Self-adaptive oil cleaning system of hydraulic system

Abstract

The invention is applicable to the technical field of hydraulic system oil cleaning, and provides a hydraulic system oil self-adaptive cleaning system, which comprises a pressure difference sensing module, which is used for continuously monitoring the blockage degree of a target filter element in real time and outputting a pressure difference signal delta P; the cleaning execution module is connected with the target filter and used for executing the online cleaning action, and the cleaning execution module at least comprises a backwashing unit; the intelligent control module is connected with the pressure difference sensing module and the cleaning execution module, an early-warning threshold value delta Pw and a warning threshold value delta Pa related to the pressure difference are preset in the intelligent control module, and delta Pwlt is preset in the intelligent control module; and an alarm unit and a multi-stage control strategy based on differential pressure change are integrated in the intelligent control module. Therefore, clear on-demand cleaning can be realized through multi-threshold division and multi-mode decision, the optimal cleaning parameters in the blockage state can be automatically searched, the maintenance pertinence is improved, the online dredging success rate is improved, and the energy consumption is reduced.

Description

Technical Field

[0001] This invention relates to the field of hydraulic system oil cleaning technology, and in particular to a hydraulic system oil adaptive cleaning system. Background Technology

[0002] In hydraulic systems, filters are core components ensuring hydraulic fluid cleanliness. During operation, filter elements gradually become clogged by trapping solid particles and other contaminants, leading to an increase in the inlet and outlet pressure difference. Excessive pressure difference not only increases system energy consumption and reduces filtration efficiency but can also cause filter element structural damage or system malfunction. Currently, there are three main maintenance methods for filter elements: 1. Replacing the filter element according to a fixed time or equipment operation cycle lacks awareness of the actual condition of the filter element, which can easily lead to the filter element being replaced before its life is exhausted or the filter element being blocked prematurely and not replaced in time, causing malfunctions. 2. Install a mechanical differential pressure transmitter on the filter. When the differential pressure exceeds a certain fixed threshold, a visual or electrical alarm is triggered, prompting manual inspection or replacement. This method cannot predict the clogging trend, and manual handling is required after the alarm is triggered, making online recovery impossible. 3. Some systems integrate backflushing functions, but the control logic is simple. It is usually triggered at a time or after a single fixed differential pressure threshold is reached to perform a flush with a fixed duration and pressure. This method cannot distinguish between minor and severe blockages and uses the same flushing intensity for both. It may be effective for gradual soft blockages, but for sudden or stubborn blockages, a single fixed flush is often ineffective, and the system still needs to be shut down in the end.

[0003] In summary, existing technologies for filter cartridge maintenance generally suffer from inaccurate maintenance, lack of early intervention capabilities, and insufficient or inefficient online recovery methods in the event of severe clogging. Therefore, there is an urgent need for an intelligent system capable of accurately assessing filter cartridge health in real time, making intelligent decisions, and executing differentiated cleaning interventions to achieve predictive maintenance and efficient online recovery. Summary of the Invention

[0004] To address the aforementioned shortcomings, the present invention aims to provide a hydraulic system oil adaptive cleaning system that can achieve clear on-demand cleaning through multi-threshold division and multi-mode decision-making, and can automatically find the optimal cleaning parameters under blocked conditions, thereby improving the targeting of maintenance, increasing the success rate of online unblocking, and reducing energy consumption.

[0005] To achieve the above objectives, the present invention provides a hydraulic system oil adaptive cleaning system, comprising: The differential pressure sensing module is used to continuously and in real time monitor the degree of clogging of the target filter element and output a differential pressure signal, denoted as ΔP. A cleaning execution module, which is connected to the target filter, is used to perform online cleaning actions. The cleaning execution module includes at least a backwashing unit. The intelligent control module is connected to the differential pressure sensing module and the cleaning execution module. The intelligent control module has preset early warning threshold ΔP_w and warning threshold ΔP_a related to differential pressure, where ΔP_w < ΔP_a. The intelligent control module integrates an alarm unit and has a multi-level control strategy based on differential pressure changes.

[0006] According to the hydraulic system oil adaptive cleaning system of the present invention, the intelligent control module has three fixed working modes, namely, conventional monitoring mode, early warning intervention mode and deep recovery mode.

[0007] According to the hydraulic system oil adaptive cleaning system of the present invention, when ΔP is continuously lower than ΔP_w, the system only performs data recording and trend analysis, and does not trigger active cleaning; When ΔP_w≤ΔP<ΔP_a, the system immediately activates the early warning intervention mode, controlling the cleaning execution module to perform a preset basic cleaning procedure on the filter element according to the predetermined cleaning time.

[0008] According to the hydraulic system oil adaptive cleaning system of the present invention, when ΔP≥ΔP_a or the differential pressure change rate exceeds the preset safety limit, the system immediately interrupts any other operations and starts the deep recovery mode. In this mode, the system controls the cleaning execution module to perform intermittent closed-loop feedback cleaning cycle on the filter element.

[0009] According to the hydraulic system oil adaptive cleaning system of the present invention, the intermittent closed-loop feedback cleaning cycle includes the following steps: S1. Record the stable pressure difference P_n before the start of the nth cleaning cycle; S2. Perform a cleaning cycle consisting of a high-intensity cleaning phase and a stable effect phase; S3. After the cleaning cycle is completed and the system pressure stabilizes, record the pressure difference P_{n+1} and calculate the net decrease in pressure difference for this cleaning cycle. ; Based on the comparison between ΔP_n and the expected single-cycle pressure drop target value ΔP_s, the duration T_{n+1} of the high-intensity cleaning phase in the next cleaning cycle is dynamically adjusted, and the calculation formula is as follows: Where α is an adjustment coefficient used to control the response sensitivity; S5. Repeat steps S1 to S4 until the termination condition is met.

[0010] According to the hydraulic system oil adaptive cleaning system of the present invention, when ΔP drops below the warning threshold ΔP_w, it is determined that the online recovery is successful. If ΔP_n is less than the minimum effective improvement value ΔP_min for n consecutive cleaning cycles, it is determined that the online recovery is invalid and triggers the filter element replacement alarm. To prevent misjudgment due to single measurement fluctuations, n≥3.

[0011] The hydraulic system oil adaptive cleaning system according to the present invention further includes a moisture management module, a particle size assessment unit, and a self-learning module, wherein the moisture management module includes a moisture sensor and an independent vacuum dehydration device, and the particle size assessment unit includes an online particle counter.

[0012] According to the hydraulic system oil adaptive cleaning system of the present invention, the intelligent control module is communicatively connected to the host controller of the hydraulic system and has a linkage function for operating status. When the host is in a process stage with extremely high requirements for pressure and flow stability, the intelligent control module automatically postpones or suspends the cleaning operation until the host enters a working condition that allows maintenance.

[0013] According to the hydraulic system oil adaptive cleaning system of the present invention, the intelligent control module continuously monitors and analyzes the pressure difference ΔP and its rate of change per unit time, and switches between three working modes based on the comparison relationship between ΔP and thresholds ΔP_w and ΔP_a.

[0014] The purpose of this invention is to provide a hydraulic system oil adaptive cleaning system, which has the following beneficial effects: 1. Driven by real-time differential pressure, through multi-threshold division and multi-mode decision-making, the vague periodic replacement is transformed into clear on-demand intervention, which significantly improves the targeting of maintenance and the economic efficiency of filter cartridge use. 2. Through the intermittent closed-loop feedback cleaning cycle of "execution-measurement-optimization", the system can automatically find the optimal cleaning parameters under the current blockage state, which improves the success rate of online unblocking and provides a key buffer for unplanned downtime; 3. The key parameters in the core algorithm are all set based on clear engineering principles and can be adjusted according to the filter model and system operating conditions, so that the system has good generalization ability and practicality. 4. The linkage mechanism with the hydraulic system's main controller ensures that maintenance operations will not interfere with production, and the clear failure judgment conditions prevent the equipment from running idle under ineffective cleaning and promptly prompt manual intervention.

[0015] In summary, the beneficial effects of this invention are: it can achieve clear on-demand cleaning through multi-threshold division and multi-mode decision-making, and can automatically find the optimal cleaning parameters under blockage conditions, thereby improving the targeting of maintenance, increasing the success rate of online unblocking, and reducing energy consumption. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the process of this invention; Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] See Figure 1 This invention provides a hydraulic system oil adaptive cleaning system, comprising: The differential pressure sensing module is a high-precision differential pressure sensor installed at the inlet and outlet of the target filter. It is used to continuously and in real time monitor the degree of clogging of the filter element and output a differential pressure signal, denoted as ΔP.

[0019] The cleaning execution module is mechanically and hydraulically connected to the target filter to perform online cleaning actions; the cleaning execution module includes at least a backwashing unit, which includes a controllable backwashing oil circuit, a pressure source, and a drain valve.

[0020] The intelligent control module communicates with the differential pressure sensing module and the cleaning execution module. The intelligent control module has preset warning thresholds ΔP_w and alert thresholds ΔP_a related to the differential pressure, where ΔP_w < ΔP_a. The setting of the warning thresholds ΔP_w and ΔP_a is based on the inherent performance parameters of the filter element: ΔP_w is recommended to be set to 2-4 times the initial cleaning differential pressure of the filter element, and not exceeding 30%-50% of its manufacturer-recommended maximum allowable differential pressure; ΔP_a is recommended to be set not exceeding 70%-85% of its maximum allowable differential pressure, ensuring timely warnings and safe recovery operations.

[0021] The intelligent control module also integrates an alarm unit to provide early warnings to users when necessary, enabling manual intervention.

[0022] The intelligent control module incorporates a multi-level control strategy based on differential pressure changes. It continuously monitors and analyzes the differential pressure ΔP and its rate of change per unit time, and automatically switches between three operating modes based on the comparison between ΔP and thresholds ΔP_w and ΔP_a: 1. Conventional monitoring mode The trigger condition for this mode is: when ΔP is continuously lower than ΔP_w, the system only records data and performs trend analysis, and does not trigger active cleaning.

[0023] 2. Early warning and intervention model The trigger condition for this mode is: when ΔP_w≤ΔP<ΔP_a, the system immediately starts the early warning intervention mode and controls the cleaning execution module to perform the preset basic cleaning program on the filter element according to the predetermined cleaning time.

[0024] 3. Deep Recovery Mode The trigger condition for this mode is: when ΔP ≥ ΔP_a or the differential pressure change rate exceeds the preset safety limit (this safety limit can be set and adjusted based on experience), the system immediately interrupts any other operations and starts the deep recovery mode; in this mode, the system controls the cleaning execution module to perform an intermittent closed-loop feedback cleaning cycle on the filter element, and the specific steps are as follows: S1. Record the stable pressure difference P_n before the start of the nth cleaning cycle; S2. Perform a cycle consisting of a high-intensity cleaning phase and a phase where the effect stabilizes; S3. After the cycle ends and the system pressure stabilizes, record the pressure difference P_(n+1) and calculate the net decrease in pressure difference for this cycle. ; S4. Based on the comparison between ΔP_n and the expected single-cycle pressure difference reduction target value ΔP_s, dynamically adjust the duration T_(n+1) of the high-intensity cleaning phase in the next cleaning cycle, following the formula: Where α is an adjustment coefficient used to control the response sensitivity, and clamp is a limiting function to ensure that the result is between the preset minimum time T_min and maximum time T_max; α is selected between 0.1 and 0.5 to ensure a smooth feedback adjustment process and avoid excessive oscillation. The smaller the α value, the more conservative the system response; the larger the α value, the more aggressive the system adjustment. The setting of T_min needs to take into account the minimum reliable operating cycle of the cleaning actuator (such as a solenoid valve) and the system response time. The setting of T_max needs to prevent excessively long single cleaning operation time, which may lead to energy waste, oil overheating, or component fatigue. The typical range is 1 second to 300 seconds. ΔP_s is estimated and set according to 10% to 25% of the differential pressure range to be cleaned (ΔP_a - ΔP_w), aiming to achieve a steady and efficient gradual recovery.

[0025] To address the non-minimum phase issue that may arise from the hysteresis and overshoot characteristics of hydraulic systems, and to prevent oscillations during the adjustment of various parameters in the cleaning system, the intelligent control module incorporates a speed feedback compensation unit and a pole configuration optimization strategy into the closed-loop feedback regulation logic. The speed feedback compensation unit collects the pressure response rate signal from the cleaning execution module in real time, forming a dual closed-loop feedback with the differential pressure signal to reduce the adjustment delay caused by system hysteresis. The pole configuration strategy constrains the dynamic changes of α by preset the system stable pole range. When the frequency of differential pressure fluctuation exceeds the preset threshold (recommended to be 0.5~2Hz), the adjustment amplitude of the α value is automatically reduced to ensure a smooth feedback regulation process.

[0026] S5. Repeat steps S1 to S4 until one of the following termination conditions is met: 1. When ΔP drops below the warning threshold ΔP_w, it is determined that the online recovery was successful; 2. If ΔP_n is less than the minimum effective improvement value ΔP_min for n consecutive cleaning cycles, it is determined that the online recovery is ineffective and triggers the filter replacement alarm. To prevent misjudgment due to fluctuations in a single measurement, n≥3.

[0027] ΔP_min should be greater than the comprehensive measurement error of the differential pressure sensor under system operating conditions. It is usually set to 0.5% to 2% of the full scale of the differential pressure sensor or a fixed engineering experience value (such as 0.01 to 0.02 MPa).

[0028] The system also includes a moisture management module, which contains a moisture sensor and an independent vacuum dehydration device. When the moisture content exceeds its independently set threshold, the dehydration operation is triggered, which aims to control the humidity of the oil, slow down the formation of sludge from the source, and indirectly extend the life of the filter element.

[0029] This system also includes a particle size assessment unit, which comprises an online particle counter. Its main function is to assess whether the overall cleanliness of the system oil has been restored synchronously after a successful deep recovery mode, and to provide long-term contamination trend data to assist in optimizing early warning thresholds or conducting contamination source analysis.

[0030] The intelligent control module communicates with the main controller of the hydraulic system and has the function of linkage of operating status. When the main machine is in a process stage with extremely high requirements for pressure and flow stability, the intelligent control module can automatically postpone or suspend the cleaning operation until the main machine enters the working condition that allows maintenance, so as to ensure that the maintenance operation does not affect the core production process.

[0031] This system also includes a self-learning module, which collects historical cleaning data (such as differential pressure change rate). The differential pressure change rate is the difference in differential pressure per unit time, denoted as Q. Based on the differential pressure change rate, the blockage situation is divided into slow blockage (Q < 0.01 MPa / h), moderate blockage (0.01 MPa / h ≤ Q < 0.05 MPa / h), and rapid blockage (Q ≥ 0.05 MPa / h). The system then optimizes and adjusts the fine-tuning logic of α for different blockage situations. In the slow blockage scenario, α... The value is finely adjusted in the range of 0.1 to 0.2, adopting a conservative adjustment strategy to extend the filter life. In the case of moderate clogging, the α value is maintained in the range of 0.2 to 0.3 to balance cleaning efficiency and energy consumption. In the case of rapid clogging, the α value is finely adjusted in the range of 0.3 to 0.5, adopting an aggressive adjustment strategy to quickly clear the clogging. Every 10 to 20 cleaning cycle data accumulated by the self-learning module, the optimal range of α value under different scenarios is automatically updated, and the prediction accuracy of ΔP_s is optimized at the same time, so that the adaptive cleaning parameters are more in line with the actual clogging characteristics.

[0032] During operation, the differential pressure detection module monitors the degree of clogging of the filter element in real time. 1. During system operation, when ΔP is consistently lower than ΔP_w, the system only records the data of ΔP and calculates its daily average rate of increase for trend analysis. No cleaning operations are performed, and energy consumption is lowest in this state. 2. During system operation, when ΔP_w≤ΔP<ΔP_a, the system immediately activates the early warning intervention mode and controls the cleaning execution module to perform the preset basic cleaning program on the filter element according to the predetermined cleaning time; 3. When ΔP ≥ ΔP_a or the differential pressure change rate exceeds the preset safety limit, the system immediately interrupts any other operations and starts the deep recovery mode. In this mode, the system controls the cleaning execution module to perform intermittent closed-loop feedback cleaning cycles on the filter element. First, record the stable pressure difference before the start of the cleaning cycle. Then, control the cleaning execution module to perform high-pressure continuous flushing of the target filter element for a certain period of time, i.e., the high-intensity cleaning stage. Then, stop flushing the target filter element and enter the effect stabilization stage. After the pressure in the system stabilizes, record the pressure difference P_{n+1} and calculate the net pressure drop value of this cycle. Compare the net pressure drop value of this cleaning cycle with the expected single-cycle pressure drop target value ΔP_s, and dynamically adjust the duration of the high-intensity cleaning stage in the next cleaning cycle based on the comparison result.

[0033] If ΔP drops below the warning threshold ΔP_w in a certain cleaning cycle, it is determined that the online recovery is successful; if ΔP_n is less than the minimum effective improvement value ΔP_min for no less than 3 consecutive cleaning cycles, it is determined that the online recovery is ineffective and triggers the filter replacement alarm.

[0034] This invention provides a hydraulic system oil adaptive cleaning system, which has the following beneficial effects: 1. Driven by real-time differential pressure, through multi-threshold division and multi-mode decision-making, the vague periodic replacement is transformed into clear on-demand intervention, which significantly improves the targeting of maintenance and the economic efficiency of filter cartridge use. 2. Through the intermittent closed-loop feedback cleaning cycle of "execution-measurement-optimization", the system can automatically find the optimal cleaning parameters under the current blockage state, which improves the success rate of online unblocking and provides a key buffer for unplanned downtime; 3. The key parameters in the core algorithm are all set based on clear engineering principles and can be adjusted according to the filter model and system operating conditions, so that the system has good generalization ability and practicality. 4. The linkage mechanism with the hydraulic system's main controller ensures that maintenance operations will not interfere with production, and the clear failure judgment conditions prevent the equipment from running idle under ineffective cleaning and promptly prompt manual intervention.

[0035] In summary, the beneficial effects of this invention are: it can achieve clear on-demand cleaning through multi-threshold division and multi-mode decision-making, and can automatically find the optimal cleaning parameters under blockage conditions, thereby improving the targeting of maintenance, increasing the success rate of online unblocking, and reducing energy consumption.

[0036] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A hydraulic system oil adaptive cleaning system, characterized in that, include: The differential pressure sensing module is used to continuously and in real time monitor the degree of clogging of the target filter element and output a differential pressure signal, denoted as ΔP. A cleaning execution module, which is connected to the target filter, is used to perform online cleaning actions. The cleaning execution module includes at least a backwashing unit. The intelligent control module is connected to the differential pressure sensing module and the cleaning execution module. The intelligent control module has preset early warning threshold ΔP_w and warning threshold ΔP_a related to differential pressure, where ΔP_w < ΔP_a. The intelligent control module integrates an alarm unit and has a multi-level control strategy based on differential pressure changes.

2. The hydraulic system oil adaptive cleaning system according to claim 1, characterized in that, The intelligent control module has three built-in working modes: regular monitoring mode, early warning and intervention mode, and deep recovery mode.

3. The hydraulic system oil adaptive cleaning system according to claim 2, characterized in that, When ΔP remains below ΔP_w, the system only records data and performs trend analysis, without triggering active cleaning. When ΔP_w≤ΔP<ΔP_a, the system immediately activates the early warning intervention mode, controlling the cleaning execution module to perform a preset basic cleaning procedure on the filter element according to the predetermined cleaning time.

4. The hydraulic system oil adaptive cleaning system according to claim 2, characterized in that, When ΔP ≥ ΔP_a or the differential pressure change rate exceeds the preset safety limit, the system immediately interrupts any other operations and starts the deep recovery mode. In this mode, the system controls the cleaning execution module to perform intermittent closed-loop feedback cleaning cycles on the filter element.

5. The hydraulic system oil adaptive cleaning system according to claim 4, characterized in that, The intermittent closed-loop feedback cleaning cycle includes the following steps: S1. Record the stable pressure difference P_n before the start of the nth cleaning cycle; S2. Perform a cleaning cycle consisting of a high-intensity cleaning phase and a stable effect phase; S3. After the cleaning cycle is completed and the system pressure stabilizes, record the pressure difference P_{n+1} and calculate the net decrease in pressure difference for this cleaning cycle. ; Based on the comparison between ΔP_n and the expected single-cycle pressure drop target value ΔP_s, the duration T_{n+1} of the high-intensity cleaning phase in the next cleaning cycle is dynamically adjusted, and the calculation formula is as follows: Where α is an adjustment coefficient used to control the response sensitivity; S5. Repeat steps S1 to S4 until the termination condition is met.

6. The hydraulic system oil adaptive cleaning system according to claim 5, characterized in that, When ΔP drops below the warning threshold ΔP_w, it is determined that the online recovery is successful. If ΔP_n is less than the minimum effective improvement value ΔP_min for n consecutive cleaning cycles, it is determined that the online recovery is invalid and triggers the filter replacement alarm. To prevent misjudgment due to single measurement fluctuations, n≥3.

7. The hydraulic system oil adaptive cleaning system according to claim 1, characterized in that, It also includes a moisture management module, a particle size assessment unit, and a self-learning module. The moisture management module includes a moisture sensor and an independent vacuum dehydration device, and the particle size assessment unit includes an online particle counter.

8. The hydraulic system oil adaptive cleaning system according to claim 6, characterized in that, The intelligent control module is connected to the main controller of the hydraulic system and has a linkage function for operating status. When the main machine is in a process stage with extremely high requirements for pressure and flow stability, the intelligent control module automatically postpones or suspends the cleaning operation until the main machine enters a working condition that allows maintenance.

9. The hydraulic system oil adaptive cleaning system according to claim 2, characterized in that, The intelligent control module continuously monitors and analyzes the differential pressure ΔP and its rate of change per unit time, and switches between three working modes based on the comparison relationship between ΔP and the thresholds ΔP_w and ΔP_a.

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