated output value

[0115] Referring to Table 2, the system completed the conversion calculation from physical signals to accurate concentration values.

[0116] The above embodiments illustrate preferred embodiments of the present invention. Any equivalent adjustments to the technical solution based on software engineering methods are within the scope of protection, including but not limited to: implementing algorithm logic using different programming languages, refactoring functional modules into services, adjusting data interaction protocols, and optimizing resource scheduling strategies. Any implementation scheme derived from reasonable modifications to the data processing flow, service call chain, or system architecture layer without departing from the core technology of the present invention should be considered within the scope of protection defined by the claims of the present invention.

Claims

1. A quality monitoring and control system for the entire process of disinfectant use, characterized in that, The system includes: The demand calculation module obtains the disinfection area, disinfection frequency, and unit area consumption coefficient of the ward surface, processes the disinfection area, disinfection frequency, and unit area consumption coefficient to generate the theoretical disinfectant demand, and transmits it to the inventory status monitoring module. The inventory status monitoring module reads the electronic tag based on the theoretical disinfectant demand, parses the production date and expiration threshold from the electronic tag to filter valid inventory batch information, and transmits the valid inventory batch information and the theoretical disinfectant demand to the proportioning execution control module. The mixing control module calculates the water intake and tablet quantity based on the effective inventory batch information and the theoretical disinfectant requirement. It adjusts the water intake valve duration and motor stepping frequency according to the water intake and tablet quantity, generates a stirring completion command, and transmits it to the concentration data acquisition module. The concentration data acquisition module acquires the solution conductivity voltage and solution temperature values ​​based on the stirring completion command, calls the least squares method to process the solution conductivity voltage and solution temperature values ​​to calculate the actual concentration value, and outputs the actual concentration value.

2. The disinfectant usage process quality monitoring and control system according to claim 1, characterized in that, The theoretical disinfectant requirement includes the theoretical usage per task, the cumulative quota per unit period, and the preset consumption deviation threshold. The effective inventory batch information includes the serial number of the available bottle electronic tag, the coordinates of the corresponding storage cabinet, and the batch call priority identifier. The mixing completion instruction includes a mixing status confirmation flag, a preparation process end timestamp, and a drain system activation signal. The actual concentration value includes the chloride ion concentration reading after temperature compensation, the current detection confidence interval, and the linear regression fitting residual value.

3. The disinfectant usage process quality monitoring and control system according to claim 2, characterized in that, The demand calculation module includes: The task parameter parsing submodule obtains the disinfection area and frequency of the ward surface, performs a multiplication operation on the disinfection area and the disinfection frequency to quantify the basic workload, and calls the preset risk level database to match the corresponding unit area consumption coefficient. The consumption simulation calculation submodule uses the unit area consumption coefficient to perform weighted calculations on the basic workload to generate the theoretical consumption of a single task, and retrieves the task records of historical periods for cumulative processing to update the cumulative quota of the unit period. The threshold dynamic setting submodule calculates the statistical variance of the theoretical usage of the single task within a preset time window, sets a preset consumption deviation threshold that allows fluctuations based on the statistical variance, and combines these to generate the theoretical disinfectant requirement.

4. The disinfectant usage process quality monitoring and control system according to claim 3, characterized in that, The inventory status monitoring module includes: The label information decoding submodule initiates an RFID scanning procedure in response to the theoretical disinfectant demand, captures the RFID feedback signal in the area and performs demodulation processing, and extracts the production date and expiration date threshold from the demodulated data frame. The expiration date screening and verification submodule obtains the current system time and calculates the remaining shelf life by comparing it with the production date, and then removes batches that exceed the expiration date threshold to lock the available bottle electronic label serial number. The sorting optimization arbitration submodule performs a weighted score based on the remaining shelf life and the spatial distance to the corresponding storage cabinet coordinates, generates a batch call priority identifier based on the score results, and packages and outputs the valid inventory batch information.

5. The disinfectant usage process quality monitoring and control system according to claim 4, characterized in that, The proportioning execution control module includes: The material allocation and execution submodule analyzes the theoretical disinfectant requirement to determine the target solution concentration and total volume, and calculates the water intake and tablet quantity based on the specification parameters in the effective inventory batch information. The hardware-driven mapping submodule maps the water inlet volume to the opening time characteristics of the solenoid valve to adjust the water inlet valve duration, and converts the number of tablets into the rotation angle pulse of the feeding mechanism to adjust the motor stepping number. The preparation status feedback submodule monitors the load current change rate of the stirring motor in real time. When the current fluctuation value converges to the stable range, it generates a stirring completion instruction including a mixing status confirmation flag and a preparation process end timestamp, and presets the drainage system activation signal.

6. The disinfectant usage process quality monitoring and control system according to claim 5, characterized in that, The concentration data acquisition module includes: The sensor array acquisition submodule receives the stirring completion command and synchronously triggers the conductivity probe and thermistor to continuously acquire the solution conductivity voltage and solution temperature values ​​during the static stage after stirring stops. The compensation algorithm processing submodule uses the least squares algorithm model to linearly fit the solution conductivity voltage, introduces the solution temperature value to perform thermodynamic correction on the fitting result, and calculates the chloride ion concentration reading after temperature compensation. The quality confidence assessment submodule analyzes the dispersion of continuously collected data, calculates the linear regression fitting residual value, determines the current detection confidence interval based on the linear regression fitting residual value, and outputs the actual concentration value.

7. The disinfectant usage process quality monitoring and control system according to claim 6, characterized in that, The process of calculating the theoretical usage for a single task in the consumption simulation calculation submodule includes: The disinfection area of ​​the ward surface, the disinfection frequency, and the unit area consumption coefficient are obtained. A consumption calculation model is established in combination with the environmental evaporation loss factor to calculate the theoretical consumption of a single task. The calculation of the theoretical usage for a single task follows the following formula: ； in, This represents the theoretical usage per single task. Represents the total number of functional partitions. The area of ​​surface disinfection in the representative ward is the first The specific area of ​​each functional zone Representing the Disinfection frequency for each functional area, Representing the The unit area consumption coefficient corresponding to each functional zone This represents the environmental evaporation loss factor derived from historical environmental humidity data.

8. The disinfectant usage process quality monitoring and control system according to claim 7, characterized in that, The process of calculating the temperature-compensated chloride ion concentration reading in the compensation algorithm processing submodule includes: The solution conductivity voltage and solution temperature values ​​are obtained, and the parameters are substituted into the pre-calibrated electrochemical response equation to calculate the temperature-compensated chloride ion concentration reading. The temperature-compensated chloride ion concentration reading is calculated according to the following formula: ； in, This represents the chloride ion concentration reading after temperature compensation. Voltage representing solution conductivity The slope of the conductivity-concentration standard curve represents the electrical conductivity-concentration standard curve. The intercept of the conductivity-concentration standard curve represents the value of the standard curve. The temperature compensation coefficient representing chloride ions. Represents the solution temperature value. This represents the standard calibration temperature.

9. The disinfectant usage process quality monitoring and control system according to claim 4, characterized in that, The process of generating the batch call priority identifier in the sorting optimization arbitration submodule includes: Obtain the production date and the corresponding storage cabinet coordinates, calculate the remaining shelf life days of the inventory batch and the robotic arm grasping path length, and generate the batch call priority identifier using dual weight logic; Specifically, the batches with earlier production dates are assigned a first high priority weight, and the batches whose corresponding storage cabinet coordinates are closer to the discharge port are assigned a second auxiliary weight. After comprehensive calculation, a sorted list including the batch call priority identifier is generated.

10. The disinfectant usage process quality monitoring and control system according to claim 5, characterized in that, The process of adjusting the motor step count in the hardware driver mapping submodule includes: The number of tablets and the single-step feed constant of the feeding screw mechanism are obtained, the total rotation angle required to complete the feeding is calculated, and the total rotation angle is quantized into discrete drive pulses to determine the number of motor steps. During the feeding process, the feedback signal of the motor encoder is read in real time, and the difference between the actual number of steps and the number of motor steps is calculated. If the difference exceeds the preset safety protection zone, a compensation pulse signal is automatically generated.

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