A method and system for balancing the life of dual canister filter cartridges

Abstract

The application provides a double-cylinder filter core life balance regulation method and system, relates to the technical field of balance regulation, collects data of a double-cylinder filter, obtains filter collection data, acquires filter differential pressure reference data, combines and analyzes the filter differential pressure reference data and the filter collection data, and obtains filter combined analysis data; performs filter core life balance analysis according to the filter combined analysis data, obtains life balance analysis data, performs balance regulation analysis according to the life balance analysis data, obtains balance regulation analysis data; performs cleanliness analysis and regulation according to the balance regulation analysis data, obtains updated regulation data, performs life analysis and early warning according to the updated regulation data, and obtains life analysis and early warning data; the application can realize active filter core life balance regulation and oil cleanliness collaborative management and control, improve filter utilization and system operation stability, and reduce maintenance cost and system failure risk.

Description

Technical Field

[0001] This invention proposes a method and system for balancing the lifespan of a dual-cylinder filter element, which relates to the field of balancing control technology, specifically to the field of balancing control of the lifespan of a dual-cylinder filter element. Background Technology

[0002] Dual-cylinder filters are widely used in hydraulic systems and other fields. Their core function is to filter particulate impurities in the oil, ensuring the normal operation of core system components. Currently, traditional dual-cylinder filters generally adopt a passive control mode triggered by final differential pressure switching. This mode can only switch when one filter element becomes clogged to the set differential pressure, which has many technical defects. Traditional filters mostly collect single differential pressure data, which cannot comprehensively reflect the filter element status. They are prone to misinterpreting false differential pressure increases caused by operating condition fluctuations as filter element clogging, leading to incorrect control and replacement. At the same time, they cannot predict the difference in lifespan between the two filter elements and cannot actively intervene in the rate of decay, resulting in uneven lifespan of the two filter elements. This often leads to one filter element failing prematurely while the other remains idle and wasted, increasing maintenance costs and the risk of system downtime. In addition, in traditional technology, lifespan control and oil cleanliness control are independent of each other, which can easily lead to insufficient or excessive filtration, further aggravating filter element wear and system failure. Summary of the Invention

[0003] This invention provides a method and system for balancing the lifespan of a dual-tube filter element, to solve the above-mentioned problems:

[0004] This invention proposes a method and system for balancing the lifespan of a dual-cylinder filter element, the method comprising:

[0005] S1. Collect data from the dual-cylinder filter to obtain filter data collection data and filter differential pressure reference data. Combine and analyze the filter differential pressure reference data with the filter data collection data to obtain filter combined analysis data.

[0006] S2. Based on the filter and combined analysis data, perform filter element life balance analysis to obtain life balance analysis data. Based on the life balance analysis data, perform balance control analysis to obtain balance control analysis data.

[0007] S3. Based on the balanced control analysis data, perform cleanliness analysis and control to obtain updated control data. Based on the updated control data, perform lifespan analysis and early warning to obtain lifespan analysis and early warning data.

[0008] Furthermore, the system includes:

[0009] The combined analysis module is used to collect data from the dual-cylinder filter, obtain filter collection data, acquire filter differential pressure reference data, and combine and analyze the filter differential pressure reference data with the filter collection data to obtain filter combined analysis data.

[0010] The equalization analysis module is used to perform filter cartridge life equalization analysis based on the filter and analysis data to obtain life equalization analysis data, and to perform equalization control analysis based on the life equalization analysis data to obtain equalization control analysis data.

[0011] The cleaning analysis module is used to perform cleaning analysis and control based on the balanced control analysis data, obtain updated control data, and perform lifespan analysis and early warning based on the updated control data, thereby obtaining lifespan analysis and early warning data.

[0012] The beneficial effects of this invention are as follows: This invention achieves a fundamental shift from passive to active balancing, synchronous attenuation, synchronous use, and synchronous replacement of dual-cylinder filter elements, breaking the limitations of traditional passive control. It allows for a more rational load distribution between the two filter elements, avoiding excessive wear on one filter element and wasteful idleness on the other. It significantly improves the overall service life and utilization rate of the filter elements, fully utilizing the value of each element and maximizing the replacement cycle, thus reducing total filter element consumption and replacement costs. It reduces system maintenance frequency and downtime risk. Through early warning and active control, it effectively avoids system failures caused by sudden filter element blockage, reduces downtime due to filter element maintenance and replacement, and ensures continuous and stable operation of the hydraulic system. It enhances the long-term operational stability and reliability of the hydraulic system. Through precise balancing control and cleanliness management, it effectively avoids problems such as system component wear and frequent failures caused by filter element life imbalance and substandard oil cleanliness, extending the service life of the entire hydraulic system. It improves the intelligence and precision of control. Through multi-dimensional data collection and analysis, it can accurately determine the filter element status and lifespan differences. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of a method for balancing the lifespan of a dual-cylinder filter element. Detailed Implementation

[0014] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0015] Example 1:

[0016] In one embodiment of the present invention, a method and system for balancing the lifespan of a dual-cylinder filter element are provided, the method comprising:

[0017] S1. Collect data from the dual-cylinder filter to obtain filter data collection data and filter differential pressure reference data. Combine and analyze the filter differential pressure reference data with the filter data collection data to obtain filter combined analysis data.

[0018] S2. Based on the filter and combined analysis data, perform filter element life balance analysis to obtain life balance analysis data. Based on the life balance analysis data, perform balance control analysis to obtain balance control analysis data.

[0019] S3. Based on the balanced control analysis data, perform cleanliness analysis and control to obtain updated control data. Based on the updated control data, perform lifespan analysis and early warning to obtain lifespan analysis and early warning data, such as... Figure 1 As shown.

[0020] The working principle and technical effects of the above-mentioned technical solution are as follows: This method comprehensively collects data from a dual-cylinder filter, covering the operating parameters, pressure parameters, and oil characteristic parameters of each cylinder. Simultaneously, it acquires preset filter differential pressure benchmark data. This benchmark data is pre-calibrated based on the filter's rated operating conditions, filter element rated parameters, and industry standards, reflecting the differential pressure range under normal filter operation. The real-time collected filter data is combined with the differential pressure benchmark data for multi-dimensional and comprehensive analysis, eliminating invalid data interference and integrating effective information to ultimately obtain filter combined analysis data that comprehensively reflects the dual-cylinder filter's operating status, filter element contamination level, and parameter deviations. Based on the filter combined analysis data, the differential pressure change pattern of the dual-cylinder filter elements is deeply extracted, and then filter element life balancing analysis is conducted to accurately determine the life differences and decay rate differences between the dual-cylinder filter elements, forming life balancing analysis data. Then, combined with the life balancing analysis data, targeted balancing control analysis is performed to formulate balancing control strategies that meet actual operating conditions, clarifying the control direction, control parameters, and control methods, and obtaining balancing control analysis data. By using the obtained balanced control analysis data, the cleanliness of the system oil is monitored and comprehensively analyzed in real time to determine whether the current oil cleanliness meets the system's operating requirements. If not, targeted cleanliness control is performed to obtain oil cleanliness adjustment data. Then, the original balanced control data is dynamically updated based on the oil cleanliness adjustment data to obtain updated control data. Based on the updated control data, the lifespan decay of the dual-cylinder filter element is tracked in real time, and accurate lifespan analysis and early warning are performed to obtain lifespan analysis and early warning data. This promptly reminds staff to maintain or replace the filter element, ensuring that the entire control process forms a closed loop and continuously guarantees the balanced lifespan of the dual-cylinder filter element.

[0021] This method fundamentally solves many technical problems in the control of filter element life in traditional dual-cylinder filters. Traditional dual-cylinder filters generally adopt a passive control mode of "final pressure differential trigger switching," which can only trigger switching when one filter element becomes clogged to a certain extent. It cannot predict the lifespan difference between the two filter elements in advance, nor can it actively intervene in the filter element decay rate. This results in a severe imbalance in the lifespan of the two filter elements, often leading to one filter element prematurely clogging and failing, requiring frequent replacement, while the other filter element remains in good condition, resulting in significant idle waste. This not only increases the consumption and maintenance costs of the filter elements but also causes system downtime due to frequent switching and maintenance, affecting the continuous and stable operation of the entire hydraulic system. This method, by constructing a complete closed-loop control system, achieves active and balanced control of the dual-cylinder filter element life, effectively solving the above-mentioned technical problems.

[0022] In one embodiment of the present invention, S1 includes:

[0023] Obtain preset data collection type information, and perform multiple types of data collection on the dual-barrel filter according to the preset data collection type information to obtain filter collection data;

[0024] Obtain the preset data type reference data of the dual-cylinder filter and obtain the filter differential pressure reference data;

[0025] The filter-collected data is compared with the filter baseline data in multiple categories to obtain multiple categories of comparison data.

[0026] Multi-class comparative analysis is performed based on multi-class comparative data to obtain filter-combined analysis data.

[0027] The working principle and technical effects of the above solution are as follows: Based on the model, filter element specifications, system operating requirements, and industry standards of the dual-cylinder filter, the preset data acquisition types are determined in advance. The types of data to be collected are clearly defined, covering various operating parameters and oil characteristic parameters for each cylinder, such as inlet pressure, outlet pressure, flow rate, operating temperature, start-up temperature, oil kinematic viscosity, and oil density. This ensures that the collected data comprehensively covers all key aspects of filter operation. According to the preset data acquisition types, the corresponding sensors and data acquisition modules are activated to collect multiple types of data from the dual-cylinder filter in real time and continuously, ensuring the real-time nature, completeness, and accuracy of the collected data. All collected data are integrated to obtain the filter acquisition data. Simultaneously, the preset data type benchmark data for the dual-cylinder filter is obtained. This benchmark data includes parameters such as the filter's rated differential pressure, rated flow rate, rated temperature, and standard oil viscosity under standard operating conditions. These parameters serve as reference standards for the normal operation of the filter. Benchmark parameters related to differential pressure are extracted from this data to obtain the filter differential pressure benchmark data. The collected filter data is compared item by item and from multiple dimensions with preset filter benchmark data. For each type of collected data, it is compared with the corresponding benchmark data, and the deviation between the two is calculated, forming multiple types of comparative data. This data can clearly reflect the difference between the current operating state of the filter and the standard state. Based on the multiple types of comparative data, a comprehensive multi-type comparative analysis is performed. The deviation of each comparative data is analyzed in depth to determine the rationality of the deviation and the cause of the deviation. Invalid deviation data caused by sensor failure or instantaneous operating condition fluctuations are eliminated. The analysis results of all valid comparative data are integrated to finally obtain the filter combined analysis data. This data can comprehensively and accurately reflect the actual operating state of the dual-cylinder filter, the degree of filter element contamination, and the deviation of various parameters.

[0028] This method effectively solves the technical deficiencies of traditional dual-cylinder filters in data acquisition and analysis. Traditional dual-cylinder filters typically only collect single differential pressure data, resulting in overly simplistic data collection that fails to comprehensively reflect the filter's operating status and the true condition of the filter element. This leads to misjudgments and omissions, causing issues such as malfunctioning controls and incorrect filter element replacements, increasing maintenance costs and system failure risks. This method addresses the problems of limited data acquisition and insufficient judgment criteria in traditional filters. By collecting multiple operating parameters and oil characteristic parameters, it comprehensively captures the filter's operating status, avoiding biased judgments due to limited data. It achieves multi-parameter collaborative judgment by comparing real-time acquired data with baseline data from multiple dimensions, enabling more accurate assessment of filter element contamination and abnormal filter operation, improving the accuracy and reliability of status identification. Furthermore, it enhances the intelligence level of the entire control system, achieving precise identification and quantitative analysis of filter status through standardized and regulated data acquisition and analysis processes.

[0029] In one embodiment of the present invention, the step of performing multi-class comparison analysis based on multi-class comparison data to obtain filter combination analysis data includes:

[0030] The difference between the inlet and outlet pressure data of each of the two cylinders is obtained by comparing various types of data to obtain the actual pressure difference data.

[0031] The difference between the two actual differential pressure data and the preset differential pressure threshold is obtained to obtain the differential pressure difference data;

[0032] Based on the pressure difference data, a pressure difference deviation determination is performed between the two cylinders to obtain pressure difference deviation determination information;

[0033] Obtain operational parameter comparison data based on multiple types of comparison data, and obtain operational parameter deviation judgment information based on operational parameter comparison data;

[0034] Deviation features are extracted from differential pressure deviation judgment information and operational deviation judgment information to obtain differential pressure deviation feature data and operational deviation feature data;

[0035] Calculate the correlation between the differential pressure deviation characteristic data and the operational deviation characteristic data to obtain the deviation correlation data;

[0036] The deviation correlation data is compared with a preset deviation correlation threshold to obtain the deviation correlation comparison result;

[0037] Based on the deviation correlation comparison results, deviation feature correlation is performed to obtain filter combination analysis data.

[0038] The working principle and technical effect of the above technical solution are as follows: This method accurately distinguishes between actual filter element contamination and parameter anomalies caused by operating condition fluctuations by extracting features and performing correlation analysis on differential pressure deviation and operating parameter deviation. It extracts the inlet and outlet pressure data of each of the two cylinders from various comparative data sets. By calculating the difference between the inlet and outlet pressures, the actual differential pressure data of each cylinder is obtained. This data directly reflects the degree of filter element clogging and the resistance of oil flow through the filter element. A preset differential pressure threshold is obtained. This threshold is pre-set based on the rated dirt-holding capacity of the filter element and the operating requirements of the filter, reflecting the differential pressure range for normal operation of the filter element. The difference between the two actual differential pressure data and the preset differential pressure threshold is calculated separately to obtain differential pressure difference data. This data clearly indicates the degree of deviation between the actual differential pressure of each cylinder and the standard differential pressure. Based on the differential pressure data, a differential pressure deviation judgment is performed on the dual-cylinder system to determine whether the differential pressure deviation is within a reasonable range. If the differential pressure exceeds the reasonable range, it is judged as an abnormal differential pressure deviation, thus obtaining differential pressure deviation judgment information, including the direction, magnitude, and degree of abnormality of the deviation. Simultaneously, comparative data of operating parameters such as flow rate, temperature, oil viscosity, and density are extracted from various types of comparative data; this is called operating parameter comparison data. The real-time acquired data of each operating parameter is compared with the corresponding benchmark data to determine whether the operating parameter deviates from the standard range, thus obtaining operating parameter deviation judgment information, including the deviation item, magnitude, and preliminary judgment of the cause of the deviation. Then, deviation feature extraction is performed on the differential pressure deviation judgment information and the operating deviation judgment information to extract the core features reflecting both types of deviation, forming differential pressure deviation feature data and operating deviation feature data. The differential pressure deviation feature data includes the rate of change and duration of the differential pressure deviation, while the operating deviation feature data includes the type of operating parameter deviation and the trend of the magnitude of the deviation. Then, using a preset correlation calculation method (such as grey relational analysis, Pearson correlation coefficient, etc.), the correlation degree between the differential pressure deviation characteristic data and the operational deviation characteristic data is calculated to obtain deviation correlation data. This data reflects the degree of correlation between differential pressure deviation and operational parameter deviation. If the correlation degree is high, it indicates that the differential pressure deviation is mainly caused by operational parameter deviation, rather than actual filter element blockage; if the correlation degree is low, it indicates that the differential pressure deviation is mainly caused by filter element blockage and is unrelated to operational parameter deviation. The deviation correlation data is compared with a preset deviation correlation threshold to obtain the deviation correlation comparison result. This result clarifies whether the correlation degree between differential pressure deviation and operational parameter deviation is within a reasonable range, thereby determining the core cause of the differential pressure abnormality. Based on the deviation correlation comparison result, deviation feature correlation is performed, correspondingly associating differential pressure deviation features with operational deviation features. All analysis results are integrated to finally obtain filter combined analysis data. This data accurately reflects the actual contamination state of the dual-cylinder filter element, the deviation of operational parameters, and the correlation between the two.

[0039] This method effectively solves the core technical challenge of differential pressure judgment in traditional dual-cylinder filters. Traditional dual-cylinder filters rely solely on a single differential pressure data point to determine the degree of filter element clogging during operation. This fails to distinguish between a genuine increase in differential pressure caused by actual filter element blockage ("true clogging") and a "false increase" caused by fluctuations in operating conditions such as flow rate, temperature, or oil viscosity. This often leads to erroneous adjustments, false alarms, and unnecessary filter element replacements due to these fluctuations, increasing maintenance costs and impacting system operation. This method addresses this issue through feature extraction and correlation analysis of differential pressure deviations and operational deviations.

[0040] In one embodiment of the present invention, S2 includes:

[0041] Information on the filter differential pressure change trend is obtained by combining filter data with analysis data.

[0042] Lifetime difference analysis is performed based on the filter differential pressure change trend information to obtain lifetime difference analysis data;

[0043] Based on the lifespan difference analysis data, lifespan equilibrium analysis is performed to obtain lifespan equilibrium analysis data.

[0044] Balance control analysis is performed based on lifespan difference analysis data and lifespan balance analysis data to obtain balance control analysis data.

[0045] The working principle and technical effect of the above technical solution are as follows: This method extracts real-time and historical differential pressure data of each of the dual-cylinder filter elements based on filter analysis data. Through data fitting, trend analysis, and other methods, it obtains information on the trend of differential pressure change in the filter. This information can clearly reflect the change law of differential pressure of the dual-cylinder filter elements over time, including the rate of increase of differential pressure, the stability of the upward trend, and whether there are abnormal fluctuations. The rate of increase of differential pressure is directly related to the degree of contamination and the rate of life decay of the filter element. The faster the differential pressure increases, the more serious the contamination of the filter element and the faster the life decay. Based on the filter differential pressure change trend information, a life difference analysis is performed. By comparing the rate of increase of differential pressure, the cumulative change of differential pressure, and the deviation characteristic changes of the dual-cylinder filter elements, the difference in the rate of life decay and the difference in remaining life between the two filter elements are determined. This clarifies whether there is a life imbalance between the two filter elements, and thus obtains life difference analysis data, which includes the magnitude of life difference, the distribution of difference, and the comparison of decay rates of the dual-cylinder filter elements. Based on the lifespan difference analysis data, a lifespan balancing analysis is performed. Combined with a preset lifespan balancing threshold, it is determined whether the lifespan difference of the dual-cylinder filter elements exceeds a reasonable range. If it does, it is judged as a lifespan imbalance. Simultaneously, the core causes of lifespan imbalance are analyzed in depth, including uneven flow distribution, differences in oil contamination load distribution, differences in the initial state of the filter elements, and fluctuations in operating parameters. The influence weight and severity of each imbalance cause are determined, and preliminary balancing adjustment directions and principles are formulated, ultimately obtaining lifespan balancing analysis data. Based on the lifespan difference analysis data and the lifespan balancing analysis data, a balancing control analysis is performed. Considering the operating conditions of the dual-cylinder filter and system control requirements, the balancing adjustment directions and principles from the lifespan balancing analysis data are transformed into specific balancing control strategies. The control objectives, control methods, control parameters, and control nodes are clarified to ensure that the control strategy can effectively offset the lifespan difference of the dual-cylinder filter elements, making the decay rates of the two filter elements tend to be consistent, ultimately obtaining balancing control analysis data.

[0046] The technical solution of this method effectively solves the core technical problem of life control in traditional dual-cylinder filters. Traditional dual-cylinder filters cannot judge the difference in the rate of life decay between the two filter elements, nor can they actively balance the life of the two filter elements. They can only passively wait for one filter element to become clogged to the final pressure difference before switching. This results in a serious imbalance in the life of the two filter elements. Often, one filter element will become clogged and fail prematurely and need to be replaced frequently, while the other filter element will still be in good condition and there will be a lot of idle waste. This not only increases the consumption and maintenance costs of the filter elements, but also causes system downtime due to frequent switching and maintenance, affecting the continuous and stable operation of the entire hydraulic system. This method solves the problems of traditional dual-cylinder filters, such as the inability to judge the difference in lifespan between the two filter elements, the inability to actively balance lifespan, and the problem of one cylinder clogging first while the other remains idle. It achieves early identification, accurate judgment, and proactive intervention of filter element lifespan imbalance; it improves the synchronicity of dual-cylinder filter element use. Through scientific balance analysis and control strategy formulation, it can effectively adjust the load distribution of the two filter elements, making the pressure difference rise rate and lifespan decay rate of the two filter elements tend to be consistent, achieving synchronous decay and synchronous use; it reduces the risk of premature failure of single-cylinder filter elements. Through proactive intervention and balance control, it avoids premature clogging and failure of single-cylinder filter elements due to excessive load and rapid contamination, thus extending the overall service life of the filter elements.

[0047] In one embodiment of the present invention, the step of performing lifespan difference analysis based on filter differential pressure change trend information to obtain lifespan difference analysis data includes:

[0048] Based on the filter and combined analysis data, the change data of differential pressure deviation characteristic data and operational deviation characteristic data are obtained, and the change data of differential pressure deviation characteristic data and operational deviation characteristic data are obtained.

[0049] Calculate the differences between the differential pressure deviation characteristic data and the operational deviation characteristic data and the differential pressure deviation characteristic change data and the operational deviation characteristic change data respectively, to obtain differential pressure change difference data and deviation change difference data;

[0050] Obtain the preset lifespan corresponding change threshold, and compare the preset lifespan corresponding change threshold with the differential pressure change difference data and the deviation change difference data to obtain lifespan comparison information;

[0051] Based on the lifespan comparison information, the filter pressure difference change trend information is used to determine the lifespan difference and obtain lifespan difference analysis data.

[0052] The working principle and technical effect of the above technical solution are as follows: This method extracts real-time change data of differential pressure deviation characteristic data and operational deviation characteristic data based on filter analysis data. These change data reflect the changing patterns and magnitudes of the two deviation characteristics over time, such as the rate of increase of the differential pressure deviation characteristic and the magnitude of the operational deviation characteristic. These change data are directly related to the filter element's lifespan decay rate. The differences between the differential pressure deviation characteristic data and the differential pressure deviation characteristic change data, and the differences between the operational deviation characteristic data and the operational deviation characteristic change data are calculated separately to obtain differential pressure change difference data and deviation change difference data. The differential pressure change difference data reflects the magnitude of the differential pressure deviation characteristic change, and the deviation change difference data reflects the magnitude of the operational deviation characteristic change. These two types of data can quantify the changes in the lifespan decay of the dual-cylinder filter element. A preset lifespan variation threshold is obtained. This threshold is pre-set based on the correlation between the filter element's rated lifespan, rated dirt holding capacity, differential pressure rise rate, and lifespan decay. It reflects the normal range of filter element lifespan decay. The preset lifespan variation threshold is compared one by one with differential pressure variation difference data and deviation variation difference data to determine whether the two types of difference data exceed the preset threshold range, thereby obtaining lifespan comparison information. This information includes the comparison results of the difference data with the preset threshold and whether there is any abnormal lifespan decay. Based on the lifespan comparison information, the filter differential pressure change trend information is used to determine the lifespan difference. Combining the differential pressure change trend, differential pressure variation difference, and deviation variation difference data of the dual-cylinder filter elements, the lifespan difference between the two-cylinder filter elements is quantified. It is determined whether there is a significant difference in the lifespan decay rate between the two-cylinder filter elements, whether there is a lifespan imbalance, and the core causes of the lifespan difference are identified, ultimately obtaining lifespan difference analysis data.

[0053] This method effectively solves the technical shortcomings of traditional dual-cylinder filters in judging lifespan differences. Traditional methods can only judge the degree of filter element contamination based on the current pressure difference, but cannot judge the rate of filter element lifespan decay or predict the remaining lifespan. They can only passively wait for the filter element to become clogged to the final pressure difference before replacement, often resulting in untimely control and filter element waste due to the inability to predict lifespan differences in advance. This method solves the problems of traditional methods that can only look at the current pressure difference and cannot judge the rate of filter element decay or predict the remaining lifespan. It achieves trend-based and predictive judgment of filter element lifespan differences, rather than single-point instantaneous judgment, enabling early detection of potential lifespan imbalances. It improves the foresight and accuracy of lifespan assessment. Through quantitative analysis of pressure difference deviation characteristics and operational deviation characteristics, it can accurately judge the difference in lifespan decay rate of dual-cylinder filters, predict the remaining lifespan of filters in advance, and allow sufficient time for balanced control, avoiding excessive filter element wear due to untimely control. It reduces the risk of sudden clogging. By identifying abnormal lifespan decay in advance, it can take timely control measures to avoid sudden failures caused by excessive filter element clogging, ensuring the normal operation of the system.

[0054] In one embodiment of the present invention, the step of performing lifetime balancing analysis based on the lifetime difference analysis data to obtain lifetime balancing analysis data includes:

[0055] The lifespan difference characteristics of the dual-cylinder filter element are determined based on the lifespan difference analysis data.

[0056] The life difference value of the dual-cylinder filter element is compared with the preset life balance judgment threshold based on the life difference characteristic information of the dual-cylinder filter element to obtain the dual-cylinder difference judgment information.

[0057] Determine the cause of lifespan imbalance based on the binocular difference assessment information;

[0058] By combining information on the difference between the two tubes with information on the causes of life imbalance, the influence weight of the causes of life imbalance and the severity of the imbalance data are determined.

[0059] Based on the influence weights of the causes of lifespan imbalance and the severity of the imbalance, combined with the filter operating parameter requirements, the balancing adjustment parameters are determined, and lifespan balance analysis data is obtained.

[0060] The working principle and technical effect of the above technical solution are as follows: This method extracts the core characteristics of the life difference of the dual-cylinder filter element based on the life difference analysis data, including the life difference amplitude, decay rate difference, and pressure difference trend difference, etc., to clarify the specific manifestation of the life difference of the dual-cylinder filter element, and thus determine the life difference characteristic information of the dual-cylinder filter element. This information can comprehensively reflect the specific situation of the life imbalance of the dual-cylinder filter element. Based on the life difference characteristic information of the dual-cylinder filter element, the life difference value of the dual-cylinder is extracted and compared with a preset life balance judgment threshold. The preset life balance judgment threshold is pre-set according to the operating requirements, filter element specifications, and system reliability requirements of the dual-cylinder filter, and can reflect the reasonable range of life balance of the dual-cylinder filter element. By comparison, it is determined whether the life difference of the dual-cylinder filter element exceeds the reasonable range. If it exceeds the range, it is judged as life imbalance; if it is within the range, it is judged as life balance. Thus, the dual-cylinder difference judgment information is obtained, which includes the judgment result of whether the life imbalance exists and the magnitude of the imbalance. Based on the dual-cylinder difference assessment information, the causes of lifespan imbalance are determined. Combining filter analysis data, differential pressure deviation data, and operational deviation data, a thorough analysis of the core causes of lifespan imbalance is conducted. These include, but are not limited to, uneven flow distribution between the two cylinders, differences in oil contamination load distribution, initial filter element installation accuracy deviations, differences in filter element manufacturing processes, and fluctuations in operating parameters. The specific manifestations and impact range of each imbalance cause are clarified. Then, using the dual-cylinder difference assessment information combined with the lifespan imbalance cause information, a preset weighting calculation method is employed to determine the influence weight of each lifespan imbalance cause. This identifies which cause is the primary factor leading to lifespan imbalance and quantifies the severity of the lifespan imbalance, determining whether it will affect the normal operation of the system and whether immediate adjustment is necessary. Based on the influence weights and severity data of the lifespan imbalance causes, and considering the filter's operating parameter requirements (such as rated flow rate, rated pressure, target cleanliness, etc.), targeted balancing adjustment parameters are determined. These include flow distribution ratios, adjustment amplitudes, and adjustment timings. This ensures that the adjustment parameters effectively resolve the lifespan imbalance problem, making the lifespan decline of the dual-cylinder filter elements more uniform, ultimately obtaining lifespan balancing analysis data.

[0061] This method effectively solves the technical challenges of lifespan balancing analysis in traditional dual-cylinder filters. Even if traditional dual-cylinder filters can detect differences in the lifespan of the two filter cartridges, they cannot accurately pinpoint the root cause of the imbalance or quantify its severity. This leads to a lack of targeted and often ineffective adjustments, resulting in repeated and inefficient adjustments that fail to address the lifespan imbalance problem and still result in filter cartridge waste and high maintenance costs. This method, through precise lifespan balancing analysis, solves the problems of traditional dual-cylinder filters not knowing why the imbalance occurs, not accurately locating the root cause, and having ineffective adjustments. It achieves the ability to locate, quantify, and analyze lifespan imbalances; it improves the targeting and effectiveness of control strategies. By identifying the core causes and influencing weights of lifespan imbalance, targeted balancing adjustment parameters can be formulated, avoiding ineffective and repeated adjustments, improving control efficiency, and enabling the dual-cylinder filter cartridges to quickly return to a balanced state; it reduces control costs and maintenance workload. By accurately locating the root cause of the imbalance, it avoids the waste of resources caused by ineffective adjustments, reduces the workload of maintenance personnel, and improves maintenance efficiency.

[0062] In one embodiment of the present invention, the step of performing equilibrium control analysis based on lifetime difference analysis data and lifetime equilibrium analysis data to obtain equilibrium control analysis data includes:

[0063] Determine the equilibrium adjustment target and its parameters based on the lifetime difference analysis data;

[0064] Multiple control nodes and their parameters are determined based on the equilibrium control objective;

[0065] The corresponding offsetting node is determined based on multiple control nodes;

[0066] Determine the corresponding cancellation parameters based on the corresponding cancellation node;

[0067] Determine the target control node and its parameters based on the corresponding offset node and corresponding offset parameters;

[0068] Equilibrium control is carried out based on the target control node and its parameters to obtain equilibrium control analysis data.

[0069] Simple examples include:

[0070] Based on the lifespan difference analysis data, the balance adjustment target and its parameters were determined: The lifespan difference analysis showed that the lifespan decay rate of cartridge A was 30% faster than that of cartridge B. The balance adjustment target was determined to make the decay rates of the two cartridges more consistent. The parameters were set to reduce the decay rate of cartridge A by 15% and increase the decay rate of cartridge B by 15%, so that the difference in the decay rate between the two cartridges was ≤5%.

[0071] Based on the equilibrium adjustment target, multiple control nodes and their parameters are determined: around the adjustment target, two core control nodes (flow control node and pressure control node) are determined, and the parameters are set as follows: initial flow rate of cylinder A is 10L / min, initial flow rate of cylinder B is 10L / min, and control pressure threshold is 0.3-0.5MPa;

[0072] Based on multiple control nodes, corresponding offset nodes are determined: for flow control nodes, the node where the flow rate of cylinder A decreases and the node where the flow rate of cylinder B increases are determined as offset nodes; for pressure control nodes, the pressure fine-tuning point of cylinder A and the pressure fine-tuning point of cylinder B are determined as offset nodes.

[0073] The corresponding offset parameters are determined based on the corresponding offset nodes: the offset parameter for the flow rate reduction node of cylinder A is a flow rate decrease of 2L / min, and the offset parameter for the flow rate increase node of cylinder B is a flow rate increase of 2L / min; the offset parameters for the pressure fine adjustment points of both cylinders are ±0.05MPa.

[0074] Based on the corresponding offsetting nodes and corresponding offsetting parameters, the target control nodes and their parameters are determined: the flow control node is selected as the core target control node, and the parameters are updated to A cylinder flow rate of 8L / min and B cylinder flow rate of 12L / min. The pressure control node is used as an auxiliary node, and the parameters are maintained within the threshold range.

[0075] Balanced control is performed based on the target control node and its parameters to obtain balanced control analysis data: the flow rate of the two cylinders is controlled according to the updated flow parameters, the attenuation rate of the two cylinders is monitored in real time, and finally balanced control analysis data with the attenuation rate difference between the two cylinders ≤5% and meeting the balance target is obtained.

[0076] The working principle and technical effects of the above technical solution are as follows: Based on the lifespan difference analysis data, this method clarifies the core information such as the lifespan difference amplitude and decay rate difference of the dual-cylinder filter element. Combined with the balance adjustment parameters and adjustment targets in the lifespan balance analysis data, the balance adjustment target and its parameters are determined. The core of the balance adjustment target is to make the pressure difference rise rate and lifespan decay rate of the dual-cylinder filter element tend to be consistent, achieving synchronous use and synchronous replacement. The balance adjustment parameters include the target pressure difference value and the target decay rate. Based on the balance adjustment target, combined with the operating conditions of the dual-cylinder filter and system control requirements, multiple control nodes and their parameters are determined. Control nodes refer to key operating nodes that can achieve lifespan balance control, including flow control nodes and pressure control nodes. Each control node corresponds to specific control parameters, such as the flow ratio parameter corresponding to the flow control node and the pressure threshold parameter corresponding to the pressure control node. Through the synergistic effect of multiple control nodes, comprehensive control of lifespan differences is achieved. Based on multiple control nodes and considering the lifespan differences and imbalance causes of the dual-tube filter cartridges, corresponding offsetting nodes are determined. These offsetting nodes are key points that can compensate for the lifespan differences between the two cartridges, corresponding one-to-one with the control nodes. Their core function is to compensate for the lifespan differences between the two cartridges through targeted adjustments. For example, for a cartridge with a faster pressure differential increase and faster lifespan decay, the corresponding offsetting node is to reduce its flow rate; for a cartridge with a slower pressure differential increase and slower lifespan decay, the corresponding offsetting node is to increase its flow rate. Then, based on the corresponding offsetting nodes and data such as the magnitude of the lifespan difference and the severity of the imbalance, corresponding offsetting parameters are determined. These offsetting parameters refer to the specific adjustment range and frequency of the offsetting nodes, such as the adjustment ratio and frequency of the flow rate, ensuring that the offsetting parameters can accurately compensate for the lifespan differences and make the decay rates of the two cartridges tend to be consistent. Then, based on the corresponding offset nodes and their corresponding offset parameters, the initially set multiple control nodes and their parameters are optimized and adjusted. Ineffective control nodes are eliminated, control parameters are optimized, and the final target control node and its parameters are determined. The target control node refers to the key node that can achieve the best equilibrium control effect, and its parameters can accurately match the offset nodes and offset parameters to ensure the feasibility and effectiveness of the control strategy. Based on the target control node and its parameters, a specific equilibrium control execution process is formulated, clarifying the order of control, execution timing, feedback mechanism, etc. The equilibrium control operation is executed, the control effect is tracked in real time, and the control parameters are adjusted in a timely manner based on the control feedback. Finally, equilibrium control analysis data is obtained, which includes the target control node, control parameters, control process, feedback mechanism, etc.

[0077] This method solves the core technical problems of inconsistent lifespan rates, inability to actively offset differences, and difficulty in synchronized aging of dual-cylinder filter elements. It achieves active offsetting, dynamic balancing, and precise adjustment of lifespan differences, fundamentally solving the lifespan imbalance problem. It enables synchronized attenuation, use, and replacement of dual-cylinder filter elements, significantly improving the synchronized utilization rate of dual-cylinder filter elements and making the load distribution between the two filter elements more even, avoiding the phenomenon of excessive wear of one filter element and idle waste of the other. It improves the accuracy and effectiveness of balancing control. By setting control nodes, offset nodes, and offset parameters, it can specifically compensate for lifespan differences, ensuring the accuracy and durability of the control effect and avoiding ineffective and repeated control.

[0078] In one embodiment of the present invention, S3 includes:

[0079] The system oil cleanliness information is obtained based on the balanced control data, and the system oil cleanliness analysis is performed based on the system oil cleanliness information to obtain oil cleanliness analysis data.

[0080] Based on the oil cleaning analysis data, the filter oil cleaning is adjusted to obtain oil cleaning adjustment data;

[0081] The equilibrium control data is updated based on the oil cleaning adjustment data to obtain updated control data.

[0082] Based on the updated control data, filter life decay data is obtained, and life analysis and early warning are performed to obtain life analysis and early warning data.

[0083] The working principle and technical effect of the above technical solution are as follows: Based on the balanced control analysis data obtained by S2, this method extracts core information such as target control nodes and control parameters. Combined with the preset oil cleanliness acquisition specifications, the oil cleanliness acquisition module is activated to collect the oil at the outlet side of the dual-cylinder filter in real time, obtaining system oil cleanliness information. This information includes the number of particles of different sizes in the oil, particle distribution density, cleanliness level, etc., which can reflect the degree of oil contamination. Based on the system oil cleanliness information, system oil cleanliness analysis is performed. The collected oil cleanliness information is compared with the preset target cleanliness level standard (such as ISO 4406:1999, SAE AS 4059 related standards), and the deviation between the current oil cleanliness and the target cleanliness is analyzed to determine whether the oil cleanliness meets the system operation requirements, thereby obtaining oil cleanliness analysis data. This data includes the cleanliness deviation range, preliminary judgment of the cause of the deviation, etc. Based on the oil cleanliness analysis data, the filter oil cleanliness is adjusted. If the current oil cleanliness meets the target requirements, the current balanced control state is maintained, and changes in cleanliness are continuously monitored. If the current oil cleanliness does not meet the target requirements, the core reasons for the unacceptable cleanliness are analyzed, and targeted cleaning adjustment measures are taken, such as adjusting the filter element's operating mode, increasing the flow rate, and activating auxiliary filtration devices, to ensure that the oil cleanliness quickly recovers to the target level. This results in oil cleanliness adjustment data, including the cleaning adjustment measures, adjustment parameters, and adjustment timing. Subsequently, the balanced control data is updated based on the oil cleanliness adjustment data. Combining the cleaning adjustment measures and adjustment parameters, the original balanced control strategy is optimized, and the target control nodes and control parameters are adjusted to ensure that balanced control and cleanliness control are carried out in tandem, avoiding the impact of cleanliness adjustments on the filter element's lifespan balance. Finally, updated control data is obtained. Based on the updated control data, the real-time operating parameters, differential pressure change data, and cleanliness change data of the dual-cylinder filter element are extracted. Combined with parameters such as the rated life and dirt holding capacity of the filter element, the life decay of the filter element is analyzed, the remaining life of the filter element is calculated, and a life warning threshold is set. When the remaining life of the filter element is lower than the warning threshold, a life warning signal is issued to remind the staff to perform filter element maintenance or replacement, thereby obtaining life analysis and warning data.

[0084] The technical solution of this method effectively solves the technical problem that the life balance control and oil cleanliness control are independent and cannot be coordinated in traditional dual-cylinder filters. Traditional dual-cylinder filters often only focus on the replacement of filter element life and ignore the control of oil cleanliness, or only monitor cleanliness separately without linking it with life control, which leads to problems such as insufficient filtration (oil cleanliness does not meet the standard, wear and tear on system components) or over-filtration (excessive wear of filter element, increased cost). At the same time, it cannot achieve accurate life warning, and often the system failure is caused by sudden blockage of filter element. This method, through coordinated closed-loop control, solves the problems of independent and uncoordinated lifespan balancing and oil cleanliness control, which can easily lead to insufficient or excessive filtration. It achieves bidirectional coordination and closed-loop optimization of lifespan balancing and cleanliness assurance, ensuring that while achieving filter element lifespan balancing, oil cleanliness always meets system operating requirements. It improves the stability of system cleanliness by effectively controlling particulate contamination in the oil through real-time monitoring and targeted cleaning adjustments, avoiding wear on core components such as system valves, pumps, and motors caused by substandard oil cleanliness, and extending the service life of system components. It also ensures balanced use of filter elements by coordinating cleanliness adjustment and balancing control, avoiding filter element lifespan imbalance caused by cleanliness adjustments, and ensuring that both filter cartridges are always in a state of synchronous decay.

[0085] In one embodiment of the present invention, the step of obtaining system oil cleanliness information based on balanced control data, and performing system oil cleanliness analysis based on the system oil cleanliness information to obtain oil cleanliness analysis data includes:

[0086] By extracting balanced control analysis data and combining it with preset oil cleanliness collection specifications, particle counting is performed on the oil at the outlet side of the dual-cylinder filter to obtain system oil cleanliness information.

[0087] The system oil cleanliness information is compared with the preset target cleanliness level standard to obtain cleanliness deviation data;

[0088] Determine the correlation between cleanliness deviation data and filter combination analysis data to identify the core causes of cleanliness deviation;

[0089] The cleanliness deviation data is used to determine the current cleanliness level of the oil, and the pass / fail status information is obtained.

[0090] The qualification assessment information is the oil cleaning analysis data.

[0091] The working principle and technical effect of the above technical solution are as follows: This method extracts core information such as target control node parameters, balance adjustment parameters, and dual-cylinder filter element operating status data from the balance control analysis data. Combined with the preset oil cleanliness collection specifications, it clarifies the requirements for oil cleanliness collection location, collection frequency, and collection method. Among them, the collection location is preferentially selected at the outlet side of the dual-cylinder filter to ensure that the collected oil cleanliness information can truly reflect the degree of oil contamination after filtration. The oil particle counting collection device is started, and the oil at the outlet side of the dual-cylinder filter is counted and collected according to the preset collection specifications to obtain the system oil cleanliness information. This information includes core contents such as the number of particles of different sizes in the oil, particle distribution density, and cleanliness level, which can comprehensively reflect the contamination status of the oil. A preset target cleanliness level standard is obtained. This standard is pre-set based on the operating requirements of the hydraulic system, the precision requirements of system components, and industry standards (such as ISO 4406:1999 and SAE AS 4059). It clearly defines the oil cleanliness level required for normal system operation. The collected system oil cleanliness information is compared item by item with the preset target cleanliness level standard to calculate the deviation between the current cleanliness level and the target cleanliness level, obtaining cleanliness deviation data. This data clearly reflects the degree of deviation in oil cleanliness. Next, the correlation between the cleanliness deviation data and the filter integration analysis data is determined. Combining the pressure difference deviation characteristic data, operational deviation characteristic data, and deviation correlation data in the filter integration analysis data, a deeper analysis is conducted on the correlation between cleanliness deviation and the pressure difference deviation and operational parameter deviation of the dual-cylinder filter element. This identifies the core causes of cleanliness deviation, clarifying whether the unqualified cleanliness is caused by a decrease in filtration efficiency due to an imbalance in the lifespan of the dual-cylinder filter element, excessive oil contamination load, or poor filtration effect due to operational parameter deviation. The cleanliness deviation data is used to determine the current cleanliness of the oil. If the cleanliness deviation is within a reasonable range and meets the preset target cleanliness level standard, the cleanliness is deemed qualified. If the cleanliness deviation exceeds a reasonable range and does not meet the preset target cleanliness level standard, the cleanliness is deemed unqualified. The severity of the unqualification is also determined to obtain the qualification determination information, which is the oil cleanliness analysis data.

[0092] This method solves the problems of isolated cleanliness monitoring, inability to determine the source of contamination, and lack of linkage with filter element status. It enables traceability, correlation, and prediction of cleanliness anomalies, and can accurately pinpoint the core causes of unacceptable cleanliness. It improves the accuracy of cleanliness control by identifying the core causes of cleanliness deviations, allowing for targeted cleaning adjustment measures to avoid blind adjustments and ineffective maintenance, and ensuring that oil cleanliness quickly recovers to the target level. It also avoids the decline in filtration efficiency caused by filter element life imbalance. By correlating cleanliness deviations with filter element status (pressure difference deviation, operational deviation), it can promptly detect poor filtration performance caused by filter element life imbalance, and take balancing control measures in advance to ensure filtration efficiency.

[0093] In one embodiment of the present invention, the system includes:

[0094] The combined analysis module is used to collect data from the dual-cylinder filter, obtain filter collection data, acquire filter differential pressure reference data, and combine and analyze the filter differential pressure reference data with the filter collection data to obtain filter combined analysis data.

[0095] The equalization analysis module is used to perform filter cartridge life equalization analysis based on the filter and analysis data to obtain life equalization analysis data, and to perform equalization control analysis based on the life equalization analysis data to obtain equalization control analysis data.

[0096] The cleaning analysis module is used to perform cleaning analysis and control based on the balanced control analysis data, obtain updated control data, and perform lifespan analysis and early warning based on the updated control data, thereby obtaining lifespan analysis and early warning data.

[0097] The working principle and technical effects of the above-mentioned technical solution are as follows: This system comprehensively collects data from the dual-cylinder filter, covering the operating parameters, pressure parameters, and oil characteristic parameters of each cylinder. Simultaneously, it acquires preset filter differential pressure benchmark data. This benchmark data is pre-calibrated based on the filter's rated operating conditions, filter element rated parameters, and industry standards, reflecting the differential pressure range under normal filter operation. The real-time collected filter data is combined with the differential pressure benchmark data for multi-dimensional and comprehensive analysis, eliminating invalid data interference and integrating effective information to ultimately obtain filter combined analysis data that comprehensively reflects the dual-cylinder filter's operating status, filter element contamination level, and parameter deviations. Based on the filter combined analysis data, the differential pressure change pattern of the dual-cylinder filter elements is deeply extracted, and then filter element life balancing analysis is conducted to accurately determine the life differences and decay rate differences between the dual-cylinder filter elements, forming life balancing analysis data. Then, combined with the life balancing analysis data, targeted balancing control analysis is performed to formulate balancing control strategies that meet actual operating conditions, clarifying the control direction, control parameters, and control methods, and obtaining balancing control analysis data. By using the obtained balanced control analysis data, the cleanliness of the system oil is monitored and comprehensively analyzed in real time to determine whether the current oil cleanliness meets the system's operating requirements. If not, targeted cleanliness control is performed to obtain oil cleanliness adjustment data. Then, the original balanced control data is dynamically updated based on the oil cleanliness adjustment data to obtain updated control data. Based on the updated control data, the lifespan decay of the dual-cylinder filter element is tracked in real time, and accurate lifespan analysis and early warning are performed to obtain lifespan analysis and early warning data. This promptly reminds staff to maintain or replace the filter element, ensuring that the entire control process forms a closed loop and continuously guarantees the balanced lifespan of the dual-cylinder filter element.

[0098] This method fundamentally solves many technical problems in the control of filter element life in traditional dual-cylinder filters. Traditional dual-cylinder filters generally adopt a passive control mode of "final pressure differential trigger switching," which can only trigger switching when one filter element becomes clogged to a certain extent. It cannot predict the difference in lifespan between the two filter elements in advance, nor can it actively intervene in the rate of filter element decay. This results in a serious imbalance in the lifespan of the two filter elements, often with one filter element becoming clogged and failing prematurely, requiring frequent replacement, while the other filter element remains in good condition, resulting in a large amount of idle waste. This not only increases the consumption and maintenance costs of filter elements, but also causes system downtime due to frequent switching and maintenance, affecting the continuous and stable operation of the entire hydraulic system. This method, by constructing a complete closed-loop control system, achieves active and balanced control of the lifespan of dual-cylinder filter elements, effectively solving the above-mentioned technical problems.

[0099] Example 2:

[0100] To further address the problem that dual-cylinder filters are prone to misjudging operational disturbances as actual filter element blockage under fluctuating operating conditions, leading to inaccurate assessment of lifespan differences, insufficient targeted balancing control, and potential fluctuations in outlet oil cleanliness due to a simple pursuit of lifespan balance, this paper proposes a dual-cylinder filter element lifespan balancing control method based on the separation of actual blockage contributions.

[0101] In this embodiment, the dual-cylinder filter includes cylinder A and cylinder B. Both cylinders are equipped with inlet pressure acquisition units, outlet pressure acquisition units, flow rate acquisition units, operating temperature acquisition units, and oil kinematic viscosity acquisition units. An oil particle counting acquisition unit is installed on the outlet side. Differential pressure reference data and operating parameter reference data are pre-established based on the rated operating conditions of the dual-cylinder filter. The initial flow rate of both cylinder A and cylinder B is set to 10 L / min, and the pressure control threshold is maintained within the range of 0.3 MPa to 0.5 MPa. The target oil cleanliness level standard adopts a preset target cleanliness level standard. The parameter types, control node types, and cleanliness acquisition locations are all consistent with those in Embodiment 1.

[0102] The implementation plan includes the following steps:

[0103] S21. Collect inlet pressure, outlet pressure, flow rate, operating temperature, and oil kinematic viscosity data for cylinders A and B within the current sampling period nnn, and calculate the actual pressure difference data for cylinders A and B respectively; compare the actual pressure difference data, flow rate data, operating temperature data, and oil kinematic viscosity data with the corresponding pressure difference reference data and operating parameter reference data to obtain the pressure difference deviation, flow rate deviation, temperature deviation, and viscosity deviation for cylinders A and B respectively; based on this, extract the pressure difference deviation characteristic data and operating deviation characteristic data for cylinders A and B respectively, and retain the corresponding data from the previous sampling period n−1 to form the basic dataset required for subsequent life difference analysis and balance control update.

[0104] S22. Based on the deviation obtained in step S21, calculate the actual blockage characterization for cylinder A and cylinder B respectively, where the actual blockage characterization for cylinder A in sampling period n is denoted as R. A (n), the actual blockage characteristic of cylinder B during sampling period n is denoted as R. B (n), and their calculation methods are as follows:

[0105]

[0106]

[0107] Where, ΔP A (n) and ΔP B(n) represents the pressure difference deviation of cylinders A and B relative to the pressure difference reference data during the sampling period n; ΔQ A (n) and ΔQ B (n) represent the flow deviations of cylinders A and B relative to the reference flow rate data; ΔQ A (n) and ΔQ B (n) represent the viscosity deviations of cylinders A and B relative to the reference data for the kinematic viscosity of the oil, respectively; ΔT A (n) and ΔT B (n) represent the temperature deviations of cylinders A and B relative to the operating temperature reference data, respectively; α, β, and γ are preset compensation coefficients used to characterize the influence weights of flow rate, oil kinematic viscosity, and operating temperature on pressure difference deviation.

[0108] Through the above processing, the portion of the original differential pressure deviation caused by operating condition fluctuations is subtracted, thereby obtaining a more accurate measure of the filter element's true clogging level. If R A (n) and R B If one of (n) is significantly higher than the other, it is preliminarily determined that the corresponding filter element bears a higher actual pollution load. The original application has disclosed that it distinguishes between "true blockage" and "false pressure increase caused by operating condition fluctuation" by feature extraction and correlation analysis of pressure difference deviation and operating deviation.

[0109] S23. Based on the actual blockage characterization obtained in step S22, and combined with the actual blockage characterization of the previous sampling period, calculate the life imbalance characterization value E for cylinder A and cylinder B respectively. A (n) and E B (n), and further calculate the twin-tube life imbalance coefficient K(n), which is calculated as follows:

[0110]

[0111]

[0112]

[0113] Wherein, λ1 and λ2 are preset weighting coefficients, λ1 is used to characterize the degree of influence of the current actual blockage load on the life decay, and λ2 is used to characterize the degree of influence of the actual blockage change rate on the life decay; K(n) is used to characterize the direction and magnitude of the life imbalance between cylinder A and cylinder B.

[0114] When K(n) is greater than the preset life balance judgment threshold, it is determined that the lifespan of filter element A decays faster than that of filter element B; when K(n) is less than the opposite threshold of the preset life balance judgment threshold, it is determined that the lifespan of filter element B decays faster than that of filter element A; when K(n) is within the preset threshold range, it is determined that the dual-filter elements are in an acceptable lifespan balance state. In this embodiment, the actual clogging contribution is first separated, and then a lifespan imbalance coefficient is generated, so that subsequent balance control is no longer directly based on the original pressure difference without the influence of the stripped operating conditions.

[0115] S24. When the lifetime imbalance coefficient K(n) obtained in step S23 exceeds the preset lifetime balance judgment threshold, the balance adjustment target and its parameters are determined according to the lifetime imbalance direction, and the target control node and its parameters are generated in the manner of "priority of flow control node and assistance of pressure control node".

[0116] Specifically, when K(n) is greater than a preset threshold, cylinder A is identified as having a faster lifespan decay, and cylinder B is identified as having a slower lifespan decay. The flow rate distribution between cylinders A and B is adjusted preferentially, causing the flow rate in cylinder A to decrease and the flow rate in cylinder B to increase. When K(n) is less than the opposite threshold, flow rate control in the opposite direction is performed. To maintain consistency with the balanced control logic of Example 1, this example still preferentially selects the flow rate control node as the core target control node and the pressure control node as the auxiliary target control node.

[0117] Taking the example of faster life decay in cylinder A, with an initial flow rate of 10 L / min, the target flow rate of cylinder A can be lowered to 8 L / min, while the target flow rate of cylinder B can be increased to 12 L / min. The pressure fine-tuning parameters for both cylinders are controlled within ±0.05 MPa to form the first round of balanced control analysis data. The direction and source of this control are consistent with the balanced control node, offset node, and offset parameter settings in Example 1, but its triggering basis, based on the general life difference analysis in Example 1, further converges to being driven by the life imbalance coefficient obtained after separating the actual blockage contribution. S25

[0118] After the first round of equalization control is completed in step S24, particle counting is performed on the oil at the outlet side of the dual-cylinder filter to obtain the system oil cleanliness information. The current system oil cleanliness information is then compared with the preset target cleanliness level standard to obtain the cleanliness deviation C. err Based on this, the core causes of cleanliness deviation are determined by combining the differential pressure deviation characteristic data and operation deviation characteristic data obtained in step S21 with the life imbalance coefficient K(n) obtained in step S23.

[0119] When the core cause of cleanliness deviation is a decrease in filtration efficiency due to lifespan imbalance, the cleanliness deviation amount C is...err (n) serves as the basis for feedback correction of the target control node parameters in step S24; when the core cause of the cleanliness deviation is a short-term increase in system contamination load or other abnormal operating parameters, the current equilibrium control direction remains unchanged, and only auxiliary cleaning adjustment measures are corrected to avoid incorrectly introducing non-life-cycle factors into the life-cycle equilibrium control chain. The original application has clearly disclosed: System oil cleanliness analysis is performed based on system oil cleanliness information to obtain oil cleanliness analysis data; filter oil cleanliness is adjusted based on the oil cleanliness analysis data; and the equilibrium control data is updated based on the oil cleanliness adjustment data.

[0120] S26

[0121] Based on the cleanliness deviation C obtained in step S25 err (n) Update the target flow rates of cylinders A and B, where the updated target flow rate of cylinder A is... And the updated target flow rate of tube B They can be represented as:

[0122]

[0123]

[0124] Among them, Q A,0 (n) and Q B,0 (n) represent the initial target flow rates of cylinder A and cylinder B generated in step S24, respectively; δ is the lifetime balance adjustment coefficient, used to characterize the influence of the lifetime imbalance coefficient on the target flow rate update magnitude; η is the cleanliness feedback correction coefficient, used to characterize the influence of the cleanliness deviation on the target flow rate update magnitude.

[0125] When the lifespan of cylinder A deteriorates rapidly and the cleanliness of the outlet side fails to meet the target level requirements, the actual contamination burden of cylinder A is further reduced through the aforementioned renewal method, while increasing the proportion of contamination handled by cylinder B, thus balancing lifespan equilibrium and cleanliness recovery; when the lifespan of cylinder A deteriorates rapidly but the current cleanliness meets the target level requirements, then ηC err The correction effect of term (n) on the target flow rate is weakened or not triggered, and the system mainly relies on term δK(n) to achieve lifetime equalization update.

[0126] After completing the target throughput update, proceed according to the updated... and The system performs the dual-cylinder flow distribution for the next sampling cycle and continues to collect the differential pressure deviation characteristics, operational deviation characteristics, and outlet cleanliness information of the two cylinders until the life imbalance coefficient K(n) falls back to the preset life balance judgment threshold range and the system oil cleanliness is restored to the preset target cleanliness level standard range, thereby obtaining updated control data and life analysis early warning data.

[0127] In this embodiment, when K(n) continuously exceeds the preset life balance judgment threshold for multiple consecutive sampling periods, and fails to fall back to the preset range after at least one round of target flow rate update based on cleanliness feedback, it is determined that the current dual-cylinder filter element has a risk of continuous life imbalance, and life analysis early warning data is generated; when the actual blockage characterization of one cylinder continuously increases, and the cleanliness deviation on the outlet side deteriorates synchronously, the cylinder is further identified as a priority maintenance object, and the corresponding filter element maintenance or replacement early warning signal is output to the maintenance end.

[0128] The working principle and technical effects of this embodiment are as follows: First, it uses multi-parameter acquisition and correlation analysis of differential pressure deviation and operational deviation, but does not directly use the original differential pressure deviation results for life difference determination. Instead, it first separates the operating condition disturbances such as flow rate, temperature, and oil kinematic viscosity from the differential pressure deviation through real blockage characterization quantities, so that the life imbalance analysis of the dual-cylinder filter element is based on a basis closer to the actual pollution load of the filter element. On this basis, the actual blockage degree and its changing trend are mapped to the equilibrium control chain through the life imbalance coefficient, so that the generation of target control nodes and their parameters has a clear, single, and continuous driving source, avoiding the malfunction caused by the instantaneous fluctuation of the original differential pressure directly triggering the equilibrium control. Furthermore, this embodiment introduces the outlet side oil cleanliness deviation as a feedback update quantity for the target flow rate, so that cleanliness analysis and control are no longer additional actions independent of life balance, but directly participate in the update process of target control node parameters, ultimately forming a closed-loop control mechanism of real blockage contribution separation, life imbalance judgment, target control node generation, cleanliness feedback correction, and life warning output. Therefore, this embodiment can not only further reduce the risk of misjudgment caused by operating condition fluctuations and improve the accuracy of identifying differences in the lifespan of the dual-cylinder filter elements, but also dynamically, continuously, and specifically balance and regulate the load distribution of the dual-cylinder filter elements while ensuring that the cleanliness of the outlet oil meets the system requirements. This further enhances the synchronous decay effect of the dual-cylinder filter elements, the overall utilization rate, and the continuous and stable operation capability of the system.

[0129] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for balancing the lifespan of a dual-cylinder filter element, characterized in that, The method includes: S1. Collect data from the dual-cylinder filter to obtain filter data collection data and filter differential pressure reference data. Combine and analyze the filter differential pressure reference data with the filter data collection data to obtain filter combined analysis data. S2. Based on the filter and combined analysis data, perform filter element life balance analysis to obtain life balance analysis data. Based on the life balance analysis data, perform balance control analysis to obtain balance control analysis data. S3. Based on the balanced control analysis data, perform cleanliness analysis and control to obtain updated control data. Based on the updated control data, perform lifespan analysis and early warning to obtain lifespan analysis and early warning data.

2. The method for balancing the lifespan of a dual-cylinder filter element according to claim 1, characterized in that, S1 includes: Obtain preset data collection type information, and perform multiple types of data collection on the dual-barrel filter according to the preset data collection type information to obtain filter collection data; Obtain the preset data type reference data of the dual-cylinder filter and obtain the filter differential pressure reference data; The filter-collected data is compared with the filter baseline data in multiple categories to obtain multiple categories of comparison data. Multi-class comparative analysis is performed based on multi-class comparative data to obtain filter-combined analysis data.

3. The method for balancing the lifespan of a dual-cylinder filter element according to claim 2, characterized in that, The step of performing multi-class comparison analysis based on multi-class comparison data to obtain filter-combined analysis data includes: The difference between the inlet and outlet pressure data of each of the two cylinders is obtained by comparing various types of data to obtain the actual pressure difference data. The difference between the two actual differential pressure data and the preset differential pressure threshold is obtained to obtain the differential pressure difference data; Based on the pressure difference data, a pressure difference deviation determination is performed between the two cylinders to obtain pressure difference deviation determination information; Obtain operational parameter comparison data based on multiple types of comparison data, and obtain operational parameter deviation judgment information based on operational parameter comparison data; Deviation features are extracted from differential pressure deviation judgment information and operational deviation judgment information to obtain differential pressure deviation feature data and operational deviation feature data; Calculate the correlation between the differential pressure deviation characteristic data and the operational deviation characteristic data to obtain the deviation correlation data; The deviation correlation data is compared with a preset deviation correlation threshold to obtain the deviation correlation comparison result; Based on the deviation correlation comparison results, deviation feature correlation is performed to obtain filter combination analysis data.

4. The method for balancing the lifespan of a dual-cylinder filter element according to claim 1, characterized in that, S2 includes: Information on the filter differential pressure change trend is obtained by combining filter data with analysis data. Lifetime difference analysis is performed based on the filter differential pressure change trend information to obtain lifetime difference analysis data; Based on the lifespan difference analysis data, lifespan equilibrium analysis is performed to obtain lifespan equilibrium analysis data. Balance control analysis is performed based on lifespan difference analysis data and lifespan balance analysis data to obtain balance control analysis data.

5. The method for balancing the lifespan of a dual-cylinder filter element according to claim 4, characterized in that, The step of performing lifespan difference analysis based on filter differential pressure change trend information to obtain lifespan difference analysis data includes: Based on the filter and combined analysis data, change data of differential pressure deviation characteristic data and operational deviation characteristic data are obtained, and change data of differential pressure deviation characteristic data and operational deviation characteristic data are obtained. Calculate the differences between the differential pressure deviation characteristic data and the operational deviation characteristic data and the differential pressure deviation characteristic change data and the operational deviation characteristic change data respectively, to obtain differential pressure change difference data and deviation change difference data; Obtain the preset lifespan corresponding change threshold, and compare the preset lifespan corresponding change threshold with the differential pressure change difference data and the deviation change difference data to obtain lifespan comparison information; Based on the lifespan comparison information, the filter differential pressure change trend information is used to determine the lifespan difference and obtain lifespan difference analysis data.

6. The method for balancing the lifespan of a dual-cylinder filter element according to claim 4, characterized in that, The step of performing lifespan balancing analysis based on the lifespan difference analysis data to obtain lifespan balancing analysis data includes: The lifespan difference characteristics of the dual-cylinder filter element are determined based on the lifespan difference analysis data. The life difference value of the dual-cylinder filter element is compared with the preset life balance judgment threshold based on the life difference characteristic information of the dual-cylinder filter element to obtain the dual-cylinder difference judgment information. Determine the cause of lifespan imbalance based on the binocular difference assessment information; By combining information on the difference between the two tubes with information on the causes of life imbalance, the influence weight of the causes of life imbalance and the severity of the imbalance data are determined. Based on the influence weights of the causes of lifespan imbalance and the severity of the imbalance, combined with the filter operating parameter requirements, the balancing adjustment parameters are determined, and lifespan balance analysis data is obtained.

7. The method for balancing the lifespan of a dual-cylinder filter element according to claim 4, characterized in that, The step of performing equilibrium control analysis based on lifespan difference analysis data and lifespan equilibrium analysis data to obtain equilibrium control analysis data includes: Determine the equilibrium adjustment target and its parameters based on the lifetime difference analysis data; Multiple control nodes and their parameters are determined based on the equilibrium control objective; The corresponding offsetting node is determined based on multiple control nodes; Determine the corresponding cancellation parameters based on the corresponding cancellation node; Determine the target control node and its parameters based on the corresponding offset node and corresponding offset parameters; Equilibrium control is carried out based on the target control node and its parameters to obtain equilibrium control analysis data.

8. The method for balancing the lifespan of a dual-cylinder filter element according to claim 1, characterized in that, S3 includes: The system oil cleanliness information is obtained based on the balanced control data, and the system oil cleanliness analysis is performed based on the system oil cleanliness information to obtain oil cleanliness analysis data. Based on the oil cleaning analysis data, the filter oil cleaning is adjusted to obtain oil cleaning adjustment data; The equilibrium control data is updated based on the oil cleaning adjustment data to obtain updated control data. Based on the updated control data, filter life decay data is obtained, and life analysis and early warning are performed to obtain life analysis and early warning data.

9. The method for balancing the lifespan of a dual-cylinder filter element according to claim 8, characterized in that, The process of obtaining system oil cleanliness information based on balanced control data, performing system oil cleanliness analysis based on the system oil cleanliness information, and obtaining oil cleanliness analysis data includes: By extracting balanced control analysis data and combining it with preset oil cleanliness collection specifications, particle counting is performed on the oil at the outlet side of the dual-cylinder filter to obtain system oil cleanliness information. The system oil cleanliness information is compared with the preset target cleanliness level standard to obtain cleanliness deviation data; Determine the correlation between cleanliness deviation data and filter combination analysis data to identify the core causes of cleanliness deviation; The cleanliness deviation data is used to determine the current cleanliness level of the oil, and the pass / fail status information is obtained. The qualification assessment information is the oil cleaning analysis data.

10. A dual-cylinder filter cartridge life balancing and control system, characterized in that, The system includes: The combined analysis module is used to collect data from the dual-cylinder filter, obtain filter collection data, acquire filter differential pressure reference data, and combine and analyze the filter differential pressure reference data with the filter collection data to obtain filter combined analysis data. The equalization analysis module is used to perform filter cartridge life equalization analysis based on the filter and analysis data to obtain life equalization analysis data, and to perform equalization control analysis based on the life equalization analysis data to obtain equalization control analysis data. The cleaning analysis module is used to perform cleaning analysis and control based on the balanced control analysis data, obtain updated control data, and perform lifespan analysis and early warning based on the updated control data, thereby obtaining lifespan analysis and early warning data.

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