Engine piston ring non-disassembly cleaning method and system based on closed-loop control

Abstract

The invention provides an engine piston ring non-disassembly cleaning method and system based on closed-loop control, and the method comprises the steps: obtaining piston ring material composition, real-time operation parameters and thermal imaging spectrum data, and carrying out fusion processing to generate a dynamic cleaning path parameter containing a deposition layer thickness distribution parameter and a cleaning priority; then, the vibration frequency of the piezoelectric ceramic array is adjusted according to the thickness parameter, and the amplitude attenuation gradient is iteratively corrected based on the priority to generate the optimized shear vibration frequency; in the cleaning process, the carbon deposition removing effect is monitored in real time and compared with a preset standard, and finally accurate carbon deposition removing is achieved by dynamically adjusting the phase difference between the chemical solvent pulse frequency and the shear vibration frequency. The precision and efficiency of engine piston ring carbon deposit cleaning are improved.

Description

Technical Field

[0001] This application relates to the field of closed-loop control technology, and particularly to a non-dismantling cleaning method and system for engine piston rings based on closed-loop control. Background Art

[0002] The problem of carbon deposition on engine piston rings directly affects the performance and lifespan of the engine. Traditional disassembly cleaning methods require the disassembly of the engine, which is costly and time-consuming. With the development of engine precision, there is an urgent need for a non-dismantling cleaning technology that can identify the carbon deposition distribution online and dynamically adjust the cleaning parameters to achieve precise and efficient carbon deposition removal, while avoiding interference with the engine operation.

[0003] Currently, there is a cleaning solution that combines chemical solvents and mechanical vibration. This solution uses piezoelectric vibration at a fixed frequency in combination with chemical solvent spraying, and utilizes the vibration cavitation effect to assist in dissolving carbon deposition. Among them, the vibration frequency is set based on a preset program, and the chemical solvent ratio is empirically selected according to the piston ring material. During the cleaning process, the change in the local carbon deposition thickness is monitored by a single sensor.

[0004] This solution has the problems that the fixed vibration frequency leads to uneven cleaning effect; the static matching of chemical solvents and vibration parameters lacks real-time feedback adjustment, making it difficult to cope with the dynamic working conditions of the engine; and the monitoring range of a single sensor is limited, prone to problems such as incomplete local cleaning or over-cleaning. Summary of the Invention

[0005] This application provides a non-dismantling cleaning method and system for engine piston rings based on closed-loop control to solve the problems of low accuracy and poor efficiency in carbon deposition cleaning of engine piston rings in the prior art.

[0006] In a first aspect, this application provides a non-dismantling cleaning method for engine piston rings based on closed-loop control, including:

[0007] Obtain the material composition information of the piston rings of the engine, the real-time operating parameter data, and the thermal imaging map data;

[0008] Fuse and process the piston ring material composition information, the real-time operating parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters, where the dynamic cleaning path parameters include the deposition layer thickness distribution parameters and the cleaning priority levels for different regions on the piston ring surface;

[0009] Adjust the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correct the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priority levels to generate a shear vibration frequency;

[0010] Monitor the carbon deposit removal effect data on the piston ring surface in real time, and compare the carbon deposit removal effect data with a preset removal standard;

[0011] According to the shear vibration frequency, combined with the pulse frequency, calculate the phase difference between the pulse frequency and the shear vibration frequency, and dynamically adjust the phase difference based on the comparison result to remove the carbon deposit particles on the surface of the engine piston ring.

[0012] Optionally, the adjusting the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameter, and iteratively correcting the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the removal priority to generate a shear vibration frequency includes:

[0013] Based on the mapping relationship between the preset deposition layer thickness distribution parameter and the vibration frequency adjustment coefficient, convert the deposition layer thickness distribution parameter into a vibration frequency adjustment coefficient according to the preset ratio corresponding to the deposition layer thickness interval;

[0014] Generate an amplitude attenuation gradient correction amount based on the vibration frequency adjustment coefficient and the removal priority;

[0015] Based on the initial vibration frequency of the piezoelectric ceramic array, use the amplitude attenuation gradient correction amount as the step size, and iteratively reduce the vibration frequency of the piezoelectric ceramic array step by step;

[0016] Monitor the uniformity of the vibration energy distribution on the outside of the engine cylinder block. When the uniformity of the vibration energy distribution reaches the preset distribution uniformity range, generate a shear vibration frequency according to the reduced vibration frequency and the amplitude attenuation gradient correction amount.

[0017] Optionally, the generating an amplitude attenuation gradient correction amount based on the vibration frequency adjustment coefficient and the removal priority includes:

[0018] Convert the value of the removal priority into a weight factor according to a preset segmentation rule, and the weight factor is inversely proportional to the value of the removal priority;

[0019] Multiply the vibration frequency adjustment coefficient by the weight factor to obtain an initial correction amount reference value;

[0020] Calculate the compensation coefficient of the initial correction amount reference value based on the spacing parameter between the installation position of the piezoelectric ceramic array and the piston ring;

[0021] Multiply the initial correction amount reference value by the compensation coefficient to generate an amplitude attenuation gradient correction amount.

[0022] Optionally, the fusion processing of the piston ring material composition information, the real-time operation parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters includes:

[0023] Generate formulation parameters for the chemical solvent used to clean the piston ring according to the piston ring material composition information and the real-time operation parameter data, where the formulation parameters include the ratio data of each group in the polar functional group and the concentration data of the chelating agent;

[0024] Adjust the pulse frequency of the cleaning equipment for spraying the chemical solvent based on the ratio data of each group and the concentration data of the chelating agent;

[0025] Extract a set of pixel points on the outer surface of the piston ring where the temperature exceeds the first preset threshold from the thermal imaging map data;

[0026] Map the image coordinates of each pixel point in the set of pixel points to the position coordinates of the corresponding area on the piston ring surface, and the corresponding area is the deposition area;

[0027] Determine the deposition layer thickness distribution parameters and the cleaning priorities of each deposition area according to the temperature gradient change rate of each deposition area;

[0028] Determine the solvent coverage area per unit time according to the pulse frequency, and generate a chemical solvent coverage path in combination with the position coordinates of each deposition area;

[0029] According to the chemical solvent coverage path, merge the deposition layer thickness distribution parameters and the cleaning priorities of all deposition areas to generate dynamic cleaning path parameters.

[0030] Optionally, the determining the deposition layer thickness distribution parameters and the cleaning priorities of each deposition area according to the temperature gradient change rate of each deposition area includes:

[0031] Calculate the thermal diffusion resistance coefficient of the corresponding deposition area according to the temperature gradient change rate of each deposition area;

[0032] Map the thermal diffusion resistance coefficients of each deposition area to the deposition layer thickness distribution parameters of the corresponding deposition area;

[0033] Determine the cleaning priorities of the corresponding deposition areas according to the deposition layer thickness distribution parameters and the position coordinates of each deposition area.

[0034] Optionally, the generating the shear vibration frequency according to the reduced vibration frequency and the amplitude attenuation gradient correction amount includes:

[0035] Generate a candidate target frequency based on the reduced vibration frequency;

[0036] Determine the product result of the candidate target frequency and the amplitude attenuation gradient correction amount as the frequency compensation value;

[0037] Add the candidate target frequency and the frequency compensation value to generate the shear vibration frequency.

[0038] Optionally, calculating the phase difference between the pulse frequency and the shear vibration frequency according to the pulse frequency and the shear vibration frequency includes:

[0039] Obtain the first time series of the pulse signal generated by the cleaning device and the second time series of the shear vibration signal generated by the piezoelectric ceramic array, wherein the first time series is defined by the opening time and the closing time of the solvent injection valve in the cleaning device corresponding to the pulse frequency, and the second time series is defined by the rising edge and the falling edge of the resonance waveform corresponding to the shear vibration frequency;

[0040] Extract the valve opening time point of each pulse in the first time series, and extract the peak time point of the oscillation waveform in the corresponding period of the second time series;

[0041] Calculate the time difference between the valve opening time point and the peak time point in the same period, and map the time difference to the phase difference.

[0042] In a second aspect, the present application provides a non-disintegrating cleaning system for an engine piston ring based on closed-loop control, including:

[0043] An acquisition module for acquiring the piston ring material composition information, real-time operating parameter data, and thermal imaging map data of the engine;

[0044] A fusion processing module for fusing the piston ring material composition information, the real-time operating parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters, where the dynamic cleaning path parameters include deposition layer thickness distribution parameters and cleaning priorities for different regions on the surface of the piston ring;

[0045] A correction module for adjusting the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correcting the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priorities to generate the shear vibration frequency;

[0046] A monitoring module for real-time monitoring of the carbon deposit removal effect data on the piston ring surface and comparing the carbon deposit removal effect data with a preset removal standard;

[0047] A calculation module, configured to calculate a phase difference between the pulse frequency and the shear vibration frequency according to the shear vibration frequency in combination with the pulse frequency, and dynamically adjust the phase difference based on a comparison result to remove carbon deposit particles on the surface of the engine piston ring.

[0048] In a third aspect, the present application provides a computing device, including a processor and a memory. A computer program is stored in the memory, and the processor is configured to run the computer program to execute a method for non-dismantling cleaning of an engine piston ring based on closed-loop control according to any one of the first aspect.

[0049] In a fourth aspect, the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, a method for non-dismantling cleaning of an engine piston ring based on closed-loop control according to any one of the first aspect is implemented.

[0050] In the present application, a method for non-dismantling cleaning of an engine piston ring based on closed-loop control is provided. The method includes: obtaining information on the material composition of the piston ring of the engine, real-time operating parameter data, and thermal imaging map data; performing fusion processing on the information on the material composition of the piston ring, the real-time operating parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters, where the dynamic cleaning path parameters include deposition layer thickness distribution parameters and cleaning priorities for different regions on the surface of the piston ring; adjusting the vibration frequency of a piezoelectric ceramic array attached to the outer side of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correcting the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priorities to generate a shear vibration frequency; monitoring data on the carbon deposit removal effect on the surface of the piston ring in real time, and comparing the carbon deposit removal effect data with a preset removal standard; calculating a phase difference between the pulse frequency and the shear vibration frequency according to the shear vibration frequency in combination with the pulse frequency, and dynamically adjusting the phase difference based on the comparison result to remove carbon deposit particles on the surface of the engine piston ring.

[0051] The technical solution of the present application has the following beneficial effects:

[0052] The present application realizes the precise adaptation of cleaning parameters to ensure that the chemical solvent and vibration characteristics match the actual working conditions of the engine. Constructs a spatial mapping of carbon deposit distribution and cleaning priorities to provide a decision-making basis for differential cleaning. Dynamically optimizes the vibration energy distribution to achieve gradient removal for carbon deposit regions with different thicknesses. Forms a closed-loop feedback to avoid insufficient cleaning or excessive damage to the surface of the piston ring. Coordinates the timing of chemical solvent penetration and mechanical vibration peeling to improve the carbon deposit removal efficiency.

[0053] Further, the present application also converts the thickness interval into a frequency adjustment coefficient in proportion according to the preset mapping relationship between the deposition layer thickness parameter and the vibration frequency adjustment coefficient, generates an amplitude attenuation gradient correction amount in combination with the cleaning priority; iteratively reduces the initial vibration frequency of the piezoelectric ceramic with the correction amount as the step size, and monitors the uniformity of the vibration energy distribution in real time. After meeting the standard, the optimized shear vibration frequency is output.

[0054] Moreover, an adaptive matching between the vibration frequency and the carbon deposit thickness is achieved, and the gradient correction is used to ensure that the vibration energy evenly covers different priority areas, avoiding local energy overload or deficiency, and improving the cleaning uniformity and the protection of the piston ring.

[0055] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0057] Figure 1 It is a flowchart of a method for non-dismantling cleaning of an engine piston ring based on closed-loop control provided by an embodiment of the present application;

[0058] Figure 2 It is a schematic structural diagram of a non-dismantling cleaning system for an engine piston ring based on closed-loop control provided by an embodiment of the present application;

[0059] Figure 3 It is a schematic structural diagram of a computing device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0060] In order to enable those skilled in the art to better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application.

[0061] In some of the processes described in the specification, claims, and the above-mentioned drawings of this application, a plurality of operations appear in a specific order. However, it should be clearly understood that these operations can be executed not in the order in which they appear herein or in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. Additionally, these processes may include more or fewer operations, and these operations can be executed in sequence or in parallel. It should be noted that the descriptions such as "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent a sequence, and do not limit that "first" and "second" are of different types.

[0062] Researchers have found that existing engine piston ring cleaning technologies have problems such as fixed cleaning parameters, inability to dynamically adapt to different carbon deposition conditions, and lack of real-time feedback adjustment, resulting in uneven cleaning effects and easy damage to the surface of the piston ring. Based on this, this application provides a non-dismantling cleaning method for engine piston rings based on closed-loop control. This method can generate a dynamic cleaning path through multi-source data fusion, intelligently adjust vibration parameters according to the carbon deposition thickness and priority, and achieve precise coordination of chemical cleaning and mechanical vibration through real-time monitoring and dynamic adjustment of the phase difference. The technical solution of this application can be applied to the on-line maintenance scenarios of various internal combustion engine piston rings, and is particularly suitable for application environments with high requirements for cleaning accuracy and engine protection.

[0063] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of this application.

[0064] Figure 1 The flowchart of a non-dismantling cleaning method for engine piston rings based on closed-loop control provided by the embodiments of this application is as Figure 1 shown, and this method includes:

[0065] Step 101: Obtain the piston ring material composition information, real-time operating parameter data, and thermal imaging map data of the engine.

[0066] In this step, the piston ring material composition information includes data such as the piston ring metal matrix composition and surface treatment process. The real-time operating parameter data includes operating condition parameters such as engine speed, load, and temperature. The thermal imaging map data represents the piston ring surface temperature distribution image data obtained by an infrared thermal imager.

[0067] In the embodiment of the present application, a sensor group installed on the engine (including a material analysis probe, a working condition sensor, and an infrared thermal imager) synchronously collects the material characteristics, operating conditions, and thermal imaging data of the piston ring. Among them, the material analysis probe uses laser-induced breakdown spectroscopy technology to obtain the surface composition of the piston ring, the working condition sensor records the engine operating parameters in real time, and the infrared thermal imager collects the surface temperature field distribution of the piston ring at a rate of 30 frames per second.

[0068] For example, taking a certain type of diesel engine as an example, first, the LIBS probe installed on the cylinder block analyzes that the material of the piston ring is chrome-plated cast iron. At the same time, the operating parameters of the engine with a current speed of 1800 rpm and a load rate of 75% are collected, and the temperature distribution image of the second ring groove area of the piston ring is obtained by the infrared thermal imager installed in the spark plug hole, and the temperature range is between 180 - 250 °C.

[0069] Step 102: Perform fusion processing on the piston ring material composition information, the real-time operating parameter data, and the thermal imaging atlas data to generate dynamic cleaning path parameters, where the dynamic cleaning path parameters include deposition layer thickness distribution parameters and cleaning priorities for different regions on the piston ring surface.

[0070] In this step, the dynamic cleaning path parameters are spatio-temporal control parameters for guiding the operation of the cleaning equipment. The deposition layer thickness distribution parameters represent spatial distribution data quantifying the thickness of the carbon deposit layer. The cleaning priority is an index characterizing the urgency of cleaning in each region.

[0071] In the embodiment of the present application, the material composition information and operating parameters are input into a chemical ratio model to determine the optimal solvent formula. At the same time, image processing algorithms are used to analyze the thermal imaging data to identify the carbon deposit regions, the carbon deposit thickness distribution is calculated through a temperature gradient inversion algorithm, and then a cleaning priority evaluation model is established in combination with the engine operating conditions. Finally, a dynamic cleaning path including spatial coordinates, thickness parameters, and priorities is integrated and generated.

[0072] For example, for the above-mentioned diesel engine, the system generates a solvent formula containing 15% organic amine according to the chrome-plated cast iron material and the current working conditions. Through thermal image analysis, it is found that there is an obvious high-temperature area (240 °C) in the third quadrant. The carbon deposit thickness in this area is calculated to be 0.3 mm and marked as high priority, and the thickness in other areas is 0.1 - 0.2 mm and marked as medium priority, and a spiral cleaning path starting from the third quadrant is generated.

[0073] Step 103: Adjust the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correct the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priority to generate a shear vibration frequency.

[0074] In this step, the piezoelectric ceramic array represents a vibration generating device installed on the outer wall of the cylinder. The amplitude attenuation gradient represents the attenuation rate of vibration energy with distance. The shear vibration frequency represents the optimized working vibration frequency. The vibration frequency is an intermediate parameter (the original frequency in the adjustment stage); the shear vibration frequency is the final parameter (the output frequency used for phase difference calculation). The shear vibration frequency is the final optimized output result of the vibration frequency, and the two essentially belong to the same physical quantity (frequency dimension).

[0075] In the embodiment of the present application, the basic vibration frequency is obtained by querying a preset frequency-thickness mapping table according to the thickness distribution parameter, and then the amplitude attenuation gradient correction amount is calculated by a priority weighting algorithm. The piezoelectric ceramic drive signal is adjusted by an iterative approximation method until the vibration energy distribution reaches a preset uniformity standard, and finally a stable shear vibration frequency is output.

[0076] For example, for a carbon deposition area with a thickness of 0.3 mm, an initial vibration frequency of 28 kHz is set, and an attenuation coefficient of 0.8 is set for the high-priority area. After 3 iterations of adjustment, the optimal working frequency is determined to be 26.5 kHz, and the uniformity of the vibration energy distribution reaches more than 85%.

[0077] Step 104: Monitor the carbon deposition removal effect data on the piston ring surface in real time, and compare the carbon deposition removal effect data with a preset removal standard.

[0078] In this step, the carbon deposition removal effect data represents the real-time cleaning effect evaluation parameter. The preset removal standard represents the cleaning quality index expected to be achieved.

[0079] In the embodiment of the present application, the change in the surface temperature distribution of the piston ring is monitored in real time by a thermal imager, and combined with the harmonic characteristics collected by a vibration sensor, a multi-feature fusion algorithm is used to calculate the carbon deposition removal rate, which is compared with a preset removal threshold (such as 95%) to generate a cleaning effect evaluation report.

[0080] For example, during the cleaning process, the temperature in the high-temperature area of the third quadrant drops to 200 °C, and the amplitude of the vibration second harmonic decreases by 40%. The system determines that the carbon deposition removal rate in this area reaches 92%, approaching the preset standard.

[0081] Step 105: Calculate the phase difference between the pulse frequency and the shear vibration frequency according to the shear vibration frequency, and dynamically adjust the phase difference based on the comparison result to remove the carbon deposition particles on the surface of the engine piston ring.

[0082] In this step, the phase difference represents the timing relationship between the solvent injection and the mechanical vibration. The dynamic adjustment means adjusting according to the feedback real-time parameters.

[0083] In the embodiments of the present application, based on the deviation between the cleaning effect data and the preset standard, the timing relationship between the solvent injection valve and the piezoelectric drive is dynamically adjusted through the PID control algorithm. When the cleaning rate is lower than the standard, the phase difference is increased to extend the action time, and vice versa, the phase difference is decreased to improve the cleaning efficiency.

[0084] For example, for a cleaning rate of 92% in the third quadrant, the system adjusts the phase difference from 15 ms to 18 ms. After continuing to clean for 2 minutes, the cleaning rate in this area reaches 96%, completing the cleaning task.

[0085] Through multi-source data fusion and closed-loop control, this technical solution realizes the precise and efficient removal of piston ring carbon deposits. The system can automatically adjust the cleaning parameters according to the actual carbon deposit condition of the piston ring, improve the consistency of the cleaning effect, and at the same time greatly reduce the solvent consumption and operation time. The entire cleaning process can be completed under the normal operating state of the engine, avoiding the damage to the engine caused by traditional disassembly cleaning, and making the piston ring maintenance work more intelligent and convenient. The surface cleanliness of the piston ring after cleaning reaches the expected standard, effectively restoring the original performance of the engine.

[0086] To solve the problem of the mismatch between the vibration parameters and the carbon deposit condition during the piston ring cleaning process, in some embodiments, step 103: adjusting the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameter, and iteratively correcting the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priority to generate a shear vibration frequency, includes:

[0087] Step 201: Based on the mapping relationship between the preset deposition layer thickness distribution parameter and the vibration frequency adjustment coefficient, convert the deposition layer thickness distribution parameter into a vibration frequency adjustment coefficient according to the preset ratio corresponding to the deposition layer thickness interval.

[0088] In step 201, the deposition layer thickness interval means dividing the carbon deposit thickness into three intervals: 0 - 0.1 mm, 0.1 - 0.3 mm, and 0.3 - 0.5 mm. The preset ratio means that the frequency adjustment coefficient increments corresponding to each thickness interval are 0.2, 0.5, and 0.8 respectively. The vibration frequency adjustment coefficient represents the adjustment parameter of the vibration frequency with the change of the carbon deposit thickness, and the value range is 0.5 - 1.5.

[0089] In the embodiments of the present application, the system internally sets a thickness-frequency mapping table, and automatically matches the corresponding adjustment coefficient according to the detected carbon deposit thickness. For example, when the detected thickness of a certain area is 0.25 mm, which falls into the 0.1 - 0.3 mm interval, the adjustment coefficient 1.2 is selected. This coefficient will be used as the basis for subsequent vibration parameter calculation.

[0090] Step 202: Generate an amplitude attenuation gradient correction amount based on the vibration frequency adjustment coefficient and the cleaning priority.

[0091] In step 202, the amplitude attenuation gradient correction amount represents an adjustment parameter that controls the attenuation rate of vibration energy with distance, with the unit of dB / mm.

[0092] In the embodiment of the present application, the system multiplies the vibration frequency adjustment coefficient by the correction coefficient corresponding to the priority to obtain the final attenuation gradient correction amount. The high-priority area attenuates slowly to ensure the cleaning effect in the key area; the low-priority area attenuates quickly to avoid energy waste. For example, multiplying the adjustment coefficient 1.2 by the high priority 0.7 gives a correction amount of 0.84 dB / mm.

[0093] Step 203: Based on the initial vibration frequency of the piezoelectric ceramic array, using the amplitude attenuation gradient correction amount as the step size, perform iteration to gradually reduce the vibration frequency of the piezoelectric ceramic array.

[0094] In step 203, the initial vibration frequency represents the reference operating frequency of the piezoelectric ceramic array, with a typical value of 25 kHz. The iteration step size represents the amplitude of each frequency adjustment, taking 1 / 10 of the correction amount.

[0095] In the embodiment of the present application, the system starts from the initial frequency and gradually reduces the frequency according to the calculated step size. After each adjustment, the vibration energy distribution is detected until the best uniformity is achieved. For example, starting from 25 kHz, with a step size of 0.84 kHz, the first adjustment is to 24.16 kHz, the second is to 23.32 kHz, and so on.

[0096] Step 204: Monitor the uniformity of the vibration energy distribution on the outer side of the engine cylinder block. When the uniformity of the vibration energy distribution reaches the preset distribution uniformity range, generate a shear vibration frequency according to the reduced vibration frequency and the amplitude attenuation gradient correction amount.

[0097] In step 204, the uniformity of the vibration energy distribution represents the standard deviation of the vibration intensities of each measuring point on the cylinder block surface. The preset distribution range means that the uniformity index does not exceed 15%.

[0098] In the embodiment of the present application, through the monitoring by the acceleration sensor array arranged on the cylinder block surface, when the vibration frequency is adjusted to 22.5 kHz and the detected uniformity reaches 12%, the system locks this frequency as the final shear vibration frequency and records the corresponding correction amount of 0.84 dB / mm.

[0099] The following is a specific example:

[0100] During the cleaning process of the piston rings of a certain type of diesel engine, based on the detected material of chromium-plated cast iron and the current operating conditions, the system discovers obvious carbon deposit accumulation in the second ring groove area through thermal imaging analysis. For this area, the system first automatically matches the corresponding vibration frequency adjustment coefficient according to the carbon deposit thickness, and at the same time calculates the appropriate amplitude decay gradient correction amount in combination with the marked high-priority level of this area. Subsequently, starting from the initial vibration frequency, the frequency is gradually reduced according to the calculated adjustment step size, and during this process, the vibration energy distribution on the outer wall of the cylinder block is monitored in real time. When the vibration energy uniformity reaches the predetermined standard, the system locks the current vibration frequency as the final shear vibration frequency.

[0101] In the embodiment of the present application, this solution realizes ensuring that appropriate cleaning energy can be obtained in areas with carbon deposits of different thicknesses by intelligently adjusting vibration parameters; giving priority to ensuring the cleaning quality of key areas; maintaining a uniform distribution of vibration energy to avoid local overload or deficiency. The entire adjustment process is completely automated without manual intervention.

[0102] To further improve the accuracy of vibration parameter adjustment, in some embodiments, step 202: generating the amplitude decay gradient correction amount based on the vibration frequency adjustment coefficient and the cleaning priority includes:

[0103] Step 301: Convert the value of the cleaning priority into a weight factor according to a preset segmentation rule, and the weight factor is inversely proportional to the value of the cleaning priority.

[0104] In step 301, the value of the cleaning priority refers to converting the cleaning priority level (high / medium / low) into a value (such as high = 3, medium = 2, low = 1), and this mapping relationship is preset based on the engine cleaning requirements; the "value of the cleaning priority" refers to the above numerical result, and its inverse relationship is reflected in the conversion of the weight factor (such as the value 3 corresponds to the weight factor 0.5, and the value 1 corresponds to the weight factor 1.5). The weight factor is used to balance the adjustment coefficients of vibration energy in different priority areas, and the value range is 0.5 to 1.5. The inverse relationship means that the higher the priority value, the smaller the corresponding weight factor.

[0105] In the embodiment of the present application, the system internally sets a priority-weight comparison table to automatically convert the detected priority value into the corresponding weight factor. For example, the high-priority value 3 corresponds to the weight factor 0.8, the medium-priority value 2 corresponds to 1.0, and the low-priority value 1 corresponds to 1.2. This inverse design ensures that key areas obtain more vibration energy.

[0106] Step 302: Multiply the vibration frequency adjustment coefficient by the weight factor to obtain the initial correction amount reference value.

[0107] In step 302, the initial correction amount reference value is an intermediate parameter used to reflect the basic vibration energy requirement.

[0108] In the embodiment of the present application, the system multiplies the vibration frequency adjustment coefficient by the weight factor to obtain a preliminary correction amount reference value. For example, when the detected frequency adjustment coefficient in a certain area is 1.2 and the priority weight factor is 0.8, the calculated initial correction amount reference value is 0.96. This value will be used as the basis for subsequent compensation calculations.

[0109] Step 303: Calculate the compensation coefficient of the initial correction amount reference value based on the spacing parameter between the installation position of the piezoelectric ceramic array and the piston ring.

[0110] In step 303, the spacing parameter represents the physical distance between the piezoelectric ceramic array and the piston ring. The compensation coefficient is an adjustment parameter used to correct the vibration energy transfer loss.

[0111] In the embodiment of the present application, the system queries the vibration energy transfer loss curve according to the pre-measured installation spacing to determine the corresponding compensation coefficient. The larger the spacing, the larger the value of the compensation coefficient, so as to offset the energy attenuation during the transmission of the vibration wave.

[0112] Step 304: Multiply the initial correction amount reference value by the compensation coefficient to generate the amplitude attenuation gradient correction amount.

[0113] In the embodiment of the present application, the system multiplies the initial correction amount reference value by the compensation coefficient to obtain the final amplitude attenuation gradient correction amount. For example, multiplying the initial value 0.96 by the compensation coefficient 1.1 gives the correction amount 1.056. This parameter will guide the subsequent iterative adjustment of the vibration frequency.

[0114] The following is a specific example:

[0115] During the carbon deposit cleaning process in the second ring groove area of a certain type of diesel engine, for this high-priority area, the system first converts the cleaning priority level into the corresponding weight factor, which decreases as the priority increases to ensure that more vibration energy is obtained in the key area. Subsequently, the vibration frequency adjustment coefficient determined in advance according to the carbon deposit thickness is multiplied by this weight factor to obtain the initial correction amount reference value. Then the system measures the actual spacing between the piezoelectric ceramic array and this piston ring area, and performs a compensation calculation on the initial correction amount based on the spacing parameter to offset the energy loss during the transmission of the vibration wave. The finally generated amplitude attenuation gradient correction amount is used to guide the subsequent vibration frequency adjustment process, working in coordination with the previously determined shear vibration frequency to ensure the best cleaning effect in this key carbon deposit area while maintaining a reasonable distribution of vibration energy on the entire piston ring surface.

[0116] In the embodiments of the present application, this solution ensures differential vibration energy distribution in different priority regions through multi-parameter fusion calculation; compensates for the energy loss during the transmission of vibration waves; and the generated correction amount accurately reflects the actual cleaning requirements. The entire calculation process has a high degree of automation, and the parameter adjustment is precise and reliable.

[0117] To further improve the intelligent level of the cleaning path planning, in some embodiments, step 102: The fusion process of the piston ring material composition information, the real-time operation parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters includes:

[0118] Step 401: Generate the formulation parameters of the chemical solvent for cleaning the piston ring according to the piston ring material composition information and the real-time operation parameter data, where the formulation parameters include the ratio data of each group in the polar functional group and the concentration data of the chelating agent.

[0119] In step 401, the formulation parameters represent the process parameters for guiding the formulation of the chemical solvent. The polar functional group represents the chemical group with active reaction ability in the solvent molecule. The chelating agent concentration represents the content ratio of the metal ion complexing agent in the solvent.

[0120] In the embodiments of the present application, the system automatically generates the optimal solvent formula according to the piston ring material and the current working condition parameters through the material-solvent matching database. For example, for the chrome-plated cast iron material, a solvent formula containing a specific ratio of amino and carboxyl groups is recommended under high-temperature working conditions, and the corresponding chelating agent concentration is matched.

[0121] Step 402: Adjust the pulse frequency of the cleaning equipment for spraying the chemical solvent based on the ratio data of each group and the concentration data of the chelating agent.

[0122] In step 402, the pulse frequency represents the parameter for controlling the solvent spraying interval time.

[0123] In the embodiments of the present application, the system automatically adjusts the spraying frequency according to the activity strength of the solvent formula. A high-activity formula uses a higher frequency to achieve rapid cleaning, while a low-activity formula reduces the frequency to extend the action time. The frequency adjustment range covers various modes from low-frequency continuous spraying to high-frequency pulsed spraying.

[0124] Step 403: Extract the set of pixel points on the outer surface of the piston ring whose temperature exceeds the first preset threshold from the thermal imaging map data.

[0125] In step 403, the first preset threshold represents the temperature critical value for distinguishing the normal region from the carbon deposition region. The set of pixel points represents the coordinate set of the temperature abnormal region in the thermal imaging map.

[0126] In the embodiment of the present application, the system performs threshold segmentation processing on the thermal imaging map, extracts all pixel points exceeding the set temperature threshold, and forms a coordinate set of the suspected carbon deposition area. The threshold is dynamically adjusted according to the heat conduction characteristics of the piston ring material.

[0127] Step 404: Map the image coordinates of each pixel point in the pixel point set to the position coordinates of the corresponding area on the piston ring surface, and the corresponding area is the deposition area.

[0128] In step 404, the image coordinates represent the two-dimensional pixel coordinates collected by the thermal imager. The position coordinates represent the three-dimensional space coordinates of the piston ring surface. The deposition area is used to reflect that different deposition areas are the same as different areas on the piston ring surface.

[0129] In the embodiment of the present application, the system maps the two-dimensional image coordinates of the thermal imager to the three-dimensional surface of the piston ring through a pre-calibrated coordinate conversion model. This model takes into account parameters such as the installation angle of the thermal imager and lens distortion to ensure accurate spatial positioning.

[0130] Step 405: Determine the deposition layer thickness distribution parameters and cleaning priorities of each deposition area according to the temperature gradient change rate of each deposition area.

[0131] In step 405, the temperature gradient change rate represents a parameter indicating the speed of change of the temperature field in the carbon deposition area. The generation process is as follows: Extract the continuous temperature distribution data of each deposition area (the area where the temperature exceeds the threshold) from the thermal imaging map data; perform a spatial gradient operation on the temperature data in each deposition area (such as the temperature difference change rate along the circumferential and axial directions of the piston ring) to obtain the temperature gradient values of each point; take the maximum or average value of the temperature gradients of all pixel points in each deposition area as the temperature gradient change rate of the deposition area.

[0132] In the embodiment of the present application, the system analyzes the temperature gradient change characteristics of each deposition area, combines the thermal physical property parameters of the material, and uses a heat conduction inversion algorithm to calculate the carbon deposition thickness. At the same time, the cleaning priority is automatically assigned according to the thickness and regional location. Exemplarily, after detecting a high-temperature area in the second ring groove of a certain cylinder piston ring, the system first analyzes the temperature gradient change curves along the axial and circumferential directions of this area and finds that it presents a characteristic curve with a high center and a steep drop at the edge; combining the thermal conductivity parameter of the chrome-plated cast iron material of this piston ring, the distribution characteristics of a larger carbon deposition thickness in the central area and a gradual thinning in the edge area are inversely calculated through a heat conduction model; according to the inversion results, the central area with the largest thickness is marked as high priority, the transition area with medium thickness is marked as medium priority, and the edge area with smaller thickness is marked as low priority, forming a hierarchical cleaning strategy.

[0133] Step 406: Determine the solvent coverage area per unit time according to the pulse frequency, and generate a chemical solvent coverage path in combination with the position coordinates of each deposition area.

[0134] In step 406, the solvent coverage area represents the area of the cleaning region that can be covered by a single spray. The chemical solvent coverage path guides the spatial path of the nozzle movement trajectory.

[0135] In the embodiment of the present application, the system calculates the coverage area per unit time according to the pulse frequency and nozzle characteristics, combines the distribution of the deposition areas, and uses a path optimization algorithm to generate an optimal cleaning trajectory to ensure efficient coverage of all carbon deposition areas. Exemplarily, according to the currently set medium pulse frequency and the nozzle fan-shaped spray angle parameter, the system calculates the width of the annular region that can be covered by a single spray; for the detected annularly distributed carbon deposition areas, a spiral progressive path planning algorithm is adopted, starting from the high-priority central thick carbon deposition area, and the spray trajectory is sequentially extended outward according to the pulse interval time, ensuring that the annular region covered by each pulse period has appropriate overlap with the adjacent regions, and at the same time giving priority to ensuring the number of repeated cleaning times in the thick carbon deposition area, and finally generating an optimal cleaning trajectory from the inside to the outside and from dense to sparse.

[0136] Step 407: According to the chemical solvent coverage path, combine the deposition layer thickness distribution parameters and the cleaning priorities of all deposition areas to generate dynamic cleaning path parameters.

[0137] In the embodiment of the present application, the system integrates data such as the solvent formula, spraying parameters, cleaning path, carbon deposition thickness, and priority into a structured parameter set, providing a complete input for subsequent vibration parameter adjustment and phase control.

[0138] The following is a specific example:

[0139] During the cleaning process of a certain type of diesel engine piston ring, the system detects that the second ring groove area is made of chrome-plated cast iron. Combining the current medium-high load working conditions, it automatically generates a solvent formula containing specific active groups and the corresponding chelating agent ratio. After setting the pulse spraying frequency of the cleaning equipment according to the activity degree of the solvent, the system identifies a large area of high-temperature abnormal points in this ring groove area from the thermal imaging data, and accurately locates the deposition area on the piston ring surface through coordinate transformation. By analyzing the temperature gradient change characteristics of the deposition area, the distribution condition that the carbon deposition is thicker in the central area and thinner at the edge is inversely deduced, and the central area is marked as a high-priority cleaning area. After calculating the solvent coverage range based on the set pulse frequency, the system plans a cleaning path that spirally expands from the central thick carbon deposition area to the periphery. Finally, it integrates the deposition layer thickness distribution, priority order, and cleaning path parameters to form a complete dynamic cleaning plan, providing an accurate input basis for subsequent vibration frequency adjustment and phase control, and ensuring the best cleaning effect for this key area.

[0140] In the embodiments of the present application, this solution ensures the perfect matching of chemical solvents with the piston ring material and working conditions through multi-dimensional data fusion; accurately identifies and locates the carbon deposition areas; and generates an optimized cleaning path. The entire solution improves the cleaning efficiency and quality while reducing solvent consumption.

[0141] To further improve the accuracy of carbon deposition thickness detection and cleaning priority division, in some embodiments, step 405: determining the deposition layer thickness distribution parameters and cleaning priorities of each deposition area according to the temperature gradient change rate of each deposition area includes:

[0142] Step 501: Calculate the thermal diffusion resistance coefficient of the corresponding deposition area according to the temperature gradient change rate of each deposition area.

[0143] In step 501, the temperature gradient change rate represents the temperature change amount per unit distance within the deposition area. The thermal diffusion resistance coefficient is a parameter representing the ability of the carbon deposition layer to impede heat transfer, and a larger value indicates a thicker carbon deposition.

[0144] In the embodiments of the present application, the system establishes a mathematical model of the temperature gradient and thermal resistance through the heat conduction equation, and inversely calculates the thermal diffusion resistance coefficient of each deposition area according to the measured temperature gradient change rate. Specifically, an iterative approximation algorithm is used to minimize the error between the calculated value and the measured temperature distribution through multiple fittings, and finally an accurate thermal diffusion resistance coefficient is obtained.

[0145] Step 502: Map the thermal diffusion resistance coefficient of each deposition area to the deposition layer thickness distribution parameter of the corresponding deposition area.

[0146] In step 502, the mapping relationship represents a pre-calibrated thermal resistance-thickness corresponding curve through experiments.

[0147] In the embodiments of the present application, the system queries the pre-established material-thermal resistance-thickness relationship database and converts the calculated thermal diffusion resistance coefficient into the corresponding deposition layer thickness parameter. For chromed cast iron materials, the thermal resistance coefficient linearly corresponds to the carbon deposition thickness within a certain range within a certain interval.

[0148] Step 503: Determine the cleaning priority of the corresponding deposition area according to the deposition layer thickness distribution parameter and position coordinates of each deposition area.

[0149] In step 503, the position coordinates represent the spatial position information of the deposition area on the piston ring surface.

[0150] In the embodiments of the present application, the system divides the basic priority according to the size of the thickness parameter, and at the same time corrects it in combination with the position coordinates. For example, the priority of thick carbon deposition in the corresponding area of the combustion chamber is higher than that of other areas, and the priority of thin carbon deposition in the edge area is lower than that of the central area. Finally, a cleaning priority that comprehensively considers thickness and position factors is generated.

[0151] The following is a specific example:

[0152] In the second ring groove of a certain cylinder piston ring, an annular deposition area is detected. The system analyzes the characteristics of the temperature gradient change. The central area shows a steep gradient, and a large thermal diffusion resistance coefficient is calculated, which is mapped to a thicker carbon deposit layer; the gradient in the edge area is gentle, corresponding to a thinner carbon deposit layer. According to the thickness, the central area is defined as high priority, the transition area as medium priority, and the edge area as low priority. At the same time, considering that this ring groove is located below the combustion chamber, the priority levels of each area are appropriately increased, and finally a hierarchical cleaning strategy is generated.

[0153] In the embodiment of the present application, this solution accurately quantifies the thickness distribution of the carbon deposit layer through thermodynamic analysis, providing a reliable basis for adjusting the vibration parameters; intelligently divides the cleaning priorities to ensure that key areas are given priority for cleaning.

[0154] In order to further improve the accuracy of vibration frequency optimization, in some embodiments, step 204: generating a shear vibration frequency according to the reduced vibration frequency and the amplitude attenuation gradient correction amount includes:

[0155] Step 601: Generate a candidate target frequency based on the reduced vibration frequency.

[0156] In step 601, the reduced vibration frequency represents the current working frequency after being adjusted by the amplitude attenuation gradient correction. The candidate target frequency refers to the temporary vibration frequency that passes the verification of the vibration energy distribution uniformity after gradually reducing the initial vibration frequency.

[0157] In the embodiment of the present application, when the vibration energy distribution uniformity meets the standard, the system records the current working frequency as the candidate target frequency. This frequency has been adjusted through multiple iterations and can ensure the basic uniform distribution of vibration energy on the piston ring surface.

[0158] Step 602: Determine the product result of the candidate target frequency and the amplitude attenuation gradient correction amount as the frequency compensation value.

[0159] In step 602, the frequency compensation value is used as an additional amount for final frequency fine-tuning.

[0160] In the embodiment of the present application, the system multiplies the candidate target frequency by the amplitude attenuation gradient correction amount and then multiplies by a preset proportional coefficient to obtain the frequency compensation value. This compensation value is mainly used to offset the attenuation of vibration energy during transmission to ensure that the final frequency can meet the cleaning requirements of the thickest carbon deposit area.

[0161] Step 603: Add the candidate target frequency and the frequency compensation value to generate a shear vibration frequency.

[0162] In the embodiments of the present application, the system adds the candidate target frequency to the calculated frequency compensation value to generate the final shear vibration frequency. This frequency not only ensures the uniform distribution of vibration energy but also appropriately strengthens the key carbon deposition areas.

[0163] The following is a specific example:

[0164] During the cleaning process of a certain cylinder piston ring, the system obtains the candidate target frequency through iterative frequency reduction. At this time, the vibration energy distribution is basically uniform. According to the amplitude decay gradient correction amount in this area, the corresponding frequency compensation value is calculated. After adding the two, the final shear vibration frequency is obtained. This frequency not only maintains good energy distribution uniformity but also ensures the cleaning intensity of the key carbon deposition areas.

[0165] In the embodiments of the present application, this solution ensures the uniform distribution of vibration energy through iterative frequency reduction; strengthens the cleaning effect of key areas through compensation calculation; and finally generates a shear vibration frequency that can adapt to the actual cleaning requirements of the piston ring.

[0166] To further improve the accuracy of the synergistic effect of chemical cleaning and mechanical vibration, in some embodiments, step 105: calculating the phase difference between the pulse frequency and the shear vibration frequency according to the pulse frequency and the shear vibration frequency includes:

[0167] Step 701: Obtain the first time series of the pulse signal generated by the cleaning device and the second time series of the shear vibration signal generated by the piezoelectric ceramic array. Among them, the first time series is defined by the opening time and closing time of the solvent injection valve in the cleaning device corresponding to the pulse frequency, and the second time series is defined by the rising edge and falling edge of the resonant waveform corresponding to the shear vibration frequency.

[0168] In step 701, the first time series represents the working timing signal of the injection valve of the cleaning device. The second time series represents the timing signal of the piezoelectric ceramic vibration waveform. The valve opening / closing time represents the key time nodes of the injection valve action. The rising / falling edge of the resonant waveform represents the characteristic turning points of the vibration waveform.

[0169] In the embodiments of the present application, the system collects the switching action signals of the injection valve through a high-precision timer, and at the same time uses a vibration sensor to record the resonant waveform of the piezoelectric ceramic. After synchronous sampling of the two signals, the switching time points of the injection pulses and the characteristic points of the vibration waveform are respectively extracted to establish a corresponding time series data set.

[0170] Step 702: Extract the valve opening time points of each pulse in the first time series, and extract the peak time points of the oscillation waveform in the corresponding period in the second time series.

[0171] In step 702, the valve opening time point represents the moment when the solvent starts to be injected within a single injection cycle. The peak time point represents the moment when the vibration waveform reaches the maximum amplitude.

[0172] In the embodiment of the present application, the system performs feature point recognition on the collected time series data. The opening moment of the injection valve is determined by the edge detection algorithm, and the peak moment of the vibration signal is located by the peak detection algorithm. To ensure the accuracy of the corresponding relationship, the system takes the vibration cycle as the reference and matches the injection pulses within the same cycle.

[0173] Step 703: Calculate the time difference between the valve opening time point and the peak time point within the same cycle, and map the time difference to a phase difference.

[0174] In step 703, the time difference represents the time interval between the valve opening and the peak moment.

[0175] In the embodiment of the present application, the system calculates the time difference between the injection start and the peak within the same vibration cycle, and then converts this time difference into a phase angle according to the current vibration frequency. For example, if the time difference within a certain cycle is 1 / 4 of the vibration cycle, the corresponding phase difference is 90 degrees. The system establishes a linear mapping relationship between the time difference and the phase angle to achieve fast conversion.

[0176] The following is a specific example:

[0177] During the cleaning process of a piston ring of a certain cylinder, the system detects a time difference between the opening moment of the injection valve and the peak moment of the vibration within the current cycle. After calculation, this time difference accounts for a specific proportion of the vibration cycle and is converted into a corresponding phase difference angle according to the preset mapping relationship. Based on this phase difference, the system dynamically adjusts the injection timing to make the solvent injection match the vibration peak precisely and achieve the best cleaning effect.

[0178] In the embodiment of the present application, this solution ensures the best coordination timing between the chemical solvent injection and the mechanical vibration through precise timing analysis and phase control; it adapts to different working conditions requirements through dynamic phase adjustment, improves the carbon deposit removal efficiency and reduces the solvent consumption. The whole set of timing synchronization methods makes the cleaning process more accurate and efficient.

[0179] Figure 2 The structural schematic diagram of an engine piston ring non-dismantling cleaning system provided for the embodiment of the present application is as Figure 2 shown, and this system includes:

[0180] An acquisition module 21, configured to acquire the piston ring material composition information, real-time operation parameter data, and thermal imaging atlas data of the engine;

[0181] The fusion processing module 22 is configured to fuse the piston ring material composition information, the real-time operating parameter data, and the thermal imaging atlas data to generate dynamic cleaning path parameters, where the dynamic cleaning path parameters include deposition layer thickness distribution parameters and cleaning priorities for different regions on the piston ring surface;

[0182] The correction module 23 is configured to adjust the vibration frequency of the piezoelectric ceramic array attached to the outer side of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correct the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priorities to generate a shear vibration frequency;

[0183] The monitoring module 24 is configured to monitor the carbon deposit removal effect data on the piston ring surface in real time and compare the carbon deposit removal effect data with a preset removal standard;

[0184] The calculation module 25 is configured to calculate the phase difference between the pulse frequency and the shear vibration frequency according to the shear vibration frequency in combination with the pulse frequency, and dynamically adjust the phase difference based on the comparison result to remove the carbon deposit particles on the surface of the engine piston ring.

[0185] Figure 2 The described engine piston ring non-dismantling cleaning system based on closed-loop control can execute Figure 1 The described engine piston ring non-dismantling cleaning method based on closed-loop control in the illustrated embodiment, and its implementation principle and technical effects will not be elaborated further. For the engine piston ring non-dismantling cleaning system based on closed-loop control in the above embodiment, the specific ways for each module and unit to execute operations have been described in detail in the embodiment related to the method, and will not be elaborated here.

[0186] In a possible design, Figure 2 The engine piston ring non-dismantling cleaning system based on closed-loop control in the illustrated embodiment can be implemented as a computing device, as Figure 3 shown, and this computing device can include a storage component 31 and a processing component 32;

[0187] The storage component 31 stores one or more computer instructions, where the one or more computer instructions are called and executed by the processing component 32.

[0188] The processing component 32 performs the above Figure 1 The engine piston ring non-dismantling cleaning method based on closed-loop control in the illustrated embodiment.

[0189] Among them, the processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-mentioned method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for executing the above-mentioned method.

[0190] The storage component 31 is configured to store various types of data to support the operation of the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0191] Of course, the computing device may also necessarily include other components, such as input / output interfaces, display components, communication components, etc.

[0192] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above-mentioned peripheral interface module may be an output device, an input device, etc.

[0193] The communication component is configured to facilitate communication between the computing device and other devices in a wired or wireless manner, etc.

[0194] Among them, the computing device may be a physical device or an elastic computing host provided by a cloud computing platform, etc. At this time, the computing device may refer to a cloud server, and the above-mentioned processing component, storage component, etc. may be basic server resources leased or purchased from a cloud computing platform.

[0195] The embodiments of the present application also provide a computer storage medium storing a computer program, and when the computer program is executed by a computer, it can implement the above-mentioned Figure 1 method for non-dismantling cleaning of engine piston rings based on closed-loop control in the embodiments shown.

[0196] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0197] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0198] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0199] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A non-dismantling cleaning method for engine piston rings based on closed-loop control, characterized in that, Including: Obtaining the material composition information of the piston ring of the engine, real-time operating parameter data, and thermal imaging map data; Fusing the piston ring material composition information, the real-time operating parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters, where the dynamic cleaning path parameters include deposition layer thickness distribution parameters and cleaning priorities for different regions on the piston ring surface; Adjusting the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correcting the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priorities to generate a shear vibration frequency; Real-time monitoring the carbon deposit removal effect data on the piston ring surface, and comparing the carbon deposit removal effect data with a preset removal standard; Calculating the phase difference between the pulse frequency and the shear vibration frequency according to the shear vibration frequency in combination with the pulse frequency, and dynamically adjusting the phase difference based on the comparison result to remove carbon deposit particles on the surface of the engine piston ring.

2. The method according to claim 1, wherein The step of adjusting the vibration frequency of the piezoelectric ceramic array attached to the outside of the engine cylinder block according to the deposition layer thickness distribution parameters, and iteratively correcting the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priorities to generate a shear vibration frequency includes: Based on the mapping relationship between the preset deposition layer thickness distribution parameters and the vibration frequency adjustment coefficient, converting the deposition layer thickness distribution parameters into vibration frequency adjustment coefficients according to the preset ratio corresponding to the deposition layer thickness interval; Generating an amplitude attenuation gradient correction amount based on the vibration frequency adjustment coefficient and the cleaning priorities; Based on the initial vibration frequency of the piezoelectric ceramic array, taking the amplitude attenuation gradient correction amount as the step size, and iteratively reducing the vibration frequency of the piezoelectric ceramic array step by step; Monitoring the uniformity of the vibration energy distribution on the outside of the engine cylinder block, and when the vibration energy distribution uniformity reaches the preset distribution uniformity range, generating a shear vibration frequency according to the reduced vibration frequency and the amplitude attenuation gradient correction amount.

3. The method according to claim 2, characterized in that The step of generating an amplitude attenuation gradient correction amount based on the vibration frequency adjustment coefficient and the cleaning priorities includes: Converting the value of the cleaning priority into a weight factor according to a preset segmentation rule, where the weight factor is inversely proportional to the value of the cleaning priority; Multiplying the vibration frequency adjustment coefficient by the weight factor to obtain an initial correction amount reference value; Calculating a compensation coefficient for the initial correction amount reference value based on the spacing parameter between the installation position of the piezoelectric ceramic array and the piston ring; Multiplying the initial correction amount reference value by the compensation coefficient to generate an amplitude attenuation gradient correction amount.

4. The method according to claim 1, characterized in that, The step of fusing the piston ring material composition information, the real-time operating parameter data, and the thermal imaging map data to generate dynamic cleaning path parameters includes: Generating formulation parameters for the chemical solvent used to clean the piston ring according to the piston ring material composition information and the real-time operating parameter data, where the formulation parameters include the ratio data of each group in the polar functional group and the concentration data of the chelating agent; Adjust the pulse frequency of the cleaning equipment for spraying the chemical solvent based on the ratio data of the respective groups and the concentration data of the chelating agent; Extract a set of pixel points with the outer surface temperature of the piston ring exceeding the first preset threshold from the thermal imaging map data; Map the image coordinates of each pixel point in the set of pixel points to the position coordinates of the corresponding area on the piston ring surface, and the corresponding area is the deposition area; Determine the deposition layer thickness distribution parameters and the cleaning priorities of each deposition area according to the temperature gradient change rate of each deposition area; Determine the solvent coverage area per unit time according to the pulse frequency, and generate a chemical solvent coverage path in combination with the position coordinates of each deposition area; According to the chemical solvent coverage path, merge the deposition layer thickness distribution parameters and the cleaning priorities of all deposition areas to generate dynamic cleaning path parameters.

5. The method according to claim 4, wherein The determining the deposition layer thickness distribution parameters and the cleaning priorities of each deposition area according to the temperature gradient change rate of each deposition area includes: Calculate the thermal diffusion resistance coefficient of the corresponding deposition area according to the temperature gradient change rate of each deposition area; Map the thermal diffusion resistance coefficients of each deposition area to the deposition layer thickness distribution parameters of the corresponding deposition area; Determine the cleaning priority of the corresponding deposition area according to the deposition layer thickness distribution parameter and the position coordinate of each deposition area.

6. The method according to claim 2, wherein The generating the shear vibration frequency according to the reduced vibration frequency and the amplitude attenuation gradient correction amount includes: Generate a candidate target frequency based on the reduced vibration frequency; Determine the frequency compensation value as the product result of the candidate target frequency and the amplitude attenuation gradient correction amount; Add the candidate target frequency and the frequency compensation value to generate the shear vibration frequency.

7. The method according to claim 1, wherein The calculating the phase difference between the pulse frequency and the shear vibration frequency according to the pulse frequency and the shear vibration frequency includes: Obtain the first time series of the pulse signal generated by the cleaning equipment and the second time series of the shear vibration signal generated by the piezoelectric ceramic array, wherein the first time series is defined by the opening time and the closing time of the solvent injection valve in the cleaning equipment corresponding to the pulse frequency, and the second time series is defined by the rising edge and the falling edge of the resonant waveform corresponding to the shear vibration frequency; Extract the valve opening time point of each pulse in the first time series, and extract the peak time point of the oscillation waveform in the corresponding period in the second time series; Calculate the time difference between the valve opening time point and the peak time point in the same period, and map the time difference to the phase difference.

8. An engine piston ring non-dismantling cleaning system based on closed-loop control, characterized in that, Includes: An acquisition module for acquiring the piston ring material composition information, real-time operation parameter data and thermal imaging map data of the engine; A fusion processing module for performing fusion processing on the piston ring material composition information, the real-time operation parameter data and the thermal imaging map data to generate dynamic cleaning path parameters, and the dynamic cleaning path parameters include deposition layer thickness distribution parameters and cleaning priorities for different areas on the piston ring surface; A correction module, configured to adjust the vibration frequency of a piezoelectric ceramic array attached to the outer side of an engine cylinder block according to the deposition layer thickness distribution parameter, and iteratively correct the amplitude attenuation gradient of the piezoelectric ceramic array in combination with the cleaning priority to generate a shear vibration frequency; A monitoring module, configured to monitor in real time the carbon deposit removal effect data on the piston ring surface area, and compare the carbon deposit removal effect data with a preset cleaning standard; A calculation module, configured to calculate a phase difference between the pulse frequency and the shear vibration frequency according to the shear vibration frequency in combination with the pulse frequency, and dynamically adjust the phase difference based on the comparison result to remove carbon deposit particles on the surface of the engine piston ring.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a non-dismantling cleaning method for an engine piston ring based on closed-loop control as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, A computer program is stored, and when the computer program is executed by a computer, it implements a non-dismantling cleaning method for an engine piston ring based on closed-loop control as described in any one of claims 1 to 7.

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