Power supply optimization method and system for high-efficiency and energy-saving integrated cell disruptor

Abstract

The present invention relates to the field of automation control, and discloses a high-efficiency and energy-saving integrated cell crusher power supply optimization method and system, including: obtaining the sample processing cavity corresponding to the target cell crusher and collecting its real-time load spectrum, analyzing the power demand curve under different crushing intensities, building a collaborative scheduling network, analyzing the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply, extracting the current ripple coefficient and the voltage fluctuation threshold, calculating the energy coupling matching degree, simulating the power consumption distribution map under the variable load impact working condition based on the matching degree, building an adaptive logic rule, integrating the adaptive logic rule with the synchronous compensation mechanism, generating a dynamic control strategy, extracting the execution energy efficiency parameters and calculating the energy efficiency attenuation value, dynamically adjusting the duty cycle modulation parameters, evaluating the power supply working state, and formulating a power supply optimization plan. The present invention can improve the power supply optimization efficiency of the cell crusher.

Description

Technical Field

[0001] The invention relates to a high-efficiency and energy-saving integrated cell disruptor power supply optimization method and system, belonging to the field of automatic control. Background Art

[0002] In the field of biotechnology and life sciences, cell disruption technology is a key step in obtaining cell contents, protein extraction, gene analysis and other experiments. With the continuous increase in scientific research needs, cell disruptors, as the core equipment for realizing this technology, have a direct impact on the accuracy and reliability of experimental results.

[0003] At present, traditional integrated cell disruptors still have many shortcomings in power management and energy consumption control. On the one hand, traditional power supply designs often adopt a fixed power output mode, which cannot be dynamically adjusted according to the actual load requirements in the cell disruption process, resulting in serious energy waste and high equipment operating costs. On the other hand, the stability and reliability of the power supply system are insufficient, and equipment failures may easily occur due to voltage fluctuations or current overloads. Therefore, an efficient and energy-saving integrated cell disruptor power supply optimization method is needed to improve the power optimization efficiency of the cell disruptor. Summary of the invention

[0004] The present invention provides a high-efficiency and energy-saving integrated cell disruptor power optimization method and system, the main purpose of which is to improve the power optimization efficiency of the cell disruptor.

[0005] To achieve the above object, the present invention provides a high-efficiency and energy-saving integrated cell disruptor power supply optimization method, comprising: Acquire a sample processing cavity corresponding to a target cell disruptor, and collect a real-time load spectrum corresponding to the sample processing cavity, analyze the power demand curve of the sample processing cavity under different crushing intensities based on the real-time load spectrum, and construct a collaborative scheduling network corresponding to the target cell disruptor according to the power demand curve; Analyze the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the cooperative scheduling network, extract the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristics, and calculate the energy coupling matching degree of the target cell disruptor when powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold; Based on the energy coupling matching degree, the power consumption distribution map of the sample processing chamber under the variable load impact condition is simulated, and the adaptive logic rules corresponding to the target cell disruptor are constructed according to the power consumption distribution map; Integrate the adaptive logic rules with the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, extract the execution energy efficiency parameters in the control strategy, and calculate the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameters; Based on the energy efficiency attenuation value, the duty cycle modulation parameters corresponding to the target cell disruptor are dynamically adjusted; based on the duty cycle modulation parameters, the power supply working state corresponding to the target cell disruptor is evaluated, and the energy efficiency evaluation dimension corresponding to the power supply working state is analyzed; based on the energy efficiency evaluation dimension, a power supply optimization plan corresponding to the target cell disruptor is formulated.

[0006] Optionally, analyzing the power demand curve of the sample processing chamber under different crushing intensities based on the real-time load spectrum includes: Performing multi-scale wavelet decomposition on the real-time load spectrum to obtain multi-scale spectrum components; Extracting component frequency points in the multi-scale spectral components; Query the component amplitude corresponding to the component frequency point; Based on the component amplitudes, determining a crushing intensity interval corresponding to the sample processing cavity; Extracting the power demand points in the crushing intensity interval; Based on the power demand point, the power demand curve of the sample processing chamber under different crushing intensities is analyzed.

[0007] Optionally, constructing a collaborative scheduling network corresponding to the target cell disruptor according to the power demand curve includes: Extracting key characteristic points from the electric energy demand curve; Based on the key characteristic points, dividing the dynamic load interval corresponding to the electric energy demand curve; quantifying the energy demand of the dynamic load interval to obtain an interval energy demand value; Based on the interval energy demand value, analyzing the power allocation ratio corresponding to the target cell disruptor; Based on the power allocation ratio, analyzing the degree of coordinated scheduling corresponding to the target cell disruptor; Based on the collaborative scheduling degree, a collaborative scheduling network corresponding to the target cell disruptor is constructed.

[0008] Optionally, the analyzing the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the cooperative scheduling network includes: Extracting an output signal waveform in the collaborative scheduling network; Based on the output signal waveform, determining the original phase data corresponding to the high-frequency pulse power supply and the DC regulated power supply in the coordinated scheduling network; Constructing a phase difference distribution diagram corresponding to the original phase data; Extracting phase fluctuation features in the phase difference distribution diagram; Based on the phase fluctuation characteristics, the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network are analyzed.

[0009] Optionally, the calculating the energy coupling matching degree of the target cell disruptor when powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold comprises: The energy coupling matching degree of the target cell disruptor when powered in parallel is calculated using the following formula: ; in, represents the energy coupling matching degree, and They represent the start time and end time of calculating the energy coupling matching degree, respectively. Indicates at time The comprehensive evaluation function of the current ripple coefficient and the voltage fluctuation threshold at the moment, Indicates the number of power modules in the parallel power supply system. Indicates the quantity index of the power module. Indicates The capacity factor of each power module, Represents the stability index of the parallel power supply system, Indicates the interference factor index of the parallel power supply system.

[0010] Optionally, simulating the power consumption distribution spectrum of the sample processing chamber under a variable load impact condition based on the energy coupling matching degree includes: Extracting key parameters in the energy coupling matching degree; Based on the key parameters, construct a dynamic load framework corresponding to the sample processing chamber; Based on the dynamic load framework, collecting historical power consumption data corresponding to the sample processing cavity; Analyzing the power consumption change pattern corresponding to the historical power consumption data; Based on the power consumption variation pattern, a power consumption distribution spectrum of the sample processing chamber under a variable load impact condition is simulated.

[0011] Optionally, the integration of the adaptive logic rule and a preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor includes: Extracting key trigger conditions in the adaptive logic rules; Clarify the compensation execution method corresponding to the preset synchronous compensation mechanism; Based on the key trigger conditions and the compensation execution mode, constructing a working condition database corresponding to the target cell disruptor; Filtering typical operating condition data in the operating condition database; Based on the typical operating condition data, a dynamic control strategy of the composite power supply system corresponding to the target cell disruptor is generated.

[0012] Optionally, the calculating the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameter includes: The energy efficiency attenuation value corresponding to the target cell disruptor is calculated using the following formula: ; in, represents the energy efficiency attenuation value corresponding to the target cell disruptor, represents the total number of the execution energy efficiency parameters, represents the quantity index of the execution energy efficiency parameter, represents the total number of working modes corresponding to the target cell disruptor, represents the quantitative index of the working mode, Indicated in The energy efficiency parameters and The energy efficiency value corresponding to each working mode is: Indicates that among all execution energy efficiency parameters, the corresponding The average energy efficiency of each working mode.

[0013] Optionally, dynamically adjusting a duty cycle modulation parameter corresponding to the target cell disruptor based on the energy efficiency attenuation value includes: Extracting key attenuation factors from the energy efficiency attenuation value; Analyze the attenuation fluctuation period corresponding to the key attenuation factor; Dividing the energy efficiency stages corresponding to the attenuation fluctuation period; Counting the execution energy efficiency parameters in the energy efficiency stage; Based on the execution energy efficiency parameter, the duty cycle modulation parameter corresponding to the target cell disruptor is dynamically adjusted.

[0014] In order to solve the above problems, the present invention also provides a high-efficiency and energy-saving integrated cell disruptor power optimization system, the system comprising: A scheduling network construction module is used to obtain a sample processing chamber corresponding to a target cell disruptor, collect a real-time load spectrum corresponding to the sample processing chamber, analyze an electric energy demand curve of the sample processing chamber under different crushing intensities based on the real-time load spectrum, and construct a collaborative scheduling network corresponding to the target cell disruptor according to the electric energy demand curve; A matching degree calculation module is used to analyze the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the cooperative scheduling network, extract the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristics, and calculate the energy coupling matching degree of the target cell disruptor when it is powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold; A rule construction module, for simulating the power consumption distribution map of the sample processing chamber under the variable load impact condition based on the energy coupling matching degree, and constructing the adaptive logic rule corresponding to the target cell disruptor according to the power consumption distribution map; An attenuation value calculation module is used to integrate the adaptive logic rules and the preset synchronous compensation mechanism, generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, extract the execution energy efficiency parameters in the control strategy, and calculate the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameters; A program formulation module is used to dynamically adjust the duty cycle modulation parameters corresponding to the target cell disruptor based on the energy efficiency attenuation value, evaluate the power supply working state corresponding to the target cell disruptor based on the duty cycle modulation parameters, analyze the energy efficiency evaluation dimension corresponding to the power supply working state, and formulate a power supply optimization program corresponding to the target cell disruptor based on the energy efficiency evaluation dimension.

[0015] Compared with the problems described in the background technology, the present invention obtains the sample processing chamber corresponding to the target cell disruptor and collects the real-time load spectrum corresponding to the sample processing chamber. It can accurately identify the changes in power demand under different crushing intensities and realize dynamic matching of power supply output, thereby significantly improving energy utilization efficiency. At the same time, the collection of real-time load spectrum provides data support for the equipment operation status, which helps to optimize the crushing effect and extend the service life of the equipment. The present invention analyzes the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network, and can accurately control their working rhythm under different working conditions, avoid power supply disorder caused by phase deviation, improve power supply coordination efficiency, ensure the stable operation of the target cell disruptor under complex loads, reduce equipment failures, and improve energy utilization efficiency. Furthermore, based on the energy coupling matching degree, the present invention simulates the power consumption distribution spectrum of the sample processing chamber under variable load impact conditions, and can intuitively present the power consumption changes under different working conditions. Through this map, high power consumption areas and time periods can be accurately located, helping to optimize the cavity design and power supply configuration, and power consumption anomalies can be predicted in advance, providing a strong basis for energy saving and stable operation of the equipment, reducing operating costs and potential failure risks. Furthermore, the present invention integrates the adaptive logic rules and the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell crusher, which can achieve efficient switching and energy compensation of power supply modes, significantly improve the response speed and stability of the system, accurately match power output with load requirements, reduce energy loss and extend the service life of the equipment. Finally, based on the energy efficiency attenuation value, the present invention dynamically adjusts the duty cycle modulation parameters corresponding to the target cell crusher, which can optimize the matching degree of power output and load requirements in real time, significantly improve the energy utilization efficiency of the equipment, and effectively reduce energy loss and extend the service life of key components of the equipment. Therefore, the power optimization method and system of an efficient and energy-saving integrated cell crusher provided in an embodiment of the present invention can improve the power optimization efficiency of the cell crusher. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a method for optimizing power supply of an energy-efficient integrated cell disruptor provided by one embodiment of the present invention; Figure 2 A schematic diagram of a module of a high-efficiency and energy-saving integrated cell disruptor power optimization system provided by one embodiment of the present invention.

[0017] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0018] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0019] The embodiment of the present application provides a method for optimizing the power supply of an efficient and energy-saving integrated cell disruptor. The execution subject of the method for optimizing the power supply of an efficient and energy-saving integrated cell disruptor includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for optimizing the power supply of an efficient and energy-saving integrated cell disruptor can be executed by software or hardware installed in 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, etc.

[0020] Embodiment 1: Reference Figure 1 As shown, it is a schematic diagram of a flow chart of a high-efficiency and energy-saving integrated cell disruptor power supply optimization method provided by an embodiment of the present invention. In this embodiment, the high-efficiency and energy-saving integrated cell disruptor power supply optimization method includes: S1. Obtain a sample processing cavity corresponding to a target cell disruptor, and collect a real-time load spectrum corresponding to the sample processing cavity. Based on the real-time load spectrum, analyze the power demand curve of the sample processing cavity under different crushing intensities. According to the power demand curve, construct a collaborative scheduling network corresponding to the target cell disruptor.

[0021] The present invention obtains the sample processing cavity corresponding to the target cell disruptor and collects the real-time load spectrum corresponding to the sample processing cavity. It can accurately identify the changes in power demand under different crushing intensities and realize dynamic matching of power supply output, thereby significantly improving energy utilization efficiency. At the same time, the collection of real-time load spectrum provides data support for the operating status of the equipment, which helps to optimize the crushing effect and extend the service life of the equipment.

[0022] Among them, the target cell disruptor refers to an integrated device for biological sample disruption, which integrates ultrasonic, mechanical or chemical disruption functions; the sample processing chamber refers to the core component of the cell disruptor for accommodating biological samples and performing disruption operations, which is usually made of corrosion-resistant materials; the real-time load spectrum refers to the dynamic power demand characteristics generated by changes in factors such as sample characteristics and disruption intensity during the operation of the sample processing chamber, and the load state of the equipment operation can be reflected through spectrum analysis. Optionally, the acquisition of the sample processing chamber corresponding to the target cell disruptor can be achieved by sensor scanning, such as: using a laser scanner or a structured light scanner to obtain the geometric data of the cavity, combining a point cloud processing algorithm (such as an ICP algorithm) to generate a sample processing cavity; the acquisition of the real-time load spectrum corresponding to the sample processing cavity can be achieved by a spectrum analyzer, such as: using a high-performance spectrum analyzer (such as Keysight N9020A) to directly acquire the real-time load spectrum of the cavity when it is working.

[0023] Furthermore, based on the real-time load spectrum, the present invention analyzes the power demand curve of the sample processing chamber under different crushing intensities, can accurately understand the energy consumption characteristics of the cell disruptor under different working conditions, provide accurate data basis for power supply regulation, and optimize the power supply in a targeted manner, avoiding energy waste caused by fixed power output, achieving high efficiency and energy saving, and improving the overall operating efficiency and economic benefits of the cell disruptor.

[0024] Among them, the power demand curve refers to a curve obtained by fitting and analyzing the power demand points, which reflects the changing trend of the power demand of the sample processing chamber under different crushing intensities. It intuitively shows the change of the power required for the sample processing chamber with the change of crushing intensity, and provides a key energy consumption analysis basis for power supply optimization.

[0025] As an embodiment of the present invention, the method of analyzing the power demand curve of the sample processing cavity under different crushing intensities based on the real-time load spectrum includes: performing multi-scale wavelet decomposition on the real-time load spectrum to obtain multi-scale spectrum components; extracting component frequency points in the multi-scale spectrum components; querying component amplitudes corresponding to the component frequency points; determining the crushing intensity interval corresponding to the sample processing cavity based on the component amplitudes; extracting power demand points in the crushing intensity interval; and analyzing the power demand curve of the sample processing cavity under different crushing intensities based on the power demand points.

[0026] Among them, the multi-scale spectral component refers to the spectral components of different frequency ranges and resolutions obtained after multi-scale wavelet decomposition of the real-time load spectrum. Wavelet decomposition can analyze signals at different scales. The multi-scale spectral component contains load spectrum information from low frequency to high frequency with different degrees of precision, which helps to fully understand the load characteristics of the sample processing cavity when it is working; the component frequency point refers to the point representing different frequency positions in the multi-scale spectral component. These points are the basic frequency identifiers that constitute the spectrum. Through them, the positions of different frequency components in the load spectrum can be determined, thereby analyzing the working state of the sample processing cavity at different frequencies; the component amplitude refers to the amplitude value corresponding to the component frequency point, and the amplitude reflects the frequency The relative intensity of the component in the entire load spectrum, that is, the proportion of a signal of a certain frequency in the workload of the sample processing chamber, is a key indicator for measuring the influence of different frequency components on the overall load; the crushing intensity interval refers to different ranges divided according to the component amplitude and the preset crushing intensity standard, and different amplitude ranges correspond to different working intensities of the sample processing chamber, so as to determine the crushing intensity of the sample processing chamber under different working conditions; the power demand point refers to the key data point within the crushing intensity interval that can reflect the power consumption of the sample processing chamber under the crushing intensity. These points are associated with specific crushing intensities and corresponding power-related information, and are the basic data for constructing the power demand curve.

[0027] Further, the multi-scale wavelet decomposition of the real-time load spectrum can be implemented by the Mallat algorithm, such as: decomposing the spectrum signal into high-frequency detail components and low-frequency approximate components to obtain multi-scale spectrum components; the extraction of component frequency points in the multi-scale spectrum components can be implemented by a peak detection algorithm, such as: a local maximum detection algorithm to extract frequency points where energy is concentrated in the spectrum components; the query of the component amplitude corresponding to the component frequency point can be implemented by a spectrum amplitude query algorithm, such as: directly extracting the amplitude of the corresponding frequency point from the wavelet decomposition result; the determination of the crushing intensity interval corresponding to the sample processing cavity can be implemented by a clustering analysis algorithm, such as: K-means, DBSCAN and other algorithms, dividing the crushing intensity interval according to the component amplitude; the extraction of the power demand point in the crushing intensity interval can be implemented by the least squares method, such as: fitting the relationship between amplitude and power consumption, thereby extracting the power demand point; the analysis of the power demand curve of the sample processing cavity under different crushing intensities can be implemented by a curve fitting algorithm, such as: polynomial fitting, spline interpolation and other algorithms.

[0028] According to the electric energy demand curve, the present invention constructs a collaborative scheduling network corresponding to the target cell disruptor, which can achieve precise collaborative control of the high-frequency pulse power supply and the DC regulated power supply, optimize the energy distribution efficiency, and significantly reduce energy loss and improve the operation stability of the equipment by dynamically matching the power supply output with the load demand.

[0029] Among them, the collaborative scheduling network refers to a network that takes power supplies as nodes, the collaborative working relationship between power supplies and the power distribution path as edges, and is constructed in combination with the degree of collaborative scheduling. It intuitively demonstrates how the power supplies work together under different load conditions of the target cell disruptor to achieve stable power supply for the cell disruption process, and is the core architecture for achieving efficient power management.

[0030] As an embodiment of the present invention, constructing a collaborative scheduling network corresponding to the target cell disruptor according to the electric energy demand curve includes: extracting key feature points in the electric energy demand curve; dividing the dynamic load interval corresponding to the electric energy demand curve based on the key feature points; quantifying the energy demand of the dynamic load interval to obtain an interval energy demand value; analyzing the power allocation ratio corresponding to the target cell disruptor based on the interval energy demand value; analyzing the collaborative scheduling degree corresponding to the target cell disruptor based on the power allocation ratio; and constructing a collaborative scheduling network corresponding to the target cell disruptor based on the collaborative scheduling degree.

[0031] Among them, the key characteristic points refer to points with special significance and representativeness in the power demand curve, such as the peak point, valley point, inflection point, etc. of the curve, which can highlight the changing trend and key state of the power demand curve; the dynamic load interval refers to the different stage intervals obtained by dividing the power demand curve with the key characteristic points as the boundary, and the load changes in each interval have certain similarities and continuity, reflecting the load conditions of the target cell crusher under different working conditions, and are the basic units for further analyzing energy demand and power allocation; the interval energy demand value refers to the value obtained by quantitatively calculating the power demand in the dynamic load interval, reflecting the total amount of energy required for the target cell crusher to complete the work in this specific load interval, and is a key indicator for measuring load energy consumption; the power allocation ratio refers to the interval energy demand value and the characteristics of different power supplies, and this ratio determines the power supply tasks undertaken by different power supplies during the operation of the cell crusher; the degree of coordinated scheduling refers to a comprehensive evaluation indicator, which measures the degree of coordination of the power supplies in the target cell crusher based on the power allocation ratio, taking into account factors such as the smoothness of switching between different power supplies, the response speed, and the overall power supply efficiency.

[0032] Furthermore, the extraction of key characteristic points in the electric energy demand curve can be achieved through an extreme value search method, such as: traversing the electric energy demand curve data, and finding the maximum and minimum points in the curve as key characteristic points; the division of the dynamic load interval corresponding to the electric energy demand curve can be achieved through a characteristic point division method, such as: using the extracted key characteristic points as the dividing boundary, dividing the electric energy demand curve into multiple intervals, each interval corresponding to a dynamic load interval; the quantification of energy demand for the dynamic load interval can be achieved through the Origin tool, such as: using the Origin tool to directly perform integral operations on the selected dynamic load interval data to quickly obtain the interval energy demand value; the analysis of the power distribution ratio corresponding to the target cell disruptor can be achieved through a linear programming method Implementation, such as: according to the interval energy demand value, the power upper limit of different power supplies and the efficiency of the power supply and other constraints, a linear programming model is established to solve the power that different power supplies should allocate in each dynamic load interval, and then the power allocation ratio is obtained; the analysis of the degree of coordinated scheduling corresponding to the target cell disruptor based on the power allocation ratio can be achieved through the hierarchical analysis method, such as: first using AHP to determine the weight of each evaluation index, and then combining the fuzzy comprehensive evaluation method to calculate the degree of coordinated scheduling; the construction of the coordinated scheduling network corresponding to the target cell disruptor can be achieved through the Dijkstra algorithm, such as: used to find the optimal power transmission path in the constructed coordinated scheduling network, ensure that the power supplies can work efficiently and collaboratively under different load conditions, and optimize the network structure to improve the overall power supply efficiency.

[0033] S2. Analyze the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network, extract the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristics, and calculate the energy coupling matching degree of the target cell disruptor when powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold.

[0034] By analyzing the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network, the present invention can accurately control their working rhythm under different working conditions, avoid power supply disorder caused by phase deviation, improve power supply coordination efficiency, ensure the stable operation of the target cell disruptor under complex loads, reduce equipment failures, and improve energy utilization efficiency.

[0035] Among them, the high-frequency pulse power supply refers to a power supply device that can output high-frequency pulse signals, which outputs high voltage or high current pulses in a very short time, and the pulse frequency is usually tens of kilohertz or even higher. It has the characteristics of narrow pulse width and high peak power, and can be used in occasions requiring instantaneous high-energy output, such as providing instantaneous high-energy impact for cell disruption in a cell disruptor to achieve functions such as the release of cell contents; the DC regulated power supply refers to a power supply device that converts AC power into stable DC power output, which can provide a stable DC voltage for the load, and the output voltage does not fluctuate significantly with time and load changes, and the ripple factor is small, which can ensure that the electrical equipment works under a stable voltage. In the cell disruptor, it can provide stable power support for some components that require stable DC power supply, such as control circuits, sensors, etc.; the phase response characteristic refers to the phase matching performance of the high-frequency pulse power supply and the DC regulated power supply when working together, including the stability of the phase difference, the response speed and the dynamic adjustment capability.

[0036] As an embodiment of the present invention, the analysis of the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network includes: extracting the output signal waveform in the collaborative scheduling network; based on the output signal waveform, determining the original phase data corresponding to the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network; constructing a phase difference distribution diagram corresponding to the original phase data; extracting the phase fluctuation characteristics in the phase difference distribution diagram; based on the phase fluctuation characteristics, analyzing the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network.

[0037] Among them, the output signal waveform refers to the intuitive presentation of the change of the electrical signal over time generated by the joint action of the high-frequency pulse power supply and the DC regulated power supply when the coordinated scheduling network is working. It comprehensively reflects the dynamic change of the voltage and current over time after the superposition of the two power supplies. By observing the waveform, we can preliminarily understand the characteristics of the electrical signal during the coordinated work; the original phase data refers to the initial data of the phase of the high-frequency pulse power supply and the DC regulated power supply obtained by analyzing the output signal waveform. These data represent the phase values ​​of the two power supplies at different times, which is the basis for the subsequent analysis of the phase relationship and directly reflects the phase state of the power supply during the working process; the phase The difference distribution diagram refers to a graph obtained by calculating the phase difference between the high-frequency pulse power supply and the DC regulated power supply based on the original phase data, and then visually displaying these phase differences in chronological order or other relevant dimensions. It can clearly present the distribution of the phase difference between the two power supplies at different time points or under different working conditions, and facilitate the rapid positioning of the changing trend and law of the phase difference; the phase fluctuation characteristics refer to the key information extracted from the phase difference distribution diagram that can characterize the characteristics of the phase difference change, such as the fluctuation range, fluctuation frequency, peak and valley values ​​of the phase difference, etc. These characteristics reflect the dynamic change characteristics of the phase when the high-frequency pulse power supply and the DC regulated power supply work together.

[0038] Furthermore, the extraction of the output signal waveform in the collaborative scheduling network can be achieved through a fast Fourier transform algorithm, such as: the collected discrete signal data can be processed, converted from the time domain to the frequency domain, and then converted back to the time domain through an inverse transform to remove noise interference, etc., to obtain a clearer output signal waveform; the determination of the original phase data corresponding to the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network can be achieved through a Hilbert transform algorithm, such as: the signal can be processed to obtain its analytical signal, and then the instantaneous phase of the signal is extracted as the original phase data; the construction of the phase difference distribution map corresponding to the original phase data can be achieved through a difference calculation algorithm, such as: the high-frequency pulse The original phase data of the pulse power supply and the DC regulated power supply are subtracted point by point to obtain phase difference data, and then the phase difference data is mapped to the two-dimensional plane coordinates using a coordinate mapping algorithm to form a phase difference distribution diagram; the extraction of the phase fluctuation characteristics in the phase difference distribution diagram can be achieved through a wavelet transform algorithm, such as: multi-scale analysis can be performed on the phase difference distribution data to extract phase fluctuation characteristics at different scales, such as detail features and approximate features; the analysis of the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network can be achieved through a correlation analysis algorithm, such as: calculating the correlation between the phases of the high-frequency pulse power supply and the DC regulated power supply, evaluating the degree of coordination between the two, and thus obtaining the phase response characteristics.

[0039] The present invention can effectively identify abnormal fluctuations in power supply output by extracting the current ripple coefficient and voltage fluctuation threshold in the phase response characteristics, thereby optimizing the power supply design and improving the reliability of equipment operation. In addition, the extraction of these parameters lays an important foundation for the subsequent dynamic regulation and fault warning of the power supply system, which helps to achieve efficient and energy-saving operation of the cell disruptor.

[0040] Among them, the current ripple coefficient refers to the ratio of the effective value of the AC component to the DC component in the current, usually expressed as a percentage. The current ripple coefficient intuitively reflects the degree of current fluctuation. The larger the coefficient, the higher the proportion of the AC component in the current, the worse the current stability, which will affect the normal operation of the electrical equipment, such as increasing heat generation and shortening the life of the equipment; the voltage fluctuation threshold refers to the upper and lower limits of the output voltage of the power supply allowed to fluctuate under normal working conditions. During the operation of the power supply, due to factors such as load changes and grid voltage fluctuations, the output voltage will fluctuate to a certain extent. The voltage fluctuation threshold is an acceptable voltage fluctuation limit set to ensure the normal operation of the equipment. Optionally, the extraction of the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristic can be achieved through an oscilloscope measurement method, such as: through the measurement function of the oscilloscope, the peak-to-peak value of the current ripple and other parameters can be directly read, and then the current ripple coefficient is calculated, and the fluctuation range of the voltage waveform is observed to determine the voltage fluctuation threshold.

[0041] Furthermore, based on the current ripple coefficient and the voltage fluctuation threshold, the present invention calculates the energy coupling matching degree of the target cell disruptor when it is powered in parallel, can accurately determine the synergistic effect of different power supplies in parallel, and promptly discover energy loss problems caused by abnormal current and voltage, and optimize the power supply configuration according to the calculation results, thereby ensuring the stable operation of the cell disruptor, reducing energy consumption, and extending the service life of the equipment.

[0042] The energy coupling matching degree refers to a quantitative index of the energy transmission efficiency of each power module in a parallel power supply system when working together, and is used to evaluate whether the energy distribution between the power modules is balanced and the overall energy utilization efficiency of the system.

[0043] As an embodiment of the present invention, the energy coupling matching degree of the target cell disruptor when powered in parallel is calculated based on the current ripple coefficient and the voltage fluctuation threshold, including: The energy coupling matching degree of the target cell disruptor when powered in parallel is calculated using the following formula: ; in, represents the energy coupling matching degree, and They represent the start time and end time of calculating the energy coupling matching degree, respectively. Indicates at time The comprehensive evaluation function of the current ripple coefficient and the voltage fluctuation threshold at the moment, Indicates the number of power modules in the parallel power supply system. Indicates the quantity index of the power module. Indicates The capacity factor of each power module, Represents the stability index of the parallel power supply system, Indicates the interference factor index of the parallel power supply system.

[0044] In detail, the comprehensive evaluation function refers to a dynamic evaluation function constructed based on the current ripple coefficient and the voltage fluctuation threshold, which is used to describe the comprehensive performance of the power supply system at time t; the parallel power supply system refers to a power supply network composed of multiple power supply modules (such as high-frequency pulse power supply and DC regulated power supply) in parallel, which is used to provide stable and efficient power supply for the target cell disruptor; the power supply module refers to an independent power supply unit in the parallel power supply system, each module has independent voltage and current output capabilities, such as high-frequency pulse power supply module and DC regulated power supply module; the capacity coefficient refers to the ratio of the rated output capacity of the jth power supply module to its actual output capacity, which is used to characterize the energy contribution capacity of the module in the system; the stability index refers to the ability of the parallel power supply system to maintain voltage and current stability during operation; the interference factor index refers to the comprehensive quantitative value of external and internal interference factors that affect the stability of the parallel power supply system, including electromagnetic interference, circuit noise, temperature fluctuations, etc.

[0045] S3. Based on the energy coupling matching degree, simulate the power consumption distribution map of the sample processing chamber under the variable load impact condition, and construct the adaptive logic rules corresponding to the target cell disruptor according to the power consumption distribution map.

[0046] Based on the energy coupling matching degree, the present invention simulates the power consumption distribution map of the sample processing cavity under the variable load impact condition, and can intuitively present the power consumption changes under different working conditions. Through this map, high power consumption areas and time periods can be accurately located, helping to optimize the cavity design and power supply configuration, and power consumption anomalies can be predicted in advance, providing a strong basis for energy saving and stable operation of equipment, reducing operating costs and potential failure risks.

[0047] Among them, the variable load impact condition refers to the situation that the load borne by the sample processing chamber during operation is not constant, but is in dynamic change and accompanied by impact. This change may be caused by differences in sample properties, fluctuations in processing volume, etc., and the impact may be caused by equipment start-up and shutdown, processing flow switching, etc.; the power consumption distribution map refers to the graphical presentation of the power consumption distribution of the sample processing chamber at different positions and different time periods under the variable load impact condition, which intuitively displays the spatial and temporal distribution characteristics of the power consumption.

[0048] As an embodiment of the present invention, the power consumption distribution spectrum of the sample processing cavity under the variable load impact condition is simulated based on the energy coupling matching degree, including: extracting key parameters in the energy coupling matching degree; based on the key parameters, constructing a dynamic load framework corresponding to the sample processing cavity; based on the dynamic load framework, collecting historical power consumption data corresponding to the sample processing cavity; analyzing the power consumption change pattern corresponding to the historical power consumption data; based on the power consumption change pattern, simulating the power consumption distribution spectrum of the sample processing cavity under the variable load impact condition.

[0049] Among them, the key parameters refer to parameters extracted from the energy coupling matching degree that have a significant impact on the power consumption of the sample processing chamber, such as the current distribution ratio and voltage difference between parallel power supplies; the dynamic load framework refers to a model architecture built based on key parameters, which is used to describe the dynamic changes in the load of the sample processing chamber under different working conditions, which defines the rules and ranges of changes in the chamber load with time, energy coupling state and other factors; the historical power consumption data refers to the power consumption related data recorded in the past operation of the sample processing chamber under various working conditions (including but not limited to variable load impact conditions), such as power values ​​at different times, accumulated power consumption, etc.; the power consumption change mode refers to the law and trend of changes in the power consumption of the sample processing chamber with time, load and other factors obtained by analyzing the historical power consumption data, such as linear changes, periodic fluctuations, mutations and other modes.

[0050] Furthermore, the extraction of key parameters in the energy coupling matching degree can be achieved through principal component analysis, such as: performing linear transformation on multiple related variables of the energy coupling matching degree, converting them into a set of unrelated principal components, and selecting the original variables corresponding to the principal components with larger variance contribution rates as key parameters; the construction of the dynamic load framework corresponding to the sample processing cavity can be achieved through a finite element algorithm, such as: dividing the sample processing cavity into multiple finite units, analyzing the physical characteristics and interactions of each unit, and thus constructing an overall dynamic load framework; the collection of historical power consumption data corresponding to the sample processing cavity can be achieved through a power analyzer, such as: various electrical parameters can be measured with high precision, including power, Voltage, current, etc. can record the power consumption data of the sample processing cavity stably for a long time; the analysis of the power consumption change pattern corresponding to the historical power consumption data can be achieved through a time series analysis method, such as: treating the historical power consumption data as a time series, using ARIMA (autoregressive integrated moving average model) and other models to analyze and predict it, and find out the trend, seasonality and periodicity and other change patterns in the data; the simulation of the power consumption distribution map of the sample processing cavity under the variable load impact condition can be achieved through a Monte Carlo algorithm, such as: simulating various possible situations of the variable load impact condition by random sampling, combining the historical power consumption data and the power consumption change pattern, calculating the power consumption distribution under different working conditions, and finally generating a power consumption distribution map.

[0051] The present invention constructs adaptive logic rules corresponding to the target cell disruptor based on the power consumption distribution map, intuitively displays the energy consumption of the device under different working conditions, and the rules constructed in this way can allow the device to autonomously adjust the working mode according to the real-time power consumption, avoid energy waste, ensure stable operation of the equipment, reduce long-term operating costs, and enhance the adaptability of the equipment to complex working environments.

[0052] Among them, the adaptive logic rules refer to a set of criteria for automatically adjusting the working strategy based on the operating status and environmental changes of the target cell disruptor. The adaptive logic rules take the power consumption distribution map as an important basis and comprehensively consider the energy consumption differences under different working conditions. For example, when the power consumption is detected to be in the high energy consumption range in the map, the rules will instruct the device to reduce the operating power or adjust the working rhythm; if it is in a low power consumption and stable stage, it maintains an efficient operating mode. Optionally, the construction of the adaptive logic rules corresponding to the target cell disruptor can be implemented through rule construction tools, such as: MATLAB, LabVIEW and other tools.

[0053] S4. Integrate the adaptive logic rules with the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, extract the execution energy efficiency parameters in the control strategy, and calculate the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameters.

[0054] The present invention integrates the adaptive logic rules and the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, which can achieve efficient switching and energy compensation of power supply modes, significantly improve the response speed and stability of the system, accurately match power supply output and load requirements, reduce energy loss and extend the service life of the equipment.

[0055] Among them, the synchronous compensation mechanism refers to a control mechanism that dynamically adjusts the power output to compensate for energy fluctuations by real-time monitoring of parameters such as voltage and current during the power mode switching process. This mechanism ensures the energy continuity and stability during the power switching process by quickly responding to load changes, and avoids voltage sag or current shock caused by switching; the composite power supply system refers to a hybrid power supply system composed of multiple types of power supplies (such as high-frequency pulse power supply, DC regulated power supply, etc.). Through collaborative work, the system can dynamically switch power modes according to load requirements, achieve efficient energy distribution and stable output, and meet the power requirements of the cell disruptor under different working conditions; the dynamic control strategy refers to a method and strategy for dynamically controlling the composite power supply system according to the real-time working conditions of the cell disruptor by integrating adaptive logic rules and synchronous compensation mechanisms. It stipulates how the composite power supply system switches working modes, when to start synchronous compensation, and in what way to compensate under different working conditions, to ensure that the cell disruptor can operate stably and efficiently under various conditions.

[0056] As an embodiment of the present invention, the adaptive logic rules and the preset synchronous compensation mechanism are integrated to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, including: extracting the key trigger conditions in the adaptive logic rules; clarifying the compensation execution method corresponding to the preset synchronous compensation mechanism; constructing a working condition database corresponding to the target cell disruptor based on the key trigger conditions and the compensation execution method; screening typical working condition data in the working condition database; and generating a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor based on the typical working condition data.

[0057] Among them, the key trigger condition refers to the key factor in the adaptive logic rule that determines whether the rule is activated. For example, when the power consumption of the target cell disruptor exceeds or falls below a certain set threshold, or when it is detected that the cell sample processing progress reaches a specific stage, these power consumption thresholds, processing progress stages and other conditions are key trigger conditions; the compensation execution method refers to the specific operation method taken by the synchronous compensation mechanism after it is started. For example, when it is detected that the voltage output of the power supply fluctuates, the voltage and current deviations are corrected by adjusting the capacitance and inductance parameters in the circuit, or changing the pulse width and frequency of the power supply, etc., to ensure stable output of the power supply. These specific adjustment actions constitute the compensation execution method. Formula; the working condition database refers to a collection of relevant data of the target cell disruptor under various operating conditions, and the data sources include operating parameters of the composite power supply system under different experimental samples, different processing volumes, different ambient temperatures and other working conditions, such as the current and voltage values ​​output by the power supply, and the working status data of the cell disruptor, such as the rotation speed, vibration amplitude, etc.; the typical working condition data refers to data selected from the working condition database, which can represent the common working conditions of the cell disruptor with research and reference value, such as the most commonly used sample types in daily experiments and the operating data under the most frequent processing volume settings. These data reflect the working conditions of the cell disruptor in most cases.

[0058] Furthermore, the extraction of key trigger conditions in the adaptive logic rules may be achieved through a decision tree algorithm, such as converting the adaptive logic rules into a decision tree structure, where the nodes of the tree are conditional judgments and the branches are results under different conditions. By traversing the decision tree, all conditional nodes are extracted, which are the key trigger conditions; the compensation execution mode corresponding to the preset synchronous compensation mechanism can be implemented by a circuit simulation tool, such as: building a circuit model of the synchronous compensation mechanism in the Multisim tool, simulating different voltage and current fluctuations, observing the actions and parameter changes of each component in the model, so as to determine the actual compensation execution mode; the construction of the working condition database corresponding to the target cell disruptor can be implemented by a database construction tool, such as: MySQL, Oracle and other tools; the screening of typical working condition data in the working condition database can be implemented by the KMeans function, such as: clustering the working condition data using the KMeans function, setting a suitable number of clusters n_clusters, and then selecting data from the vicinity of each cluster center as typical working condition data; the generation of the dynamic control strategy of the composite power supply system corresponding to the target cell disruptor can be implemented by a reinforcement learning algorithm, such as: taking the state of the composite power supply system as the environmental state input, taking various control actions (such as power switching, compensation operation, etc.) as the action space, and continuously learning through interaction with the environment, optimizing the control strategy according to the reward function (such as power supply stability, cell disruption effect, etc.), and finally obtaining a dynamic control strategy.

[0059] By extracting the execution energy efficiency parameters in the control strategy, the present invention can identify the inefficient links in the control strategy and make targeted improvements, which can significantly improve the overall energy efficiency of the power supply system and help achieve efficient and energy-saving operation of the cell disruptor.

[0060] Among them, the execution energy efficiency parameters refer to a series of quantitative indicators used to measure the energy utilization efficiency and work effectiveness of the target cell disruptor composite power supply system when implementing the control strategy. It covers the power conversion efficiency, that is, the proportion of input electrical energy converted into effective working electrical energy for the cell disruptor; power factor, which reflects the ratio of useful power to apparent power in the power supply system, and reflects the effective utilization of electrical energy; and unit processing capacity energy consumption, which shows the amount of electricity consumed per unit cell disruption task. Optionally, the extraction of the execution energy efficiency parameters in the control strategy can be achieved through deep learning algorithms, such as: recurrent neural networks, long short-term memory networks, etc.

[0061] The present invention calculates the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameter, and can timely detect the energy utilization efficiency decline of the equipment under long-term operation or different working conditions, accurately locate the key links that lead to energy efficiency reduction, and then optimize the equipment operation plan and arrange maintenance plan in a targeted manner to ensure that the equipment is always in an efficient operation state and reduce energy consumption costs.

[0062] The energy efficiency attenuation value refers to the degree of dispersion of the energy efficiency corresponding to the energy efficiency parameters executed by the target cell disruptor under different working modes relative to the overall average level, thereby reflecting the decline of the energy efficiency of the equipment.

[0063] As an embodiment of the present invention, the step of calculating the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameter includes: The energy efficiency attenuation value corresponding to the target cell disruptor is calculated using the following formula: ; in, represents the energy efficiency attenuation value corresponding to the target cell disruptor, represents the total number of the execution energy efficiency parameters, represents the quantity index of the execution energy efficiency parameter, represents the total number of working modes corresponding to the target cell disruptor, represents the quantity index of the working mode, Indicated in The energy efficiency parameters and The energy efficiency value corresponding to each working mode is: Indicates that among all execution energy efficiency parameters, the corresponding The average energy efficiency of each working mode.

[0064] In detail, the working mode refers to the different operating states or operating modes set by the target cell disruptor in order to adapt to different cell disruption requirements, sample characteristics or operating conditions, for example, there may be a low-speed high-torque mode, a high-speed low-torque mode, etc. for cell samples of different hardness; the energy efficiency value refers to a value related to the energy utilization efficiency of the target cell disruptor under specific execution energy efficiency parameters and working modes, which reflects the ability of the device to convert input energy into effective cell disruption energy when the parameters are set and the working mode is running. Different combinations of execution energy efficiency parameters (such as power factor, power conversion efficiency, etc.) and working modes will have different energy efficiency values, which are the basic data for calculating the energy efficiency attenuation value; the energy efficiency average value refers to the average energy utilization efficiency value calculated by comprehensively considering all execution energy efficiency parameters for each working mode of the target cell disruptor, which represents the average energy efficiency level under the influence of all execution energy efficiency parameters in this working mode, and is used to compare with each specific energy efficiency value to calculate the energy efficiency attenuation value and measure the degree of energy efficiency deviation of the working mode under different execution energy efficiency parameters.

[0065] S5. Based on the energy efficiency attenuation value, dynamically adjust the duty cycle modulation parameters corresponding to the target cell disruptor, evaluate the power supply working state corresponding to the target cell disruptor based on the duty cycle modulation parameters, and analyze the energy efficiency evaluation dimension corresponding to the power supply working state, and formulate a power supply optimization plan corresponding to the target cell disruptor based on the energy efficiency evaluation dimension.

[0066] The present invention dynamically adjusts the duty cycle modulation parameters corresponding to the target cell disruptor based on the energy efficiency attenuation value, can optimize the matching degree between power output and load demand in real time, significantly improve the energy utilization efficiency of the equipment, effectively reduce energy loss and extend the service life of key components of the equipment.

[0067] Among them, the duty cycle modulation parameter refers to the parameter used to control the ratio of the on-time and off-time of the power supply signal when the target cell disruptor is working. By adjusting this parameter, the power input, operating state, etc. of the device can be changed, thereby affecting the energy efficiency performance of the device.

[0068] As an embodiment of the present invention, dynamically adjusting the duty cycle modulation parameters corresponding to the target cell disruptor based on the energy efficiency attenuation value includes: extracting the key attenuation factor in the energy efficiency attenuation value; analyzing the attenuation fluctuation period corresponding to the key attenuation factor; dividing the energy efficiency stages corresponding to the attenuation fluctuation period; counting the execution energy efficiency parameters in the energy efficiency stage; and dynamically adjusting the duty cycle modulation parameters corresponding to the target cell disruptor based on the execution energy efficiency parameters.

[0069] Among them, the key attenuation factor refers to the factor that plays a key role and has a greater impact on the energy efficiency decline of the target cell disruptor among the factors that constitute the energy efficiency attenuation value. These factors include the decrease in power conversion efficiency, the increase in power loss in a specific working mode, etc.; the attenuation fluctuation period refers to the duration of the periodic fluctuation of the key attenuation factor over time, that is, the time it takes for the key attenuation factor to start from a state and return to a similar state after a series of changes; the energy efficiency stage refers to different time periods divided according to the attenuation fluctuation period. The energy efficiency performance of the target cell disruptor in each time period has certain similarities or regularity. In different energy efficiency stages, the energy utilization efficiency, operating status, etc. of the equipment are different; the execution energy efficiency parameters refer to a series of quantitative indicators used to measure the energy utilization efficiency and work effectiveness of the composite power supply system of the target cell disruptor when implementing the control strategy, such as power conversion efficiency, power factor, energy consumption per unit processing volume, etc.

[0070] Furthermore, the extraction of the key attenuation factor in the energy efficiency attenuation value can be achieved through a factor analysis method, such as: decomposing the influencing factors of the energy efficiency attenuation value, and determining the key attenuation factor by gradually analyzing the contribution of each factor to the energy efficiency attenuation value; the analysis of the attenuation fluctuation period corresponding to the key attenuation factor can be achieved through a spectrum analysis method, such as: Fourier transforming the data of the key attenuation factor changing over time, converting the time domain signal into a frequency domain signal, thereby finding the main frequency component in the signal, and the reciprocal of which is the attenuation fluctuation period; the division of the energy efficiency stage corresponding to the attenuation fluctuation period can be achieved through a cluster analysis method, such as: dividing the entire attenuation fluctuation period into several similar stages according to the numerical characteristics of the key attenuation factor at different time points; the statistics of the execution energy efficiency parameters in the energy efficiency stage can be achieved through statistical functions, such as: AVERAGE, STDEV and other functions; the dynamic adjustment of the duty cycle modulation parameters corresponding to the target cell disruptor can be achieved through an Arduino development board, such as: the PID control algorithm can be programmed and implemented on the Arduino development board, the execution energy efficiency parameters are obtained in real time by connecting sensors, and the duty cycle modulation parameters are dynamically adjusted according to the calculation results.

[0071] The present invention evaluates the power supply working state corresponding to the target cell disruptor based on the duty cycle modulation parameters, and analyzes the energy efficiency evaluation dimension corresponding to the power supply working state, and can accurately measure the power supply energy efficiency from multiple aspects, such as energy consumption, power output stability, etc. This can not only detect potential power supply problems in a timely manner, but also provide a strong basis for further optimizing power supply performance and improving the overall energy efficiency of the cell disruptor.

[0072] Among them, the power supply working status refers to the real-time status of the power supply of the target cell disruptor during operation, covering multiple key aspects of the power supply, for example, whether the output voltage of the power supply is stable within the rated range, whether the output current fluctuates normally with the load change, and whether the operating frequency of the power supply is constant. At the same time, it also includes the working conditions of each circuit module inside the power supply, such as whether the rectification, filtering, inversion and other links are operating normally. These combined reflect the operating status of the power supply under the current duty cycle modulation parameters; the energy efficiency evaluation dimension refers to an indicator system that evaluates the energy utilization efficiency of the power supply when the target cell disruptor is running from multiple angles, which includes power conversion efficiency, that is, the proportion of the input electrical energy converted by the power supply into the usable electrical energy of the cell disruptor, which directly reflects the effective utilization of electrical energy; power factor, which reflects the useful power in the power supply system and The ratio of apparent power, a high power factor means that the power supply has a higher utilization rate of the power grid; there is also energy consumption per unit time, which shows the amount of electricity consumed by the power supply to maintain the operation of the cell disruptor per unit time. Optionally, the evaluation of the working state of the power supply corresponding to the target cell disruptor can be achieved through a Kalman filtering algorithm, such as filtering the collected voltage, current and other data to remove noise interference, and more accurately obtain the true value of the power supply parameters, thereby determining whether the power supply is in a normal working state; the analysis of the energy efficiency evaluation dimension corresponding to the working state of the power supply can be achieved through a hierarchical analysis method, such as using energy efficiency evaluation dimensions such as power conversion efficiency, power factor, and energy consumption per unit time as indicators at different levels, constructing a hierarchical model, and comprehensively evaluating the energy efficiency level of the power supply by calculating the weight of each indicator, thereby obtaining the energy efficiency evaluation dimension.

[0073] Based on the dimension of energy efficiency evaluation, the present invention formulates a power supply optimization plan corresponding to the target cell disruptor, which can accurately locate the links with high power consumption and low efficiency, and make targeted improvements, such as upgrading circuit components and optimizing control strategies, so as to ensure the efficient and stable operation of the cell disruptor and extend the service life of the equipment.

[0074] Among them, the power supply optimization plan refers to a comprehensive and systematic improvement measure aimed at improving the performance and energy efficiency of the target cell disruptor power supply. At the hardware level, it involves replacing higher quality, low-loss electronic components, such as replacing existing components with low-resistance power transistors to reduce energy loss during current transmission; or upgrading the transformer to improve the efficiency of power conversion. In terms of software and control strategies, by optimizing the duty cycle modulation algorithm, the power supply can output adaptive power more accurately under different workloads to avoid unnecessary energy waste. Optionally, the power supply optimization plan corresponding to the target cell disruptor can be achieved through a solution generation tool, such as: Tableau, PowerBI and other tools.

[0075] Compared with the problems described in the background technology, the present invention obtains the sample processing chamber corresponding to the target cell disruptor and collects the real-time load spectrum corresponding to the sample processing chamber. It can accurately identify the changes in power demand under different crushing intensities and realize dynamic matching of power supply output, thereby significantly improving energy utilization efficiency. At the same time, the collection of real-time load spectrum provides data support for the equipment operation status, which helps to optimize the crushing effect and extend the service life of the equipment. The present invention analyzes the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network, and can accurately control their working rhythm under different working conditions, avoid power supply disorder caused by phase deviation, improve power supply coordination efficiency, ensure the stable operation of the target cell disruptor under complex loads, reduce equipment failures, and improve energy utilization efficiency. Furthermore, based on the energy coupling matching degree, the present invention simulates the power consumption distribution spectrum of the sample processing chamber under variable load impact conditions, and can intuitively present the power consumption changes under different working conditions. Through this map, high power consumption areas and time periods can be accurately located, helping to optimize the cavity design and power supply configuration, and power consumption anomalies can be predicted in advance, providing a strong basis for energy saving and stable operation of the equipment, reducing operating costs and potential failure risks. Furthermore, the present invention integrates the adaptive logic rules and the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell crusher, which can achieve efficient switching and energy compensation of power supply modes, significantly improve the response speed and stability of the system, accurately match power output with load requirements, reduce energy loss and extend the service life of the equipment. Finally, based on the energy efficiency attenuation value, the present invention dynamically adjusts the duty cycle modulation parameters corresponding to the target cell crusher, which can optimize the matching degree of power output and load requirements in real time, significantly improve the energy utilization efficiency of the equipment, and effectively reduce energy loss and extend the service life of key components of the equipment. Therefore, the power optimization method and system of an efficient and energy-saving integrated cell crusher provided in an embodiment of the present invention can improve the power optimization efficiency of the cell crusher.

[0076] Embodiment 2: like Figure 2 The figure shows a functional module diagram of a high-efficiency and energy-saving integrated cell disruptor power optimization system of the present invention.

[0077] The high-efficiency and energy-saving integrated cell disruptor power optimization system 200 of the present invention can be installed in an electronic device. According to the functions to be implemented, the high-efficiency and energy-saving integrated cell disruptor power optimization system can include a scheduling network construction module 201, a matching degree calculation module 202, a rule construction module 203, an attenuation value calculation module 204 and a program formulation module 205. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0078] In the embodiment of the present invention, the functions of each module / unit are as follows: The scheduling network construction module 201 is used to obtain the sample processing chamber corresponding to the target cell disruptor, collect the real-time load spectrum corresponding to the sample processing chamber, analyze the power demand curve of the sample processing chamber under different crushing intensities based on the real-time load spectrum, and construct the collaborative scheduling network corresponding to the target cell disruptor according to the power demand curve; The matching degree calculation module 202 is used to analyze the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the cooperative scheduling network, extract the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristics, and calculate the energy coupling matching degree of the target cell disruptor when it is powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold; The rule construction module 203 is used to simulate the power consumption distribution map of the sample processing chamber under the variable load impact condition based on the energy coupling matching degree, and construct the adaptive logic rule corresponding to the target cell disruptor according to the power consumption distribution map; The attenuation value calculation module 204 is used to integrate the adaptive logic rules and the preset synchronous compensation mechanism, generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, extract the execution energy efficiency parameters in the control strategy, and calculate the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameters; The scheme formulation module 205 is used to dynamically adjust the duty cycle modulation parameters corresponding to the target cell disruptor based on the energy efficiency attenuation value, evaluate the power supply working state corresponding to the target cell disruptor based on the duty cycle modulation parameters, and analyze the energy efficiency evaluation dimension corresponding to the power supply working state, and formulate a power supply optimization scheme corresponding to the target cell disruptor based on the energy efficiency evaluation dimension.

[0079] In detail, each module in the high-efficiency and energy-saving integrated cell disruptor power optimization system 200 described in the embodiment of the present invention adopts the same method as above when in use. Figure 1 The same technical means are used as the power optimization method for an efficient and energy-saving integrated cell disruptor described in the text and can produce the same technical effects, so they will not be repeated here.

[0080] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method, characterized in that: The method comprises: Acquire a sample processing cavity corresponding to a target cell disruptor, and collect a real-time load spectrum corresponding to the sample processing cavity, analyze the power demand curve of the sample processing cavity under different crushing intensities based on the real-time load spectrum, and construct a collaborative scheduling network corresponding to the target cell disruptor according to the power demand curve; Analyze the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the cooperative scheduling network, extract the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristics, and calculate the energy coupling matching degree of the target cell disruptor when powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold; Based on the energy coupling matching degree, the power consumption distribution map of the sample processing chamber under the variable load impact condition is simulated, and the adaptive logic rules corresponding to the target cell disruptor are constructed according to the power consumption distribution map; Integrate the adaptive logic rules with the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, extract the execution energy efficiency parameters in the control strategy, and calculate the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameters; Based on the energy efficiency attenuation value, the duty cycle modulation parameters corresponding to the target cell disruptor are dynamically adjusted; based on the duty cycle modulation parameters, the power supply working state corresponding to the target cell disruptor is evaluated, and the energy efficiency evaluation dimension corresponding to the power supply working state is analyzed; based on the energy efficiency evaluation dimension, a power supply optimization plan corresponding to the target cell disruptor is formulated.

2. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The step of analyzing the electric energy demand curve of the sample processing chamber under different crushing intensities based on the real-time load spectrum includes: Performing multi-scale wavelet decomposition on the real-time load spectrum to obtain multi-scale spectrum components; Extracting component frequency points in the multi-scale spectral components; Query the component amplitude corresponding to the component frequency point; Determining a crushing intensity interval corresponding to the sample processing cavity based on the component amplitude; Extracting the power demand points in the crushing intensity interval; Based on the power demand point, the power demand curve of the sample processing chamber under different crushing intensities is analyzed.

3. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The step of constructing a coordinated scheduling network corresponding to the target cell disruptor according to the electric energy demand curve includes: Extracting key characteristic points from the electric energy demand curve; Based on the key characteristic points, dividing the dynamic load interval corresponding to the electric energy demand curve; quantifying the energy demand of the dynamic load interval to obtain an interval energy demand value; Based on the interval energy demand value, analyzing the power allocation ratio corresponding to the target cell disruptor; Based on the power allocation ratio, analyzing the degree of coordinated scheduling corresponding to the target cell disruptor; Based on the collaborative scheduling degree, a collaborative scheduling network corresponding to the target cell disruptor is constructed.

4. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The analyzing the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the coordinated scheduling network includes: Extracting an output signal waveform in the collaborative scheduling network; Based on the output signal waveform, determining the original phase data corresponding to the high-frequency pulse power supply and the DC regulated power supply in the coordinated scheduling network; Constructing a phase difference distribution diagram corresponding to the original phase data; Extracting phase fluctuation features in the phase difference distribution diagram; Based on the phase fluctuation characteristics, the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the collaborative scheduling network are analyzed.

5. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The calculating the energy coupling matching degree of the target cell disruptor when powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold comprises: The energy coupling matching degree of the target cell disruptor when powered in parallel is calculated using the following formula: ； in, represents the energy coupling matching degree, and They represent the start time and end time of calculating the energy coupling matching degree, respectively. Indicates at time The comprehensive evaluation function of the current ripple coefficient and the voltage fluctuation threshold at the moment, Indicates the number of power modules in the parallel power supply system. Indicates the quantity index of the power module. Indicates The capacity factor of each power module, Represents the stability index of the parallel power supply system, Indicates the interference factor index of the parallel power supply system.

6. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The simulating the power consumption distribution spectrum of the sample processing chamber under the variable load impact condition based on the energy coupling matching degree includes: Extracting key parameters in the energy coupling matching degree; Based on the key parameters, construct a dynamic load framework corresponding to the sample processing chamber; Based on the dynamic load framework, collecting historical power consumption data corresponding to the sample processing cavity; Analyzing the power consumption change pattern corresponding to the historical power consumption data; Based on the power consumption variation pattern, a power consumption distribution spectrum of the sample processing chamber under a variable load impact condition is simulated.

7. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The integration of the adaptive logic rules and the preset synchronous compensation mechanism to generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor includes: Extracting key trigger conditions in the adaptive logic rules; Clarify the compensation execution method corresponding to the preset synchronous compensation mechanism; Based on the key trigger conditions and the compensation execution mode, constructing a working condition database corresponding to the target cell disruptor; Filtering typical operating condition data in the operating condition database; Based on the typical operating condition data, a dynamic control strategy of the composite power supply system corresponding to the target cell disruptor is generated.

8. The method for optimizing the power supply of an energy-efficient integrated cell disruptor according to claim 1, characterized in that: The step of calculating the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameter includes: The energy efficiency attenuation value corresponding to the target cell disruptor is calculated using the following formula: ； in, represents the energy efficiency attenuation value corresponding to the target cell disruptor, represents the total number of the execution energy efficiency parameters, represents the quantity index of the execution energy efficiency parameter, represents the total number of working modes corresponding to the target cell disruptor, represents the quantity index of the working mode, Indicated in The energy efficiency parameters and The energy efficiency value corresponding to each working mode is: Indicates that among all execution energy efficiency parameters, the corresponding The average energy efficiency of each working mode.

9. A high-efficiency and energy-saving integrated cell disruptor power supply optimization method as claimed in claim 1, characterized in that: The dynamically adjusting the duty cycle modulation parameter corresponding to the target cell disruptor based on the energy efficiency attenuation value includes: Extracting key attenuation factors from the energy efficiency attenuation value; Analyze the attenuation fluctuation period corresponding to the key attenuation factor; Dividing the energy efficiency stages corresponding to the attenuation fluctuation period; Counting the execution energy efficiency parameters in the energy efficiency stage; Based on the execution energy efficiency parameter, the duty cycle modulation parameter corresponding to the target cell disruptor is dynamically adjusted.

10. An efficient and energy-saving integrated cell disruptor power optimization system, characterized in that: The system comprises: A scheduling network construction module is used to obtain a sample processing chamber corresponding to a target cell disruptor, collect a real-time load spectrum corresponding to the sample processing chamber, analyze an electric energy demand curve of the sample processing chamber under different crushing intensities based on the real-time load spectrum, and construct a collaborative scheduling network corresponding to the target cell disruptor according to the electric energy demand curve; A matching degree calculation module is used to analyze the phase response characteristics of the high-frequency pulse power supply and the DC regulated power supply in the cooperative scheduling network, extract the current ripple coefficient and the voltage fluctuation threshold in the phase response characteristics, and calculate the energy coupling matching degree of the target cell disruptor when it is powered in parallel based on the current ripple coefficient and the voltage fluctuation threshold; A rule construction module, for simulating the power consumption distribution map of the sample processing chamber under the variable load impact condition based on the energy coupling matching degree, and constructing the adaptive logic rule corresponding to the target cell disruptor according to the power consumption distribution map; An attenuation value calculation module is used to integrate the adaptive logic rules and the preset synchronous compensation mechanism, generate a dynamic control strategy for the composite power supply system corresponding to the target cell disruptor, extract the execution energy efficiency parameters in the control strategy, and calculate the energy efficiency attenuation value corresponding to the target cell disruptor based on the execution energy efficiency parameters; A program formulation module is used to dynamically adjust the duty cycle modulation parameters corresponding to the target cell disruptor based on the energy efficiency attenuation value, evaluate the power supply working state corresponding to the target cell disruptor based on the duty cycle modulation parameters, analyze the energy efficiency evaluation dimension corresponding to the power supply working state, and formulate a power supply optimization program corresponding to the target cell disruptor based on the energy efficiency evaluation dimension.

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