Liquid medicine circulation filling control method and system for restraining flow pulsation

Abstract

The invention relates to the technical field of process control, and discloses a liquid medicine circulation filling control method and system for inhibiting flow pulsation, and the method comprises the steps: obtaining an original flow signal and liquid medicine viscosity data of liquid medicine in a liquid medicine filling pipeline, and calculating a reference deviation value of the liquid medicine viscosity data, performing gain effect analysis on the liquid medicine viscosity data based on the calculated reference deviation value to obtain a dynamic gain coefficient of the liquid medicine viscosity data, and acting the dynamic gain coefficient on the obtained original flow signal of the liquid medicine in the liquid medicine filling pipeline to obtain a compensation control signal; a pressure fluctuation signal in the compensation control signal is decomposed into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, the two decomposed components are subjected to frequency-band-divided collaborative filtering, a frequency division filtering signal is obtained, and the opening degree of a liquid medicine filling valve is adjusted according to the frequency division filtering signal; according to the invention, the filling precision of the liquid medicine capable of inhibiting the flow pulsation can be improved.

Description

Technical Field

[0001] This invention relates to the field of process control technology, and in particular to a method and system for controlling the circulation and filling of pharmaceutical liquid to suppress flow pulsation. Background Technology

[0002] In the process of filling liquid medicine, flow pulsation is one of the main problems affecting filling accuracy. Existing technologies usually use fixed-gain PID control or simple filtering methods to suppress flow fluctuations. However, these methods are difficult to adapt to the dynamic changes in the viscosity of the liquid medicine. Since the viscosity of the liquid medicine fluctuates with factors such as temperature and batch, fixed-gain control cannot adjust the compensation intensity in real time, resulting in sluggish response of high-viscosity liquid medicine or overcompensation of low-viscosity liquid medicine, which in turn leads to filling volume deviation. In addition, the existing technology is relatively crude in processing pressure fluctuation signals. It often only suppresses interference through single-band filtering and fails to effectively distinguish the coupling effect of high-frequency mechanical vibration and low-frequency flow pulsation. As a result, interference components are still left in the filtered signal, affecting the accuracy of valve control.

[0003] Traditional methods do not consider dynamic gain analysis of viscosity data, resulting in a mismatch between the compensation signal and actual needs. At the same time, the lack of frequency band collaborative filtering technology makes it impossible to completely separate high-frequency mechanical noise and low-frequency flow pulsation. Valve opening adjustment is easily affected by residual noise. These defects not only reduce filling accuracy, but may also cause mechanical oscillation or filling interruption due to control signal distortion. Therefore, how to dynamically adapt to changes in drug viscosity, accurately separate and suppress multi-frequency interference to ensure flow stability and improve filling accuracy has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for controlling the circulation and filling of pharmaceutical liquid to suppress flow pulsation, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for controlling the circulation and filling of pharmaceutical solutions to suppress flow pulsation, comprising:

[0006] S1, acquire the original flow signal and viscosity data of the liquid medicine in the liquid medicine filling pipeline;

[0007] S2, calculate the baseline deviation value of the drug solution viscosity data, perform gain effect analysis on the drug solution viscosity data based on the baseline deviation value, and obtain the dynamic gain coefficient of the drug solution viscosity data;

[0008] S3, apply the dynamic gain coefficient to the original flow signal to obtain a compensation control signal;

[0009] S4, decompose the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, and perform frequency-band collaborative filtering on the decomposed result to obtain the frequency-band filtered signal of the compensation control signal;

[0010] S5, adjust the opening degree of the liquid filling valve according to the frequency division filter signal.

[0011] In a preferred embodiment, acquiring the original flow signal and viscosity data of the liquid medicine in the filling pipeline includes:

[0012] The flow signal of the medicine liquid is obtained by the flow sensor in the medicine liquid filling pipeline, and the flow signal of the medicine liquid is converted into digital simulation to obtain the original flow signal of the medicine liquid in the medicine liquid filling pipeline.

[0013] Based on the viscosity detection device in the drug filling pipeline, real-time viscosity data sampling values ​​are extracted;

[0014] The real-time viscosity data sampling values ​​are subjected to data standardization processing to obtain the viscosity data of the drug solution in the drug solution filling pipeline.

[0015] In a preferred embodiment, calculating the baseline deviation value of the drug solution viscosity data includes:

[0016] Calculate the difference between the viscosity data of the liquid medicine and the preset reference viscosity to obtain the reference deviation item of the liquid medicine in the liquid medicine filling pipeline;

[0017] The ratio of the reference deviation term to the reference viscosity is used as the viscosity deviation term of the drug solution in the drug solution filling pipeline;

[0018] The viscosity deviation term is scaled to obtain the baseline deviation value of the drug solution viscosity data.

[0019] In a preferred embodiment, the step of performing gain effect analysis on the drug solution viscosity data based on the reference deviation value to obtain the dynamic gain coefficient of the drug solution viscosity data includes:

[0020] The reference deviation value is input into the nonlinear gain function to obtain the original gain coefficient, wherein the mathematical expression of the nonlinear gain function is as follows:

[0021]

[0022] In the formula, This is the original gain coefficient. Basic gain coefficient, Gain adjustment factor It is a non-linear exponent. This is the baseline deviation value;

[0023] The original gain coefficient is subjected to saturation limiting processing to obtain the dynamic gain coefficient.

[0024] In a preferred embodiment, applying the dynamic gain coefficient to the original flow signal to obtain a compensation control signal includes:

[0025] The original flow signal and the dynamic gain coefficient are time-aligned to obtain a time-series gain flow sequence.

[0026] The time-series gain flow rate sequence and the original flow rate signal are combined to generate the original compensation signal for the drug filling pipeline;

[0027] The original compensation signal is dynamically clipped to obtain the compensation control signal for the drug filling pipeline.

[0028] In a preferred embodiment, the step of decomposing the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component includes:

[0029] Obtain the mechanical vibration frequency band and flow pulsation frequency band of the drug filling pipeline;

[0030] The pressure fluctuation signal in the compensation control signal is subjected to anti-aliasing preprocessing to generate a standardized pressure signal;

[0031] The standardized pressure signal is decomposed into a high-frequency subband coefficient set and a low-frequency subband coefficient set;

[0032] The high-frequency subband coefficient set is correlated with the mechanical vibration frequency band to obtain the high-frequency mechanical vibration subband coefficient;

[0033] The low-frequency subband coefficient set is correlated with the flow pulsation frequency band to obtain the low-frequency flow pulsation subband coefficient;

[0034] The high-frequency mechanical vibration sub-band coefficient and the low-frequency flow pulsation sub-band coefficient are reconstructed and inversely transformed to generate the high-frequency mechanical vibration component and the low-frequency flow pulsation component of the drug filling pipeline.

[0035] In a preferred embodiment, the step of performing frequency-band collaborative filtering on the decomposed result to obtain the frequency-band filtered signal of the compensation control signal includes:

[0036] The high-frequency mechanical vibration component is subjected to time-varying narrowband filtering to generate a high-frequency mechanical filtered component.

[0037] Adaptive notch filtering is applied to the low-frequency flow pulsation component to generate a low-frequency flow filtered component;

[0038] The high-frequency mechanical filter component and the low-frequency flow filter component are combined to generate the frequency-divided filter signal of the compensation control signal.

[0039] In a preferred embodiment, the step of fusing the high-frequency mechanical filter component and the low-frequency flow filter component to generate the frequency-divided filter signal of the compensation control signal includes:

[0040] Based on the covariance of the high-frequency mechanical filter component and the low-frequency flow filter component, the high-frequency state covariance matrix and the low-frequency observation covariance matrix of the compensation control signal are constructed respectively.

[0041] Weights are assigned to the high-frequency mechanical filter component and the low-frequency flow filter component;

[0042] Based on the weight allocation result, the high-frequency state covariance matrix and the low-frequency observation covariance matrix are weighted and fused to generate the frequency-divided filter signal of the compensation control signal.

[0043] In a preferred embodiment, adjusting the opening degree of the liquid filling valve according to the frequency division filter signal includes:

[0044] Based on the frequency division filtering signal, the theoretical opening value of the liquid filling valve is generated through a preset flow-opening conversion rule;

[0045] The real-time deviation of the theoretical opening value is statistically analyzed, and the statistical results are integrated into the opening adjustment amount of the liquid filling valve.

[0046] The opening degree of the medicine filling valve is adjusted based on the opening degree adjustment amount.

[0047] To address the above problems, the present invention also provides a liquid filling control system for suppressing flow pulsation, the system comprising:

[0048] The signal dynamic capture module is used to acquire the original flow signal and viscosity data of the liquid medicine in the liquid medicine filling pipeline;

[0049] The deviation gain analysis module is used to calculate the baseline deviation value of the drug solution viscosity data, perform gain effect analysis on the drug solution viscosity data based on the baseline deviation value, and obtain the dynamic gain coefficient of the drug solution viscosity data.

[0050] The compensation signal generation module is used to apply the dynamic gain coefficient to the original flow signal to obtain a compensation control signal;

[0051] The frequency division collaborative filtering module is used to decompose the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, and to perform frequency division collaborative filtering on the decomposed result to obtain the frequency division filtered signal of the compensation control signal.

[0052] The valve intelligent adjustment module is used to adjust the opening degree of the liquid filling valve according to the frequency division filtering signal.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. By adjusting the compensation signal in real time through dynamic gain coefficient, the control deviation problem caused by changes in drug viscosity can be effectively solved. This process relies on nonlinear gain function and saturation limiting processing, which can adapt well to high and low viscosity conditions. In actual filling, the viscosity of the drug solution will change due to factors such as temperature and batch. When the viscosity increases, the dynamic gain coefficient will be adjusted accordingly to enhance the compensation force, avoiding the response lag problem that often occurs in traditional fixed gain control under high viscosity conditions. When the viscosity decreases, it can prevent overcompensation by reasonable adjustment. This dynamic adjustment mechanism accurately adapts to the viscosity change characteristics of the drug solution, thereby greatly improving filling accuracy.

[0055] 2. By employing frequency-band collaborative filtering technology, the pressure fluctuation signal in the compensation control signal can be accurately decomposed into high-frequency mechanical vibration components and low-frequency flow pulsation components. For the decomposed high-frequency mechanical vibration components, time-varying narrowband filtering is used, while for the low-frequency flow pulsation components, adaptive notch filtering is performed. Through this frequency-band collaborative filtering method, the negative impact of multi-frequency interference on valve control can be comprehensively and effectively eliminated, ensuring that the flow rate of the liquid remains stable during the filling process, and providing a strong guarantee for high-precision filling. Attached Figure Description

[0056] Figure 1 This is a schematic flowchart of a method for controlling the circulation and filling of medicine to suppress flow pulsation according to an embodiment of the present invention;

[0057] Figure 2 This is a functional block diagram of a liquid medicine circulation filling control system for suppressing flow pulsation, provided in an embodiment of the present invention. Detailed Implementation

[0058] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0059] This application provides a method for controlling the circulation and filling of pharmaceutical solutions to suppress flow pulsation. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for controlling the circulation and filling of pharmaceutical solutions to suppress flow pulsation can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0060] Reference Figure 1 The diagram shown is a flowchart illustrating a method for controlling the circulation and filling of pharmaceutical solutions to suppress flow pulsation, according to an embodiment of the present invention. In this embodiment, the method for controlling the circulation and filling of pharmaceutical solutions to suppress flow pulsation includes:

[0061] S1, acquire the original flow signal and viscosity data of the liquid medicine in the liquid medicine filling pipeline;

[0062] In this embodiment of the invention, obtaining the original flow signal and viscosity data of the liquid medicine in the filling pipeline includes:

[0063] The flow signal of the medicine liquid is obtained by the flow sensor in the medicine liquid filling pipeline, and the flow signal of the medicine liquid is converted into digital simulation to obtain the original flow signal of the medicine liquid in the medicine liquid filling pipeline.

[0064] Based on the viscosity detection device in the drug filling pipeline, real-time viscosity data sampling values ​​are extracted;

[0065] The real-time viscosity data sampling values ​​are subjected to data standardization processing to obtain the viscosity data of the drug solution in the drug solution filling pipeline.

[0066] It should be noted that the digital-to-analog signal conversion operation involves sampling, quantizing, and encoding the raw analog voltage signal output by the flow sensor to generate a raw flow signal in digital form.

[0067] Furthermore, the original analog voltage signal represents the continuous-time analog voltage value output by the sensor, and the original flow signal represents the digital flow signal value of the original analog voltage signal.

[0068] Furthermore, the sampling frequency in the sampling processing of the original analog voltage signal is set to 4 times the critical frequency of the filling system.

[0069] Furthermore, the critical frequency of the filling system is the theoretical lower limit for ensuring distortion-free sampling of the flow signal. Essentially, it is the extreme value of the composite coupling frequency of mechanical structure and fluid dynamics. Based on the dual-component dynamic coupling effect of the fundamental frequency of mechanical vibration of the filling valve and the dominant frequency of turbulent flow of the liquid medicine in the pipeline, the maximum dominant frequency component is extracted by spectrum analysis and superimposed with a safety margin frequency offset to obtain the critical frequency threshold for strict anti-aliasing of the system. The critical frequency threshold is the critical frequency of the filling system, which is used to determine the minimum safety boundary of the analog-to-digital conversion sampling rate to ensure that high-frequency vibration artifacts do not contaminate the effective flow signal.

[0070] Furthermore, the fundamental frequency of mechanical vibration of the filling valve is determined by the inherent characteristics of the valve core mass-spring system, while the dominant frequency of turbulent flow of the liquid medicine in the pipeline is the vortex shedding frequency determined by the Reynolds number.

[0071] Furthermore, the vortex shedding frequency directly affects the calculation of the critical frequency of the filling system, which is used to determine the sampling rate of the analog-to-digital conversion and avoid high-frequency aliasing noise from contaminating the effective flow signal.

[0072] Furthermore, the Reynolds number is a dimensionless parameter, obtained by calculating the product of the drug solution density, drug solution flow rate, and pipeline characteristic length, and then dividing the product result by the dynamic viscosity of the drug solution.

[0073] Furthermore, the encoding and processing of the original analog voltage signal is the core step in the digitization of the flow signal. The sampling frequency is set to four times the critical frequency of the filling system. Anti-aliasing pre-filters are used to suppress noise above the critical frequency of the filling system, and 12-bit quantization precision conversion is performed to obtain a high-precision analog voltage signal. The high-precision analog voltage signal is then subjected to time discretization and amplitude discretization to obtain a discrete digital flow sequence. The values ​​in the discrete digital flow sequence are proportional to the flow rate of the liquid.

[0074] Furthermore, the 12-bit quantization precision conversion operation is a signal digitization process implemented by an analog-to-digital converter. The specific steps include: sampling the analog voltage signal output by the flow sensor, and then performing 12-bit precision quantization. During the quantization process, the amplitude of the continuous voltage signal is discretized into 4096 levels to generate a discrete digital flow sequence. The value of this sequence is proportional to the flow rate of the liquid, ensuring high-precision signal conversion for subsequent compensation control.

[0075] Furthermore, the flow sensor adopts a turbine flow meter, whose physical response relies on the Hall effect principle. It generates a proportional voltage signal through the rotation speed of the turbine, and uses an analog-to-digital converter to complete the time domain sampling to digital domain conversion within 0.5μs to ensure real-time performance.

[0076] It should be noted that the data standardization process is obtained by dividing the difference between the original sampled value output by the viscosity detection device and the preset reference viscosity value by the standard deviation of historical viscosity data, wherein the preset reference viscosity value is the mean value generated based on historical data.

[0077] Furthermore, the standardization process is implemented using an embedded microcontroller, which reduces timing latency through direct memory access. Its physical meaning is to eliminate the systematic bias of viscosity measurement caused by ambient temperature and batch differences, creating clean data input for subsequent dynamic compensation.

[0078] S2, calculate the baseline deviation value of the drug solution viscosity data, perform gain effect analysis on the drug solution viscosity data based on the baseline deviation value, and obtain the dynamic gain coefficient of the drug solution viscosity data;

[0079] In this embodiment of the invention, calculating the benchmark deviation value of the drug solution viscosity data includes:

[0080] Calculate the difference between the viscosity data of the liquid medicine and the preset reference viscosity to obtain the reference deviation item of the liquid medicine in the liquid medicine filling pipeline;

[0081] The ratio of the reference deviation term to the reference viscosity is used as the viscosity deviation term of the drug solution in the drug solution filling pipeline;

[0082] The viscosity deviation term is scaled to obtain the baseline deviation value of the drug solution viscosity data.

[0083] It should be noted that the reference deviation term is the difference between the viscosity data of the drug solution and the preset reference viscosity, indicating the degree of difference between the viscosity data of the drug solution and the preset reference viscosity. The preset reference viscosity value is generated based on the historical viscosity data of the same batch of drug solution through a mean filter.

[0084] It should be noted that the preset reference viscosity is obtained by calculating the average value of historical viscosity data of the same batch of medicine. Specifically, historical viscosity data samples are collected and the average value is calculated. The preset reference viscosity is used to calculate the reference deviation value in subsequent calculations to eliminate systematic measurement deviations caused by ambient temperature and batch differences.

[0085] It should be noted that the viscosity deviation term is calculated by exponentially multiplying the absolute value of the ratio of the reference deviation term to the preset reference viscosity. The power function in the exponential calculation is a preset exponential weighting factor used to enhance the response intensity in the high deviation region, with a default value of 1.5.

[0086] Furthermore, the viscosity deviation term is used to convert the linear relative deviation into an exponentially weighted value to match the nonlinear characteristics of viscosity-flow control and avoid oversensitivity in the low deviation region.

[0087] Furthermore, scaling the viscosity deviation term involves applying a preset nonlinear conversion coefficient to the mapping deviation term, multiplying the mapping deviation term by the nonlinear conversion coefficient.

[0088] Furthermore, the nonlinear conversion coefficient is a dimensionless coefficient used to adjust the deviation sensitivity, with a value range of [0.8, 1.2].

[0089] In this embodiment of the invention, the step of performing gain effect analysis on the drug solution viscosity data based on the reference deviation value to obtain the dynamic gain coefficient of the drug solution viscosity data includes:

[0090] The reference deviation value is input into the nonlinear gain function to obtain the original gain coefficient, wherein the mathematical expression of the nonlinear gain function is as follows:

[0091]

[0092] In the formula, This is the original gain coefficient. Basic gain coefficient, Gain adjustment factor It is a non-linear exponent. This is the baseline deviation value;

[0093] The original gain coefficient is subjected to saturation limiting processing to obtain the dynamic gain coefficient.

[0094] It should be noted that the nonlinear gain function amplifies the viscosity deviation nonlinearly through exponential mapping, thus solving the problem of sluggish flow response of high-viscosity liquids.

[0095] It should be noted that the original gain coefficient is an intermediate gain value dynamically generated based on the viscosity deviation of the drug solution, which can dynamically adapt to the rheological properties of the drug solution.

[0096] It should be noted that the basic gain coefficient index is the reference gain value under standard viscosity to ensure the stability of flow control;

[0097] The gain adjustment factor is used to control the rate at which the gain increases with the deviation. When the gain adjustment factor is less than 0.5, it indicates that the viscosity of the drug solution is low and a gradual change compensation is performed. When the gain adjustment factor is greater than 0.5, it indicates that the viscosity of the drug solution is high and a steep change compensation is performed. The value range of the gain adjustment factor is 0.2 to 0.8.

[0098] Nonlinear exponents are used to enhance the gain response in the high-bias region;

[0099] The reference deviation value is the normalized offset between the real-time viscosity and the reference value, and its value ranges from [0,1].

[0100] Furthermore, the linear deviation is converted into an exponentially growing gain through exponential function calculations to match the nonlinear rheological characteristics of the drug solution.

[0101] It should be noted that the mathematical expression of the function used for saturation limiting is as follows:

[0102]

[0103] In the formula, This is the dynamic gain coefficient. This is the original gain coefficient. This is the lower limit of the gain coefficient. This represents the upper limit of the gain coefficient.

[0104] Furthermore, the lower limit of the gain coefficient is used to prevent ultra-low gain, such as when the drug solution suddenly becomes low in viscosity, causing insufficient opening of the control valve and interrupting the filling process.

[0105] The upper limit of the gain coefficient is used to suppress ultra-high gain, such as when a sudden increase in viscosity causes valve over-adjustment, resulting in flow oscillation.

[0106] Furthermore, saturation limiting is essentially a hardware-level threshold constraint for limiting operations, which can ensure stability under extreme viscosity fluctuations and avoid mechanical damage or filling accuracy deviations caused by gain overflow.

[0107] It should be noted that the lower limit of the gain coefficient is the minimum gain threshold preset in the saturation limiting process. It is used to constrain the dynamic gain coefficient from being too low, so as to prevent the gain from being too small due to a sudden drop in the viscosity of the liquid. It reflects the stability boundary of the control system. In order to avoid the possibility that insufficient gain may cause the valve opening to be too small, filling interruption or flow response lag when the viscosity of the liquid unexpectedly decreases due to factors such as batch changes, the lower limit of the gain coefficient can ensure the minimum compensation strength and avoid control failure under low viscosity conditions.

[0108] It should be noted that the upper limit of the gain coefficient is the maximum gain threshold preset in the saturation limiting process. It is used to limit the dynamic gain coefficient from not exceeding the safe value, to suppress the gain overflow caused by the sharp increase in viscosity, and to correspond to the maximum allowable disturbance intensity of fluid control. It is used to prevent the system from running out of control under ultra-high gain. High viscosity liquids are prone to exponential growth of gain. If not limited, it will cause valve over-adjustment, flow oscillation or mechanical resonance.

[0109] It should be noted that the dynamic gain coefficient is the final gain value after saturation limiting processing. It represents the real-time compensation intensity required for the dynamic change of the drug viscosity and is used to balance the nonlinear characteristics of fluid rheology. Its exponential growth mechanism is used to map the viscosity-flow control sensitivity. The dynamic gain coefficient acts as the core compensation parameter on the original flow signal to solve the response hysteresis problem of traditional fixed gain.

[0110] S3, apply the dynamic gain coefficient to the original flow signal to obtain a compensation control signal;

[0111] In this embodiment of the invention, applying the dynamic gain coefficient to the original flow signal to obtain a compensation control signal includes:

[0112] The original flow signal and the dynamic gain coefficient are time-aligned to obtain a time-series gain flow sequence.

[0113] The time-series gain flow rate sequence and the original flow rate signal are combined to generate the original compensation signal for the drug filling pipeline;

[0114] The original compensation signal is dynamically clipped to obtain the compensation control signal for the drug filling pipeline.

[0115] It should be noted that the time-series gain flow sequence is a synchronous data sequence generated by aligning the original flow signal and the dynamic gain coefficient in time. It is used to eliminate phase errors caused by the asynchrony of signal transmission, ensure strict correspondence between gain and flow data at the same time scale, avoid flow fluctuations during the filling start-up and shutdown phases, and essentially prevent valve action delays caused by time offset of control commands.

[0116] It should be noted that the original compensation signal is an intermediate signal generated by synthesizing the time-series gain flow rate sequence and the original flow rate signal. It solves the filling accuracy fluctuation during the acceleration and deceleration of the liquid. As an unlimited signal before dynamic clipping, it has both response agility and error pre-compensation capability.

[0117] It should be noted that the compensation control signal is a control command after the original compensation signal has been dynamically clipped. It is an execution command within the safe range. The upper and lower limits of the compensation control signal correspond to the minimum valve opening and the full-scale flow rate, ensuring that the control signal complies with the physical limitations of the mechanical actuator.

[0118] It should be noted that the time alignment process is based on the asynchronous transmission characteristics of the original flow signal and the dynamic gain coefficient. It performs delay matching and clock synchronization latching operations for two sampling cycles through a hardware-level buffer to eliminate time deviations between signals, ensure accurate data alignment under the same time scale, and prevent filling flow fluctuations caused by control phase errors.

[0119] It should be noted that signal synthesis is based on the product of the original flow signal and the dynamic gain coefficient, and the composite calculation result of the superposition of the flow derivative term and the compensation enhancement product. By using the time-aligned original flow signal and the dynamic gain coefficient, static gain weighting and dynamic rate of change enhancement are performed by a multiplier and a differential enhancement unit to generate the original compensation signal. It has both static adaptability and dynamic agility, and overcomes the response lag problem in the filling start-up and shutdown stages.

[0120] Furthermore, the flow derivative term represents the trend of change of the original flow signal per unit time. It is based on the flow change rate as the physical essence and is obtained by performing time normalization calculation on the flow difference between adjacent sampling points through the differential operation unit. The flow change rate is the difference between the original flow signal of the current sampling point and the original flow signal of the previous sampling point.

[0121] Furthermore, the compensation enhancement product is obtained by multiplying the original flow signal by the dynamic gain coefficient to obtain the static viscosity compensation base, multiplying the static viscosity compensation base by the differential factor to generate the compensation enhancement weight, and multiplying the compensation enhancement weight by the flow rate of change to finally output the compensation enhancement product. The default value of the differential factor is 0.005.

[0122] It should be noted that dynamic clipping is based on the unrestricted output of the original compensation signal. A three-state comparator circuit performs a limiting operation (the lower limit is clamped to 500PPM to maintain the minimum opening, and the upper limit is cut off at 120,000PPM to match the full scale) to constrain the signal output range under the action of dynamic gain, so as to ensure the safe and stable operation of the control system under extreme viscosity fluctuations and avoid mechanical damage or filling accuracy failure.

[0123] Furthermore, the tri-state comparator circuit is a hardware-level limiter, consisting of three sets of voltage comparators and clamping logic gates. The input of the tri-state comparator circuit is the original compensation signal, and three output states are generated through dual threshold comparison: low-bit truncation, pass-through, and high-bit truncation. Low-bit truncation means that when the input signal is less than the lower threshold of 500ppm, the lower limit value is forcibly output. Pass-through means that when the input signal is within the limiting range, the output remains unchanged. High-bit truncation means that when the input signal exceeds the upper threshold of 120000ppm, the upper limit value is forcibly limited.

[0124] Furthermore, the three-state comparator circuit is used to map the physical limits of the mechanical actuator. 500 ppm corresponds to the minimum valve opening to ensure the basic flow rate, and 120,000 ppm corresponds to the full-scale opening to prevent overload. Essentially, it is a safety interface for the control system from virtual calculation to physical execution, which can avoid the overflow of opening commands caused by viscosity changes such as overpressure burning out the solenoid valve coil.

[0125] S4, decompose the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, and perform frequency-band collaborative filtering on the decomposed result to obtain the frequency-band filtered signal of the compensation control signal;

[0126] In this embodiment of the invention, the step of decomposing the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component includes:

[0127] Obtain the mechanical vibration frequency band and flow pulsation frequency band of the drug filling pipeline;

[0128] The pressure fluctuation signal in the compensation control signal is subjected to anti-aliasing preprocessing to generate a standardized pressure signal;

[0129] The standardized pressure signal is decomposed into a high-frequency subband coefficient set and a low-frequency subband coefficient set;

[0130] The high-frequency subband coefficient set is correlated with the mechanical vibration frequency band to obtain the high-frequency mechanical vibration subband coefficient;

[0131] The low-frequency subband coefficient set is correlated with the flow pulsation frequency band to obtain the low-frequency flow pulsation subband coefficient;

[0132] The high-frequency mechanical vibration sub-band coefficient and the low-frequency flow pulsation sub-band coefficient are reconstructed and inversely transformed to generate the high-frequency mechanical vibration component and the low-frequency flow pulsation component of the drug filling pipeline.

[0133] It should be noted that the mechanical vibration frequency band and flow pulsation frequency band of the drug filling pipeline are based on the inherent characteristics of the hydraulic system. Valve vibration signals are collected under no-load conditions, and the 3-5kHz main resonance frequency band is extracted as the mechanical vibration frequency band through fast Fourier transform. At the same time, the pipeline pulsation data is sampled by a pressure sensor array under rated flow, and the 0.5-10Hz energy concentration area is determined as the flow pulsation frequency band through power spectral density analysis.

[0134] It should be noted that the extracted pressure fluctuation signal is based on the equipment status feedback data embedded in the compensation control signal. Bandpass filtering is performed through a digital signal isolation mechanism to extract the pressure fluctuation signal.

[0135] Furthermore, the pressure fluctuation signal is the raw pressure change data collected by the sensor during the operation of the experimental equipment. It has the characteristic of continuous time and is used as the input source for subsequent frequency domain separation processing.

[0136] Furthermore, the digital signal isolation mechanism performs bandpass filtering to extract the pressure fluctuation signal. This involves performing time-domain discretization on the compensation control signal to obtain a discrete original pressure signal. Subsequently, the bandwidth of the discrete original pressure signal is limited to 0.5Hz-2kHz to cover the characteristic frequency band of the equipment pressure fluctuation. The discrete original signal is then subjected to noise reduction processing, and finally a smooth analog pressure fluctuation signal is output.

[0137] Furthermore, the essence of the digital signal isolation mechanism is to achieve frequency domain isolation between control signals and noise through hardware-level signal chains. Its passband boundary is dynamically calculated by the device's resonant frequency to ensure that the extracted signal retains complete pressure dynamic characteristics.

[0138] It should be noted that the anti-aliasing preprocessing is performed by an adaptive adjustment of the cutoff frequency through a configurable finite impulse response filter to eliminate high-frequency aliasing noise in the pressure fluctuation signal and normalize the amplitude of the noise-eliminated pressure fluctuation signal to a preset dynamic range, thereby generating a standardized pressure signal and ensuring that the signal sampling quality meets the real-time requirements of the control system.

[0139] It should be noted that the decomposition operation of the standardized pressure signal is based on the wavelet packet transform algorithm. Through multi-level filter bank analysis, the frequency domain of the standardized pressure signal is divided into a high-frequency sub-band coefficient set and a low-frequency sub-band coefficient set. The high-frequency sub-band coefficient set corresponds to the mechanical vibration frequency band, and the low-frequency sub-band coefficient set corresponds to the flow pulsation frequency band, thereby achieving frequency band isolation and compressed storage of signal energy.

[0140] Furthermore, the wavelet packet transform algorithm addresses the resolution deficiency of traditional wavelet transform in frequency band division by employing a tree-like filter bank structure. It performs low-pass and high-pass orthogonal filtering operations on the input pressure fluctuation signal layer by layer to generate a full binary subband coefficient tree. The full binary subband coefficient tree is then dynamically pruned using the optimal basis selection criterion to concentrate the signal energy in the specified frequency band.

[0141] Furthermore, the essence of the wavelet packet transform algorithm is to construct a non-uniform resolution grid in the time-frequency plane at the cost of algorithm complexity. In the low-frequency band, high frequency resolution is used to capture the slowly changing characteristics of flow pulsation, and in the high-frequency band, high time resolution is used to locate the transient impact of mechanical vibration. Compared with the global frequency analysis of Fourier transform, the wavelet packet transform algorithm adapts to the non-stationary signal processing requirements of the control system through the time-frequency localization characteristics.

[0142] Furthermore, the optimal basis selection criterion is a rule for dynamically evaluating the energy concentration of each node's frequency band. First, the energy probability distribution of all sub-band nodes is calculated. Then, based on the principle of minimizing entropy, tree structure pruning is performed to automatically select the sub-band combination that makes the signal energy most concentrated as the optimal basis.

[0143] It should be noted that the reconstruction inverse transform is based on the frequency domain data of the high-frequency mechanical vibration subband coefficient and the low-frequency flow pulsation subband coefficient. Parallel reconstruction operation is performed through the inverse wavelet packet transform algorithm to generate high-frequency mechanical vibration component and low-frequency flow pulsation component respectively. The high-frequency component is used for equipment mechanical state analysis, and the low-frequency component is used for fluid dynamic performance optimization, thus completing the separation of the physical characteristics of pressure fluctuation signal in the control system.

[0144] In this embodiment of the invention, the step of performing frequency-band collaborative filtering on the decomposed result to obtain the frequency-band filtered signal of the compensation control signal includes:

[0145] The high-frequency mechanical vibration component is subjected to time-varying narrowband filtering to generate a high-frequency mechanical filtered component.

[0146] Adaptive notch filtering is applied to the low-frequency flow pulsation component to generate a low-frequency flow filtered component;

[0147] The high-frequency mechanical filter component and the low-frequency flow filter component are combined to generate the frequency-divided filter signal of the compensation control signal.

[0148] It should be noted that time-varying narrowband filtering is based on the non-stationary characteristics of the high-frequency mechanical vibration component. It tracks the rotation frequency of the equipment spindle in real time, uses a Hall sensor to collect the instantaneous angular velocity of the spindle and converts it into the fundamental frequency, calculates the center frequency based on the inherent meshing order of the gearbox, and performs dynamic bandpass filtering through a programmable filter to generate a high-frequency mechanical filter component that retains only the characteristic energy of gear meshing.

[0149] Furthermore, the essence of time-varying narrowband filtering is a hardware-level frequency tracking circuit that suppresses spectral shifts caused by changes in operating conditions through microsecond-level coefficient reconstruction.

[0150] Furthermore, the center frequency is calculated based on the real-time acquisition of the equipment spindle angular velocity signal. Frequency conversion is performed through the gear meshing order. According to the gearbox physical configuration, the meshing coefficient is preset. The equipment spindle angular velocity signal is divided by the reference constant 2μ to convert it into the fundamental frequency. Then, the preset meshing coefficient and the fundamental frequency are multiplied by the multiplication scalar operation to generate the dynamic center frequency value.

[0151] It should be noted that the adaptive notch filter operation is based on the periodic pulsating interference caused by fluid pipeline resonance. The notch filter is driven by an acoustic model to achieve frequency self-tracking. The resonant frequency is calculated based on the sound velocity and pipe length, and a zero-pole pair digital filter is constructed. When the sensor detects that the fluid pressure gradient is less than the threshold, the zero position is updated to generate a low-frequency flow filter component that eliminates the influence of pipeline standing waves.

[0152] In this embodiment of the invention, the step of fusing the high-frequency mechanical filter component and the low-frequency flow filter component to generate the frequency-divided filter signal of the compensation control signal includes:

[0153] Based on the covariance of the high-frequency mechanical filter component and the low-frequency flow filter component, the high-frequency state covariance matrix and the low-frequency observation covariance matrix of the compensation control signal are constructed respectively.

[0154] Weights are assigned to the high-frequency mechanical filter component and the low-frequency flow filter component;

[0155] Based on the weight allocation result, the high-frequency state covariance matrix and the low-frequency observation covariance matrix are weighted and fused to generate the frequency-divided filter signal of the compensation control signal.

[0156] It should be noted that the high-frequency subband coefficient set is a set of mathematical parameters generated after wavelet packet transform decomposition of the normalized pressure signal. It is generated by performing multi-level high-pass filtering on the 3-5kHz mechanical vibration frequency band through a tree-like filter bank. Each coefficient corresponds to the high-frequency energy intensity within the time-frequency window, which is used to quantify the dynamic characteristics of instantaneous mechanical impact. Its amplitude reflects the impact force at the moment of gear meshing, and its phase distribution exposes the bearing wear location.

[0157] It should be noted that the low-frequency subband coefficient set is a group of parameters output by wavelet packet transform in the 0.5-10 Hz flow pulsation frequency band. It is obtained by decomposing the signal layer by layer by an orthogonal low-pass filter bank. The coefficient values ​​characterize the gradual component of fluid pressure fluctuation and are used to reflect the mass conservation characteristics of the coded fluid network. Its energy conservation characteristics correspond to the mass continuity of the liquid in the pipeline, and the coefficient gradient distribution maps the flow balance state of the branch.

[0158] It should be noted that the weight allocation is based on the ratio of the total energy of the high-frequency component of mechanical vibration to the total energy of the low-frequency component of fluid pulsation, thus obtaining the high-frequency fusion weight and low-frequency fusion weight of the compensation control signal.

[0159] It should be noted that, in constructing the high-frequency state covariance matrix and the low-frequency observation covariance matrix of the compensation control signal respectively, the high-frequency state covariance matrix characterizing the distribution of mechanical vibration energy is generated based on the noise covariance of the process superposition of the high-frequency mechanical vibration component through the product of the state transition matrix and the autocorrelation matrix of the high-frequency component.

[0160] The low-frequency flow pulsation component is calculated by weighting the cross-correlation matrix of the low-frequency component and the observation noise covariance based on the observation matrix derived from the fluid continuity equation, thus forming a low-frequency observation covariance matrix that reflects the statistical characteristics of fluid pressure fluctuations.

[0161] Furthermore, the state transition matrix is ​​used to describe the mathematical relationship of the dynamic evolution law of the state vector in a discrete-time control system. Essentially, it is a delay characteristic of the relationship between valve mass and spring. In the control of liquid filling valve, it reflects the transmission effect of the mechanical vibration state from the current mechanical vibration state to the mechanical vibration state at the next moment. It is realized by discretization of the product of the inverse of the mass matrix and the stiffness matrix and is used to predict the future vibration mode shift.

[0162] Furthermore, the high-frequency component autocorrelation matrix is ​​a statistical representation of the vibration energy distribution in the frequency domain. It is generated by performing autocorrelation operations after converting the time-domain vibration characteristics into the frequency-domain power spectrum through Fourier transform. The diagonal elements of this matrix reflect the energy concentration at each frequency point, while the off-diagonal elements reveal the frequency coupling characteristics. It is used to calibrate the confidence level of vibration modal analysis.

[0163] Furthermore, the process noise covariance represents the output uncertainty of the valve drive mechanism, which is essentially a random deviation in torque output caused by fluctuations in the current of the electromagnet coil.

[0164] Furthermore, the fluid continuity equation is a dynamic simulation equation of a fluid network based on the law of conservation of mass. Mathematically, it is expressed as a differential constraint of "inflow mass = outflow mass + accumulation". Essentially, it ensures the flow balance between the filling branch and the return branch when the liquid is transported in the pipeline.

[0165] Furthermore, the low-frequency component cross-correlation matrix represents the mathematical expression of the correlation between flow pulsation signals at different spatial locations. Essentially, it is a spatiotemporal coupling intensity spectrum of pipeline pressure disturbance transmission, generated by calculating an array of cross-correlation coefficients with zero time offset.

[0166] S5, adjust the opening degree of the liquid filling valve according to the frequency division filter signal.

[0167] In this embodiment of the invention, adjusting the opening degree of the liquid filling valve according to the frequency division filtering signal includes:

[0168] Based on the frequency division filtering signal, the theoretical opening value of the liquid filling valve is generated through a preset flow-opening conversion rule;

[0169] The real-time deviation of the theoretical opening value is statistically analyzed, and the statistical results are integrated into the opening adjustment amount of the liquid filling valve.

[0170] The opening degree of the medicine filling valve is adjusted based on the opening degree adjustment amount.

[0171] It should be noted that the preset flow-opening conversion rule is based on the real-time flow detection value, combined with three parameters determined by calibration experiments: the quadratic term coefficient, the linear term coefficient, and the zero-point offset. The theoretical valve opening value is calculated by summing these parameters. The quadratic term coefficient ranges from 0.002 to 0.005 and is used to characterize the nonlinear saturation effect in the high flow range. The zero-point offset is used to compensate for the zero-point drift of the opening caused by mechanical wear. This rule is burned into the programmable controller's storage area in the form of a pre-compiled lookup table.

[0172] Furthermore, the linear term is a preset scaling factor used to reflect the strength of the linear relationship between flow deviation and valve opening adjustment. The default value is 0.5, which means that for every unit increase in flow deviation, the valve opening needs to increase linearly by 0.5% to compensate for the deviation.

[0173] Furthermore, the zero-point offset is a constant parameter that represents the reference opening compensation value of the valve under zero-deviation conditions, with a default value of 5%.

[0174] It should be noted that the real-time deviation of the theoretical opening value is statistically analyzed, and the statistical results are integrated into the opening adjustment amount of the liquid filling valve. The sliding window integral strategy is adopted. The arithmetic mean deviation value is accumulated within a time window of 50 milliseconds, and the deviation differential term of the current sampling point is multiplied by a gain coefficient of 0.1 to finally generate the opening adjustment command. The opening of the liquid filling valve is controlled based on the opening adjustment command.

[0175] like Figure 2 The diagram shown is a functional block diagram of a liquid filling control system for suppressing flow pulsation provided in an embodiment of the present invention.

[0176] The drug liquid circulation filling control system 100 for suppressing flow pulsation described in this invention can be installed in an electronic device. Depending on the functions implemented, the drug liquid circulation filling control system 100 may include a signal dynamic acquisition module 101, a deviation gain analysis module 102, a compensation signal generation module 103, a frequency division collaborative filtering module 104, and a valve intelligent adjustment module 105. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0177] In this embodiment, the functions of each module / unit are as follows:

[0178] The signal dynamic capture module 101 is used to acquire the original flow signal and viscosity data of the liquid medicine in the liquid medicine filling pipeline;

[0179] The deviation gain analysis module 102 is used to calculate the baseline deviation value of the drug solution viscosity data, perform gain effect analysis on the drug solution viscosity data based on the baseline deviation value, and obtain the dynamic gain coefficient of the drug solution viscosity data.

[0180] The compensation signal generation module 103 is used to apply the dynamic gain coefficient to the original flow signal to obtain a compensation control signal;

[0181] The frequency division collaborative filtering module 104 is used to decompose the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, and to perform frequency division collaborative filtering on the decomposed result to obtain the frequency division filtered signal of the compensation control signal.

[0182] The valve intelligent adjustment module 105 is used to adjust the opening degree of the liquid filling valve according to the frequency division filtering signal.

[0183] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0184] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0185] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0186] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0187] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0188] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for controlling the circulation and filling of pharmaceutical solutions to suppress flow pulsation, characterized in that, The method includes: S1, acquire the original flow signal and viscosity data of the liquid medicine in the liquid medicine filling pipeline; S2, calculate the baseline deviation value of the drug solution viscosity data, perform gain effect analysis on the drug solution viscosity data based on the baseline deviation value, and obtain the dynamic gain coefficient of the drug solution viscosity data; S3, apply the dynamic gain coefficient to the original flow signal to obtain a compensation control signal; S4, decompose the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, and perform frequency-band collaborative filtering on the decomposed result to obtain the frequency-band filtered signal of the compensation control signal; S5, adjust the opening degree of the liquid filling valve according to the frequency division filter signal.

2. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 1, characterized in that, The acquisition of the original flow signal and viscosity data of the liquid medicine in the filling pipeline includes: The flow signal of the medicine liquid is obtained by the flow sensor in the medicine liquid filling pipeline, and the flow signal of the medicine liquid is converted into digital simulation to obtain the original flow signal of the medicine liquid in the medicine liquid filling pipeline. Based on the viscosity detection device in the drug filling pipeline, real-time viscosity data sampling values ​​are extracted; The real-time viscosity data sampling values ​​are subjected to data standardization processing to obtain the viscosity data of the drug solution in the drug solution filling pipeline.

3. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 1, characterized in that, The benchmark deviation value for calculating the viscosity data of the drug solution includes: Calculate the difference between the viscosity data of the liquid medicine and the preset reference viscosity to obtain the reference deviation item of the liquid medicine in the liquid medicine filling pipeline; The ratio of the reference deviation term to the reference viscosity is used as the viscosity deviation term of the drug solution in the drug solution filling pipeline; The viscosity deviation term is scaled to obtain the baseline deviation value of the drug solution viscosity data.

4. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 3, characterized in that, The gain effect analysis of the drug solution viscosity data based on the benchmark deviation value to obtain the dynamic gain coefficient of the drug solution viscosity data includes: The reference deviation value is input into the nonlinear gain function to obtain the original gain coefficient, wherein the mathematical expression of the nonlinear gain function is as follows: ； In the formula, This is the original gain coefficient. Basic gain coefficient, Gain adjustment factor It is a non-linear exponent. This is the baseline deviation value; The original gain coefficient is subjected to saturation limiting processing to obtain the dynamic gain coefficient.

5. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 4, characterized in that, The step of applying the dynamic gain coefficient to the original flow signal to obtain a compensation control signal includes: The original flow signal and the dynamic gain coefficient are time-aligned to obtain a time-series gain flow sequence. The time-series gain flow rate sequence and the original flow rate signal are combined to generate the original compensation signal for the drug filling pipeline; The original compensation signal is dynamically clipped to obtain the compensation control signal for the drug filling pipeline.

6. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 1, characterized in that, The step of decomposing the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component includes: Obtain the mechanical vibration frequency band and flow pulsation frequency band of the drug filling pipeline; The pressure fluctuation signal in the compensation control signal is subjected to anti-aliasing preprocessing to generate a standardized pressure signal; The standardized pressure signal is decomposed into a high-frequency subband coefficient set and a low-frequency subband coefficient set; The high-frequency subband coefficient set is correlated with the mechanical vibration frequency band to obtain the high-frequency mechanical vibration subband coefficient; The low-frequency subband coefficient set is correlated with the flow pulsation frequency band to obtain the low-frequency flow pulsation subband coefficient; The high-frequency mechanical vibration sub-band coefficient and the low-frequency flow pulsation sub-band coefficient are reconstructed and inversely transformed to generate the high-frequency mechanical vibration component and the low-frequency flow pulsation component of the drug filling pipeline.

7. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 1, characterized in that, The process involves performing frequency-band collaborative filtering on the decomposed result to obtain the frequency-divided filtered signal of the compensation control signal, including: The high-frequency mechanical vibration component is subjected to time-varying narrowband filtering to generate a high-frequency mechanical filtered component. Adaptive notch filtering is applied to the low-frequency flow pulsation component to generate a low-frequency flow filtered component; The high-frequency mechanical filter component and the low-frequency flow filter component are combined to generate the frequency-divided filter signal of the compensation control signal.

8. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 7, characterized in that, The process of fusing the high-frequency mechanical filter component and the low-frequency flow filter component to generate the frequency-divided filter signal for the compensation control signal includes: Based on the covariance of the high-frequency mechanical filter component and the low-frequency flow filter component, the high-frequency state covariance matrix and the low-frequency observation covariance matrix of the compensation control signal are constructed respectively. Weights are assigned to the high-frequency mechanical filter component and the low-frequency flow filter component; Based on the weight allocation result, the high-frequency state covariance matrix and the low-frequency observation covariance matrix are weighted and fused to generate the frequency-divided filter signal of the compensation control signal.

9. The method for controlling the circulation and filling of medicine liquid to suppress flow pulsation as described in claim 1, characterized in that, The step of adjusting the opening degree of the liquid filling valve according to the frequency division filter signal includes: Based on the frequency division filtering signal, the theoretical opening value of the liquid filling valve is generated through a preset flow-opening conversion rule; The real-time deviation of the theoretical opening value is statistically analyzed, and the statistical results are integrated into the opening adjustment amount of the liquid filling valve. The opening degree of the medicine filling valve is adjusted based on the opening degree adjustment amount.

10. A liquid medicine circulation filling control system for suppressing flow pulsation, characterized in that, The system includes: The signal dynamic capture module is used to acquire the original flow signal and viscosity data of the liquid medicine in the liquid medicine filling pipeline; The deviation gain analysis module is used to calculate the baseline deviation value of the drug solution viscosity data, perform gain effect analysis on the drug solution viscosity data based on the baseline deviation value, and obtain the dynamic gain coefficient of the drug solution viscosity data. The compensation signal generation module is used to apply the dynamic gain coefficient to the original flow signal to obtain a compensation control signal; The frequency division collaborative filtering module is used to decompose the pressure fluctuation signal in the compensation control signal into a high-frequency mechanical vibration component and a low-frequency flow pulsation component, and to perform frequency division collaborative filtering on the decomposed result to obtain the frequency division filtered signal of the compensation control signal. The valve intelligent adjustment module is used to adjust the opening degree of the liquid filling valve according to the frequency division filtering signal.

Images