Bearing lubrication intelligent regulation and control grease supplementing system based on temperature-vibration feedback

Abstract

The invention discloses a bearing lubrication intelligent regulation and control grease supplementing system based on temperature-vibration feedback, relates to the technical field of bearing lubrication intelligent regulation and control, and aims to solve the technical problem that lubrication supply and actual requirements are mismatched due to the fact that a traditional bearing grease supplementing system cannot accurately recognize complex working conditions of instantaneous impact and nonlinear transition. Comprising a detection module used for collecting a temperature signal, a vibration signal and a lubrication state correlation signal in the bearing operation process in real time and transmitting the temperature signal, the vibration signal and the lubrication state correlation signal to a control module; the control module is used for receiving the signal, performing interference filtering processing on the signal, analyzing the correlation characteristics of the temperature signal and the vibration signal to identify the current operation working condition of the bearing, and generating a grease supplementing regulation and control instruction matched with the working condition in combination with the lubricating state correlation signal; and a grease supplementing execution module. The method has the advantages of accurately adapting to different working conditions of the bearing to realize dynamic grease supplementing, and forming closed-loop regulation and control to guarantee the lubricating effect.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for bearing lubrication, and more specifically, to an intelligent control and grease replenishment system for bearing lubrication based on temperature-vibration feedback. Background Technology

[0002] In the core transmission system of continuous rolling mills in large steel enterprises, the four-row cylindrical roller bearings supporting the rolls are key components ensuring rolling continuity and product precision. These bearings operate under continuous high loads and dynamic, complex conditions for extended periods: on the one hand, instantaneous impacts occur when the workpiece bites in (e.g., when strip steel bites in a cold continuous rolling mill, the bearing vibration peak can rise sharply within 0.1 seconds); on the other hand, when changing rolling specifications (e.g., switching from 5mm to 8mm thick strip steel), the bearings experience a nonlinear transition from low speed and high load to high speed and low load; simultaneously, interference factors such as electromagnetic interference from the mill motor and load transmission between multiple bearings (e.g., load fluctuations from adjacent support bearings are transmitted to the target bearing) exist around the unit, causing the bearing operating status signal to be easily distorted. Currently, most mainstream bearing grease replenishment systems in this scenario adopt control methods such as "fixed-cycle grease replenishment" or "single-temperature threshold triggered grease replenishment," which have core technical problems: they cannot accurately identify complex working conditions such as instantaneous impacts and nonlinear transitions, and their resistance to external interference and multi-bearing load transmission interference is weak, resulting in a serious mismatch between lubrication supply and actual demand. During instantaneous impacts, grease replenishment is not timely, and the pre-lubricating film cannot resist the extrusion and loss of lubricating medium caused by the impact, resulting in local wear of the bearing raceway. During nonlinear transitions, the grease replenishment rate is fixed, which easily leads to insufficient lubrication in the early stage of the transition and excessive lubrication in the later stage. At the same time, electromagnetic interference and load transmission interference can easily cause system misjudgment, resulting in ineffective grease replenishment or grease leakage, which not only shortens the service life of the bearing, but also causes unplanned downtime of the continuous rolling line due to bearing failure, resulting in huge economic losses. In view of this, we propose a bearing lubrication intelligent control grease replenishment system based on temperature-vibration feedback. Summary of the Invention

[0003] The purpose of this invention is to provide a bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback, so as to solve the technical problem that traditional bearing grease replenishment systems cannot accurately identify complex working conditions such as instantaneous impact and nonlinear transition, resulting in a mismatch between lubrication supply and actual demand.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback, comprising: The detection module is used to collect temperature signals, vibration signals, and lubrication status-related signals during the bearing operation in real time, and transmit the temperature signals, vibration signals, and lubrication status-related signals to the control module. After receiving the signal, the control module first performs interference filtering on the signal, then analyzes the correlation characteristics between the temperature signal and the vibration signal to identify the current operating condition of the bearing, and at the same time generates a grease replenishment control command that is suitable for the operating condition by combining the lubrication status correlation signal. The fat replenishment execution module communicates with the control module, receives fat replenishment control commands, and executes corresponding dynamic fat replenishment actions. The feedback verification module is used to collect bearing operation feedback signals after grease replenishment and transmit the operation feedback signals to the control module to verify the lubrication effect, forming a closed-loop control link of "detection-identification-control-verification". The control module distinguishes the characteristic differences between temperature signals and vibration signals under different operating conditions, adapts to the lubrication requirements of bearings under different operating conditions, and eliminates the influence of external environmental interference and multi-bearing load transmission on signal analysis.

[0005] Preferably, the detection module includes a temperature sensing unit, a vibration sensing unit, and a lubrication status sensing unit; The temperature sensing unit and vibration sensing unit are respectively arranged in the raceway area, bearing housing area and lubrication point area of ​​the bearing to collect multi-dimensional temperature and vibration signals of the bearing. The lubrication status sensing unit is used to collect the oil film thickness correlation signal or friction coefficient correlation signal in the bearing lubrication area, as a direct feedback basis for judging the lubrication effect. The detection module is also equipped with a signal preprocessing unit, which is used to filter and reduce noise of the collected raw temperature signal, vibration signal and lubrication status related signal, eliminate signal distortion caused by electromagnetic interference and mechanical resonance in the rolling environment, and ensure the accuracy of the signal transmitted to the control module.

[0006] Preferably, the operating condition identification function of the control module includes the following steps: The first step is to invoke a preset anti-interference algorithm to filter out pulse interference components in the temperature and vibration signals; The second step is to perform synchronous analysis on the changing trends of the filtered temperature signal and vibration signal to identify synchronous change characteristics, temporal misalignment characteristics, or nonlinear gradient change characteristics between the two. The third step is to determine the bearing operating condition based on the identification results: when the temperature signal and vibration signal have the same trend and the rate of change does not change abruptly, the bearing is determined to be in normal operating condition; when the vibration signal first shows a peak change and the temperature signal changes after a preset time delay, the bearing is determined to be in instantaneous impact condition; when the rate of change of the temperature signal and vibration signal shows a nonlinear difference, the bearing is determined to be in nonlinear transition condition.

[0007] Preferably, when the control module determines that the bearing is under instantaneous impact, it will also classify the intensity of the instantaneous impact based on the peak amplitude and rise rate of the vibration signal; the impact intensity classification includes mild impact, moderate impact, and severe impact, wherein mild impact corresponds to the vibration peak amplitude increase rate. The increase in peak vibration corresponding to moderate impact The peak vibration increase corresponding to severe impact ; The control module matches the pre-lubricating film thickness requirement of the bearing at the impact strength level. The higher the impact strength, the greater the pre-lubricating film thickness requirement. At the same time, it calculates the predictive grease replenishment amount to match the impact strength level by combining the size parameters of the bearing raceway. Specifically, the quantitative calculation of impact strength is achieved through the following algorithm formula: ; in, Instantaneous impact intensity This represents the peak value increase of the vibration signal during a momentary impact. This is the reference value for the peak vibration of the bearing under normal operating conditions. according to The calculation results are used to classify the impact level: when It was a mild impact, when At that time, it was a moderate impact, when It was a severe impact.

[0008] Preferably, when the control module detects a predicted signal of an instantaneous impact condition, it generates a graded predictive fat replenishment control command. After receiving the graded predictive fat replenishment control command, the fat replenishment execution module adjusts the action parameters of its controllable execution units according to the impact intensity level. Under mild impact conditions, the control delivery pipeline unit delivers the first amount of grease at a first rate to form a thin pre-lubricating film on the bearing surface; Under moderate impact conditions, the control delivery pipeline unit delivers the second amount of grease at a second rate to form a medium-sized pre-lubricating film on the bearing surface; Under severe impact conditions, the control delivery pipeline unit delivers the third amount of grease at the third rate. The grease delivery module completes the laying of the pre-lubricating film before the vibration signal reaches its peak, so as to resist the squeezing and loss of lubricating medium caused by instantaneous impact. Specifically, the calculation of graded predictive fat supplementation is achieved through the following algorithm formula: ; according to The corresponding impact level matches different Value: Taken for mild impact Take during moderate impact Take during severe impact Then, the first amount of fat supplementation was calculated. Second amount of fat supplementation Third amount of fat supplementation ; in, For predictive fat supplementation, For fat supplementation coefficient, Instantaneous impact intensity Let be the circumference of the bearing raceway. This refers to the width of the bearing raceway.

[0009] Preferably, after the instantaneous impact condition ends, the control module collects the bearing vibration attenuation rate signal after grease replenishment through the feedback verification module; If the vibration attenuation rate If the preset threshold is set, the pre-lubricating film will remain intact and the lubrication effect will meet the standard, without the need for additional grease replenishment. If the vibration attenuation rate A preset threshold indicates that the pre-lubricating film is damaged or the lubricating medium is lost, and the control module generates a graded repair-type grease replenishment control command. The graded repair-type grease replenishment control command determines the amount of grease replenishment based on the difference between the vibration decay rate and the preset threshold. The larger the difference, the more grease is replenished, thereby controlling the grease replenishment execution module to replenish the lubricating medium and ensuring the lubrication effectiveness of the bearing in subsequent operation. Specifically, the amount of fat replenishment for graded repair is calculated using the following algorithm formula: ; in, To restore fat intake, The repair coefficient is... This represents the difference in vibration decay rates. This is a predictive fat supplementation amount.

[0010] Preferably, when the control module determines that the bearing is in a nonlinear transition condition, it first uses a curve fitting algorithm to fit the change rates of the temperature signal and the vibration signal into nonlinear change curves, and then identifies the "rate inflection point" on the nonlinear change curve; based on the rate inflection point, the nonlinear transition condition is divided into multiple segmented conditions, including a rapid change condition in the first segment and a slow change condition in the second segment. The control module calculates the corresponding fat replenishment rate adjustment coefficient for each segment of the working condition. The fat replenishment rate adjustment coefficient for the rapidly changing working condition in the first segment is greater than the fat replenishment rate adjustment coefficient for the slowly changing working condition in the second segment, thereby generating a segmented gradient fat replenishment control command. Specifically, the fitting of the nonlinear change curve and the identification of the rate inflection point are achieved through the following algorithm formula: First, the rate of temperature change and vibration change rate By performing quadratic function fitting on each, we obtain: ; ; Secondly, the inflection point of the rate corresponds to the extreme point of the rate of change. The inflection point time can be calculated by taking the derivative and setting the derivative to 0: ; ; Pick As a segment node for nonlinear transient conditions, For the rapidly changing operating conditions in the previous stage, This refers to the later stage of slowly changing operating conditions; in, For the rate of temperature change, The rate of change of vibration, For time, , , The coefficients of the fitted curve for the rate of temperature change are... , , The coefficients are those of the fitted curve of the vibration rate change. The inflection point of the fitted curve of the rate of temperature change. The inflection point of the fitted curve of the vibration rate change is given. The point is the segmented node time for the nonlinear transient condition.

[0011] Preferably, after receiving the segmented gradient fat replenishment control command, the fat replenishment execution module controls the controllable execution unit to gradually increase the amount of fat replenishment at a relatively fast rate when the working conditions change rapidly in the early stage; after reaching the rate inflection point, it switches to gradually increasing the amount of fat replenishment at a slower rate. Meanwhile, the feedback verification module collects the temperature signal and vibration signal changes in real time after grease replenishment. If the synchronicity of the two changes is improved to the preset range, it means that the current grease replenishment parameters are adapted to the segmented working conditions. If the synchronicity of the changes is not improved, the control module will correct the grease replenishment rate adjustment coefficient according to the synchronicity deviation to further optimize the grease replenishment rate in order to adapt to the dynamic lubrication requirements of nonlinear transition working conditions. Specifically, the calculation and correction of the fat replenishment rate adjustment coefficient is achieved through the following algorithm formula: First, calculate the fat replenishment rate adjustment factor for the rapidly changing operating conditions in the initial stage. : ; Secondly, calculate the fat replenishment rate adjustment factor for the later stage of slow-changing operating conditions. : ; Finally, if the temperature-vibration change synchronization deviation is The corrected fat replenishment rate adjustment factor is: ; ; in, This is an adjustment factor for the fat replenishment rate under rapidly changing operating conditions in the initial stage. For rate coefficient, This represents the maximum rate of temperature change during the rapid temperature change conditions described earlier. This represents the average rate of temperature change during the rapid temperature change conditions described earlier. This is the adjustment factor for the fat replenishment rate under the later, slowly changing operating conditions. The attenuation coefficient is... This is due to the synchronization deviation of temperature and vibration changes. This is the adjusted coefficient for the pre-operative fat replenishment rate. This is the adjustment factor for the corrected post-fat replenishment rate.

[0012] Preferably, it also includes a working condition self-updating module, which is communicatively connected to the control module and the feedback verification module, and is used to record the entire chain data of "working condition identification - grease replenishment adjustment - lubrication effect verification"; When the lubrication effect verification result for a certain working condition fails to meet the standard three times in a row, the working condition self-updating module triggers the parameter optimization process of the control module. The control module re-analyzes the correlation characteristics of temperature and vibration signals under the working condition, adjusts the working condition identification threshold and corresponding grease replenishment parameters, and updates the preset working condition feature template.

[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention collects temperature, vibration, and oil film thickness / friction coefficient related signals in multiple areas of the bearing raceway, bearing housing, and lubrication point through a detection module. Combined with the anti-interference algorithm of the control module and the analysis of working condition correlation characteristics, it can accurately distinguish between normal, instantaneous impact, and nonlinear transition working conditions, and eliminate interference from multi-bearing load transmission. It generates grease replenishment control commands adapted to the working conditions, fundamentally solving the problem of lubrication mismatch caused by inaccurate working condition identification and weak anti-interference ability of traditional systems, and ensuring that the bearing lubrication supply under complex working conditions is highly matched with the actual needs.

[0014] 2. The present invention also collects signals such as vibration decay rate and temperature-vibration synchronicity after grease replenishment through a feedback verification module, forming a closed-loop link of "detection-identification-control-verification". If the vibration decay rate does not reach the preset threshold, a repair grease replenishment command can be generated in real time; if the temperature-vibration synchronicity deviation is large, the grease replenishment rate adjustment coefficient can be corrected to avoid hidden lubrication defects caused by grease replenishment execution deviation or sudden change in operating conditions, and further improve the bearing operation stability.

[0015] 3. The present invention also records the entire chain data of "operating condition identification - grease replenishment control - lubrication effect verification" through the operating condition self-updating module. When the lubrication effect of a certain operating condition fails to meet the standard for three consecutive times, the parameter optimization process is automatically triggered to readjust the operating condition identification threshold and grease replenishment coefficient, update the operating condition feature template, ensure that the system adapts to the operating condition changes after bearing aging in the long term, extend the effective period of the grease replenishment strategy, and reduce the risk of lubrication failure caused by outdated parameters. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0017] To facilitate understanding of the technical solution of the present invention by those skilled in the art, the technical solution of the present invention will now be further described in conjunction with the accompanying drawings.

[0018] Example 1, such as Figure 1 As shown, this invention provides a bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback, comprising: The detection module is used to collect temperature signals, vibration signals, and lubrication status-related signals during the bearing operation in real time, and transmit the temperature signals, vibration signals, and lubrication status-related signals to the control module. After receiving the signal, the control module first performs interference filtering on the signal, then analyzes the correlation characteristics between the temperature signal and the vibration signal to identify the current operating condition of the bearing, and at the same time generates a grease replenishment control command that is suitable for the operating condition by combining the lubrication status correlation signal. The fat replenishment execution module communicates with the control module, receives fat replenishment control commands, and executes corresponding dynamic fat replenishment actions. The feedback verification module is used to collect bearing operation feedback signals after grease replenishment and transmit the operation feedback signals to the control module to verify the lubrication effect, forming a closed-loop control link of "detection-identification-control-verification". The control module distinguishes the differences in characteristics between temperature and vibration signals under different operating conditions, adapts to the lubrication requirements of bearings under different operating conditions, and eliminates the influence of external environmental interference and multi-bearing load transmission on signal analysis, thereby achieving precise and intelligent control of bearing lubrication.

[0019] In an embodiment of the present invention, the detection module includes a temperature sensing unit, a vibration sensing unit, and a lubrication status sensing unit. Temperature sensing units and vibration sensing units are respectively arranged in the raceway area, bearing housing area and lubrication point area of ​​the bearing to collect multi-dimensional temperature and vibration signals of the bearing. The lubrication status sensing unit is used to collect the oil film thickness correlation signal or friction coefficient correlation signal in the bearing lubrication area, as a direct feedback basis for judging the lubrication effect; The detection module is also equipped with a signal preprocessing unit, which is used to filter and reduce noise of the acquired raw temperature signal, vibration signal and lubrication status related signal, eliminate signal distortion caused by electromagnetic interference and mechanical resonance in the rolling environment, and ensure the accuracy of the signal transmitted to the control module.

[0020] In an embodiment of the present invention, the operating condition identification function of the control module includes the following steps: The first step is to invoke a preset anti-interference algorithm to filter out pulse interference components in the temperature and vibration signals; The second step is to perform synchronous analysis on the changing trends of the filtered temperature signal and vibration signal to identify synchronous change characteristics, temporal misalignment characteristics, or nonlinear gradient change characteristics between the two. The third step is to determine the bearing operating condition based on the identification results: when the temperature signal and vibration signal have the same trend and the rate of change does not change abruptly, the bearing is determined to be in normal operating condition; when the vibration signal first shows a peak change and the temperature signal changes after a preset time delay, the bearing is determined to be in instantaneous impact condition; when the rate of change of the temperature signal and vibration signal shows a nonlinear difference (including the rate of change being fast at first and then slow or slow at first and then fast), the bearing is determined to be in nonlinear transition condition.

[0021] In an embodiment of the present invention, when the control module determines that the bearing is under instantaneous impact, it will also classify the intensity of the instantaneous impact based on the peak amplitude and rise rate of the vibration signal; the impact intensity classification includes mild impact, moderate impact, and severe impact, wherein mild impact corresponds to the increase in the peak vibration value. The increase in peak vibration corresponding to moderate impact The peak vibration increase corresponding to severe impact ; The control module matches the pre-lubrication film thickness requirement of the bearing at the impact strength level. The higher the impact strength, the greater the pre-lubrication film thickness requirement. At the same time, it calculates the predictive grease replenishment amount adapted to the impact strength level by combining the bearing raceway size parameters, so as to avoid the problem of "excessive lubrication during light impact" or "insufficient lubrication during heavy impact" due to fixed grease replenishment amount. Specifically, the quantitative calculation of impact strength is achieved through the following algorithm formula: ; in, Instantaneous impact strength, unit: It is used to intuitively reflect the strength of the instantaneous impact on the bearing and is a key quantitative indicator for formulating subsequent lubrication strategies. This represents the peak value increase of the vibration signal during instantaneous impact, expressed in units of... It is the difference between the peak vibration value of the bearing under impact conditions and the peak vibration value under normal operating conditions. The larger the difference, the more significant the vibration change caused by the impact. This is the reference value for the peak vibration of the bearing under normal operating conditions, in units of... It is a reference standard for measuring vibration changes under impact conditions. This value is determined by long-term data collection during normal and stable operation of the bearing. according to The calculation results are used to classify the impact level: when It was a mild impact, when At that time, it was a moderate impact, when It was a severe impact; The core of this algorithm is to quantify the instantaneous impact intensity by calculating the ratio of the peak increase of the vibration signal during an instantaneous impact to the baseline value of the vibration peak under normal operating conditions. First, the difference between the peak vibration value under impact conditions and normal operating conditions is determined. Then, this difference is compared with the baseline value of the normal vibration peak and converted into a percentage. Based on the percentage result, different impact intensity levels are classified, providing a quantitative basis for subsequent matching of pre-lubricating film thickness and calculation of grease replenishment. This algorithm accurately quantifies and classifies instantaneous impact intensity, avoiding the problems caused by traditional grease filling systems that employ fixed grease filling strategies due to their inability to differentiate impact intensities. Different impact intensities correspond to different pre-lubricating film thickness requirements. Matching appropriate grease filling schemes based on quantified impact intensity ensures that excessive grease filling does not waste lubricating media or increase bearing resistance during mild impacts, while sufficient grease filling forms an effective pre-lubricating film during severe impacts, resisting the squeezing and loss of lubricating media caused by the impact. This ensures that the bearing receives appropriate lubrication protection under different impact conditions, extends bearing life, and reduces equipment failures caused by improper lubrication.

[0022] In an embodiment of the present invention, when the control module identifies a prediction signal of an instantaneous impact condition (i.e., the vibration signal begins to show an upward trend but has not reached its peak), it generates a graded prediction-based fat replenishment control command. After receiving the graded predictive fat replenishment control command, the fat replenishment execution module adjusts the action parameters of its controllable execution units according to the impact intensity level. Under mild impact conditions, the control delivery pipeline unit delivers the first amount of grease at a first rate to form a thin pre-lubricating film on the bearing surface; Under moderate impact conditions, the control delivery pipeline unit delivers a second grease replenishment amount at a second rate, wherein the second rate is greater than the first rate and the second grease replenishment amount is greater than the first grease replenishment amount, forming a medium-sized pre-lubricating film on the bearing surface; Under severe impact conditions, the control delivery pipeline unit delivers the third grease replenishment amount at the third rate, where the third rate is greater than the second rate and the third grease replenishment amount is greater than the second grease replenishment amount. The grease replenishment execution module completes the laying of the pre-lubricating film before the vibration signal reaches its peak value to resist the squeezing and loss of lubricating medium caused by instantaneous impact. Specifically, the calculation of graded predictive fat supplementation is achieved through the following algorithm formula: ; according to The corresponding impact level matches different Value: Taken for mild impact Take during moderate impact ( ), take during severe impact ( ), and then calculate the first amount of fat supplementation. Second amount of fat supplementation Third amount of fat supplementation ; in, The pre-lubrication amount is measured in ml and represents the total amount of lubricating medium that the lubrication execution module needs to deliver before an instantaneous impact condition. This directly determines the effectiveness of the pre-lubrication film formation. The grease replenishment coefficient is expressed in ml / (mm・%・mm). It is preset based on the viscosity, flowability and other characteristics of the lubricating medium. Different types of lubricating media correspond to different grease replenishment coefficients to ensure that the grease replenishment amount is adapted to the characteristics of the medium. The instantaneous impact intensity is expressed as a percentage and is a key operating condition parameter that affects the amount of fat replenishment required. The greater the impact intensity, the more fat replenishment is needed. This refers to the circumference of the bearing raceway, expressed in mm. It reflects the circumferential length of the raceway. The larger the circumference, the more lubricating medium is required to form a complete pre-lubricating film. This refers to the width of the bearing raceway, expressed in mm. It represents the axial dimension of the raceway. The larger the width, the greater the need for the distribution of lubricating medium along the axial direction of the raceway. This algorithm is based on instantaneous impact intensity, combined with the dimensional parameters of the bearing raceway (circumference and width) and a pre-set grease replenishment coefficient according to the type of lubricating medium, to construct a grease replenishment calculation model. First, the corresponding grease replenishment coefficient is determined based on the impact intensity level. Then, the grease replenishment coefficient, instantaneous impact intensity, raceway circumference, and width are multiplied to obtain the predicted grease replenishment amount required for different impact levels, achieving precise matching between grease replenishment amount and impact intensity, bearing structure, and lubricating medium characteristics. This algorithm combines instantaneous impact intensity, bearing structural parameters, and lubricant characteristics to achieve precise calculation of predictive grease replenishment. Compared to traditional fixed grease replenishment methods, it dynamically adjusts the grease replenishment amount based on different impact levels, bearing sizes, and lubricant types. This avoids lubricant waste during mild impacts and ensures sufficient pre-lubrication film thickness during severe impacts, effectively resisting lubricant loss due to impact compression. Simultaneously, the grease replenishment module completes the pre-lubrication film application before the vibration signal reaches its peak, providing reliable lubrication protection for the bearing under instantaneous impact conditions. This reduces bearing wear caused by impact, improves equipment operational stability, and lowers the risk of downtime due to insufficient lubrication.

[0023] In an embodiment of the present invention, after the instantaneous impact condition ends (i.e. the vibration signal drops from the peak to the normal operating range), the control module collects the bearing vibration attenuation rate signal after grease replenishment through the feedback verification module. If the vibration decay rate If the preset threshold is set, the pre-lubricating film will remain intact and the lubrication effect will meet the standard, without the need for additional grease replenishment. If the vibration decay rate A preset threshold indicates that the pre-lubricating film is damaged or the lubricating medium is lost, and the control module generates a graded repair-type grease replenishment control command. The graded repair-type grease replenishment control command determines the amount of grease replenishment based on the difference between the vibration decay rate and the preset threshold. The larger the difference, the more grease is replenished, thereby controlling the grease replenishment execution module to replenish the lubricating medium and ensure the lubrication effectiveness of the bearing in subsequent operation. Specifically, the amount of fat replenishment for graded repair is calculated using the following algorithm formula: ; in, The amount of grease to be replenished, expressed in ml, is the total amount of lubricating medium that needs to be replenished after the instantaneous impact condition to compensate for the damage to the pre-lubricating film or the loss of lubricating medium. The repair coefficient is expressed in units of 1 / (mm・s⁻²). It is preset based on the characteristics of the lubricating medium, such as its fluidity and diffusion rate. For lubricating media with better fluidity, the repair coefficient value can be adjusted appropriately to ensure that the repair grease can diffuse quickly and form effective lubrication. The vibration decay rate difference is expressed in mm / s², which is the difference between the preset vibration decay rate threshold and the actual vibration decay rate. The larger the difference, the more severe the damage to the pre-lubricating film or the greater the loss of lubricating medium, and the greater the amount of grease required for repair. The predicted fat replenishment amount is expressed in ml and serves as the basic reference for calculating the repair fat replenishment amount. Different predicted fat replenishment amounts will result in different calculation benchmarks for the repair fat replenishment amount. This algorithm combines instantaneous impact intensity, bearing structural parameters, and lubricant characteristics to achieve precise calculation of predictive grease replenishment. Compared to traditional fixed grease replenishment methods, it dynamically adjusts the grease replenishment amount based on different impact levels, bearing sizes, and lubricant types. This avoids lubricant waste during mild impacts and ensures sufficient pre-lubrication film thickness during severe impacts, effectively resisting lubricant loss due to impact. Simultaneously, the grease replenishment execution module completes the pre-lubrication film application before the vibration signal reaches its peak, providing reliable lubrication protection for the bearing under instantaneous impact conditions, reducing bearing wear, improving equipment operational stability, and lowering the risk of downtime due to insufficient lubrication. This algorithm calculates the amount of grease to be replenished, dynamically adjusting the amount based on the actual lubrication state of the bearing after an instantaneous impact. This precisely compensates for insufficient lubrication caused by damage to the pre-lubricating film or loss of lubricating medium. When the vibration decay rate meets the standard, it indicates good lubrication, requiring no additional grease and avoiding waste of lubricating medium. When the vibration decay rate does not meet the standard, the amount of grease to be replenished is precisely calculated based on the difference in decay rates, ensuring that the replenished lubricating medium effectively repairs lubrication defects and provides continuous and reliable lubrication protection for the bearing's subsequent operation. This dynamic grease replenishment strategy further improves the lubrication stability of bearings under complex operating conditions, reduces bearing wear and equipment failures caused by insufficient lubrication, extends equipment maintenance cycles, and reduces operating costs.

[0024] In an embodiment of the present invention, when the control module determines that the bearing is in a nonlinear transition condition, it first uses a curve fitting algorithm to fit the change rates of the temperature signal and the vibration signal into nonlinear change curves, and then identifies the "rate inflection point" (i.e. the node where the change rate changes from fast to slow or from slow to fast) on the nonlinear change curve; based on the rate inflection point, the nonlinear transition condition is divided into multiple segmented conditions, including the first segment of rapid change condition and the second segment of slow change condition. For each segment of the working condition, the control module calculates the corresponding fat replenishment rate adjustment coefficient. The fat replenishment rate adjustment coefficient for the rapidly changing working condition in the first segment is greater than that for the slowly changing working condition in the second segment, thereby generating a segmented gradient fat replenishment control command. Specifically, the fitting of the nonlinear change curve and the identification of the rate inflection point are achieved through the following algorithm formula: First, the rate of temperature change and vibration change rate By performing quadratic function fitting on each, we obtain: ; ; Secondly, the inflection point of the rate corresponds to the extreme point of the rate of change. The inflection point time can be calculated by taking the derivative and setting the derivative to 0: ; ; Pick As a segment node for nonlinear transient conditions, For the rapidly changing operating conditions in the previous stage, This refers to the later stage of slowly changing operating conditions; in, The rate of temperature change is the rate at which temperature changes over time, measured in °C / min, and reflects how quickly the bearing temperature changes at different times. The vibration rate is the rate of change of vibration over time, expressed in mm / s·min, and reflects the trend of bearing vibration at different times. Time, measured in minutes, is a time dimension reference for changes in operating conditions, used to measure the evolution of temperature and vibration rates over time. , , The coefficients of the temperature change rate fitting curve are calculated by a mathematical fitting algorithm from multiple sets of temperature signals acquired in real time. The values ​​of the coefficients determine the shape and trend of the temperature change rate fitting curve, ensuring that the curve can accurately reflect the nonlinear characteristics of the actual temperature change rate. , , The coefficients of the vibration rate fitting curve are calculated by a mathematical fitting algorithm from multiple sets of vibration signals acquired in real time. The magnitude of the coefficients determines the shape of the vibration rate fitting curve, ensuring that the curve is consistent with the nonlinear law of the actual vibration rate. The inflection point of the fitted curve of the rate of temperature change, in minutes, is the critical time point when the rate of temperature change changes from fast to slow or from slow to fast, marking the entry of the temperature change into different stages. The inflection point of the fitted curve of the vibration rate of change is expressed in minutes. It is the key time point at which the vibration rate of change changes and reflects the transition of the vibration change stage. The segmentation node time for nonlinear transient conditions is expressed in minutes, ensuring that the segmentation covers the critical transition stages of temperature and vibration changes. The algorithm first fits quadratic functions to the rates of temperature and vibration change, respectively. The fitted curves reflect the nonlinear changes in these rates over time. The coefficients of the quadratic functions are calculated from the real-time acquired temperature and vibration signals, ensuring that the fitted curves accurately reflect actual operating conditions. Then, based on the mathematical principle of differentiating quadratic functions and setting the derivative to zero, the algorithm calculates the times corresponding to the extreme points of the rates of temperature and vibration change, i.e., the inflection points. Finally, the maximum value of the two inflection points is taken as the segmentation node for the nonlinear transition condition, dividing the transition condition into a rapid change phase and a slow change phase, providing a clear basis for subsequent segmented adjustments to the grease replenishment rate. This algorithm achieves precise segmentation of nonlinear transition conditions through quadratic function fitting and inflection point identification, solving the problem of mismatch between lubrication strategies and operating conditions caused by the inability of traditional systems to accurately identify the stages of operating condition changes. The fitted curve accurately reflects the nonlinear characteristics of temperature and vibration change rates, and the calculation of inflection point times provides a clear and scientific basis for segmenting the operating conditions. After dividing the transition condition into two segments, rapid change and slow change, differentiated lubrication strategies can be formulated for the characteristics of different stages. This precise segmentation of operating conditions and targeted lubrication strategies ensure that the bearing receives appropriate lubrication supply at different stages of the transition condition, avoiding lubrication defects caused by insufficient lubrication in the early stage of the transition, and avoiding the waste of lubricating medium and increased bearing resistance caused by excessive lubrication in the later stage of the transition, thus improving the operating stability and lubrication efficiency of the bearing under nonlinear transition conditions.

[0025] In an embodiment of the present invention, after receiving a segmented gradient fat replenishment control command, the fat replenishment execution module controls the controllable execution unit to gradually increase the amount of fat replenishment at a relatively fast rate when the working conditions change rapidly in the early stage; after reaching the rate inflection point, it switches to gradually increasing the amount of fat replenishment at a slower rate. Meanwhile, the feedback verification module collects the synchronicity of temperature and vibration signals after grease replenishment in real time. If the synchronicity of the two changes improves to the preset range, it indicates that the current grease replenishment parameters are suitable for segmented working conditions. If the synchronicity does not improve, the control module corrects the grease replenishment rate adjustment coefficient according to the synchronicity deviation to further optimize the grease replenishment rate in order to adapt to the dynamic lubrication requirements of nonlinear transition working conditions.

[0026] Specifically, the calculation and correction of the fat replenishment rate adjustment coefficient is achieved through the following algorithm formula: First, calculate the fat replenishment rate adjustment factor for the rapidly changing operating conditions in the initial stage. : ; Secondly, calculate the fat replenishment rate adjustment factor for the later stage of slow-changing operating conditions. : ; Finally, if the temperature-vibration change synchronization deviation is (The difference between the preset synchronicity threshold and the actual synchronicity) then the corrected fat replenishment rate adjustment coefficient is: ; ; Achieve dynamic adaptation between fat replenishment rate and operating condition synchronization requirements; in, This is a coefficient for adjusting the grease replenishment rate under rapidly changing operating conditions in the initial stage. It has no unit and is used to adjust the magnitude of the initial grease replenishment rate. The larger the coefficient, the faster the initial grease replenishment rate, in order to meet the rapidly changing lubrication requirements in the initial stage. This is a rate coefficient, without units, with a preset value range of 1.2-1.5. It is used to amplify the influence of the temperature change rate ratio on the fat replenishment rate adjustment coefficient, ensuring that the initial fat replenishment rate can fully adapt to rapidly changing working conditions. This represents the maximum rate of temperature change during the rapid temperature change conditions described earlier, expressed in °C / min. The fitted curve is The calculation within the interval reflects the fastest rate of temperature change in the previous working condition and is one of the key parameters for calculating the fat replenishment rate adjustment coefficient. This represents the average rate of temperature change during the rapid temperature change conditions described earlier, expressed in °C / min. The calculations within the interval reflect the average temperature change level during the preceding operating conditions, and are consistent with... Together they reflect the severity of the temperature changes in the preceding period; This is a coefficient for adjusting the fat replenishment rate under the later stage of slow-changing operating conditions. It has no unit and is used to determine the fat replenishment rate in the later stage. The size of the coefficient determines the speed of the fat replenishment rate in the later stage to adapt to the later stage of slow-changing operating conditions. This is the attenuation coefficient, which has no unit and is preset to a range of 0.6-0.8. It is used to reduce the adjustment coefficient of the initial fat replenishment rate so that the subsequent fat replenishment rate can adapt to the slow-changing working conditions and avoid excessive fat replenishment in the subsequent stage. This represents the temperature-vibration change synchronicity deviation, which is dimensionless. It is the difference between the preset synchronicity threshold and the actual synchronicity, reflecting the gap between the actual synchronicity and the ideal synchronicity. It serves as the basis for correcting the fat replenishment rate adjustment coefficient. The larger the deviation, the greater the correction to the coefficient. This is the adjusted coefficient for the front-end fat replenishment rate. It has no unit. The adjusted coefficient can better adapt to the synchronization requirements and ensure that the front-end fat replenishment rate matches the synchronization of the working conditions. The adjusted coefficient for the post-compensation rate is dimensionless, allowing the post-compensation rate to dynamically adapt to synchronization requirements and improve the adaptability of the compatibility between the compatibility rate and the operating conditions. The algorithm first targets the rapidly changing operating conditions in the initial stage. Combining the ratio of the maximum to the average temperature change rate with a preset rate coefficient, it calculates the initial fat replenishment rate adjustment coefficient. This rate coefficient and the temperature change rate ratio together determine the adjustment range of the initial fat replenishment rate, ensuring that the fat replenishment rate adapts to the rapidly changing operating conditions. Next, based on the initial fat replenishment rate adjustment coefficient and a preset attenuation coefficient, it calculates the fat replenishment rate adjustment coefficient for the slow-changing operating conditions in the subsequent stage. The attenuation coefficient determines the reduction in the subsequent fat replenishment rate relative to the initial stage, ensuring that the subsequent fat replenishment rate adapts to the slow-changing operating conditions. Finally, when the temperature-vibration change synchronization does not reach the preset range, the algorithm corrects the initial and subsequent fat replenishment rate adjustment coefficients based on the synchronization deviation. By multiplying the original coefficients by a correction factor of (1 + synchronization deviation), the fat replenishment rate adjustment coefficients dynamically adapt to the synchronization requirements, ensuring that the fat replenishment rate matches the synchronization of the operating conditions. This algorithm, through multi-step calculation and correction, achieves precise determination and dynamic optimization of the grease replenishment rate adjustment coefficient, ensuring that the grease replenishment rate can fully adapt to different stages of nonlinear transition conditions and the synchronization requirements of the operating conditions. In the initial stage of rapidly changing operating conditions, the grease replenishment rate adjustment coefficient is rationally calculated to ensure a rapid response to changes in operating conditions and meet rapidly changing lubrication needs. In the later stage of slowly changing operating conditions, the grease replenishment rate adjustment coefficient is reduced using an attenuation coefficient to avoid over-greasing. When synchronization is not up to standard, a synchronization deviation correction coefficient is used to dynamically adapt the grease replenishment rate to synchronization requirements. This multi-dimensional and dynamic grease replenishment rate adjustment strategy ensures that the grease replenishment rate is always highly matched to the characteristics of the operating conditions and synchronization requirements throughout the entire process of nonlinear transition conditions, providing continuous and suitable lubrication supply to the bearings, reducing lubrication defects or waste caused by improper grease replenishment rates, significantly improving the operational reliability and lifespan of bearings under complex transition conditions, and reducing equipment maintenance costs and failure rates.

[0027] In embodiments of the present invention, a working condition self-updating module is also included. The working condition self-updating module is communicatively connected to the control module and the feedback verification module, respectively, and is used to record the full-link data of "working condition identification - grease replenishment adjustment - lubrication effect verification". When the lubrication effect verification result for a certain working condition fails to meet the standard three times in a row, the working condition self-updating module triggers the parameter optimization process of the control module. The control module re-analyzes the correlation characteristics of temperature and vibration signals under the working condition, adjusts the working condition identification threshold and corresponding grease filling parameters, and updates the preset working condition feature template to make the system adapt to the working condition feature drift caused by wear and aging during long-term operation of the bearing, and ensure the long-term effectiveness of the grease filling control strategy.

[0028] In an embodiment of the present invention, when the system is applied to a unit with multiple bearings operating in coordination, the control module is further provided with a load conduction interference elimination unit. The load conduction interference elimination unit is used to analyze the correlation between temperature and vibration signals among multiple bearings: if the vibration signal change of a certain bearing is accompanied by a synchronous change in its own temperature signal, it is determined that the vibration signal change is caused by a change in the bearing's own operating condition; if the vibration signal change of a certain bearing is only accompanied by a change in the temperature signal of other bearings, while its own temperature signal does not change significantly, it is determined that the vibration signal change is a load conduction interference among multiple bearings; the control module shields the vibration signal corresponding to the load conduction interference and generates grease replenishment control commands only based on the temperature-vibration correlation characteristics of the bearing itself, avoiding misjudgment of grease replenishment caused by load conduction.

[0029] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.

Claims

1. A bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback, characterized in that, include: The detection module is used to collect temperature signals, vibration signals, and lubrication status-related signals in real time during the bearing operation, and transmit the temperature signals, vibration signals, and lubrication status-related signals to the control module. After receiving the signal, the control module first performs interference filtering on the signal, then analyzes the correlation characteristics between the temperature signal and the vibration signal to identify the current operating condition of the bearing, and at the same time generates a grease replenishment control command that is suitable for the operating condition by combining the lubrication status correlation signal. The fat replenishment execution module communicates with the control module, receives fat replenishment control commands, and executes corresponding dynamic fat replenishment actions. The feedback verification module is used to collect bearing operation feedback signals after grease replenishment and transmit the operation feedback signals to the control module to verify the lubrication effect, forming a closed-loop control link of "detection-identification-control-verification". The control module distinguishes the characteristic differences between temperature signals and vibration signals under different operating conditions, adapts to the lubrication requirements of bearings under different operating conditions, and eliminates the influence of external environmental interference and multi-bearing load transmission on signal analysis.

2. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 1, characterized in that, The detection module includes a temperature sensing unit, a vibration sensing unit, and a lubrication status sensing unit. The temperature sensing unit and vibration sensing unit are respectively arranged in the raceway area, bearing housing area and lubrication point area of ​​the bearing to collect multi-dimensional temperature and vibration signals of the bearing. The lubrication status sensing unit is used to collect the oil film thickness correlation signal or friction coefficient correlation signal in the bearing lubrication area, as a direct feedback basis for judging the lubrication effect. The detection module is also equipped with a signal preprocessing unit, which is used to filter and reduce noise of the collected raw temperature signal, vibration signal and lubrication status related signal, eliminate signal distortion caused by electromagnetic interference and mechanical resonance in the rolling environment, and ensure the accuracy of the signal transmitted to the control module.

3. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 1, characterized in that, The operating condition identification function of the control module Includes the following steps: The first step is to invoke a preset anti-interference algorithm to filter out pulse interference components in the temperature and vibration signals; The second step is to perform synchronous analysis on the changing trends of the filtered temperature signal and vibration signal to identify synchronous change characteristics, temporal misalignment characteristics, or nonlinear gradient change characteristics between the two. The third step is to determine the bearing operating condition based on the identification results: when the temperature signal and vibration signal have the same trend and the rate of change does not change abruptly, the bearing is determined to be in normal operating condition; when the vibration signal first shows a peak change and the temperature signal changes after a preset time delay, the bearing is determined to be in instantaneous impact condition; when the rate of change of the temperature signal and vibration signal shows a nonlinear difference, the bearing is determined to be in nonlinear transition condition.

4. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 3, characterized in that, When the control module determines that the bearing is under instantaneous impact, it will also classify the intensity of the instantaneous impact based on the peak amplitude and rise rate of the vibration signal. The impact intensity classification includes mild impact, moderate impact, and severe impact, where mild impact corresponds to a vibration peak amplitude increase rate of 100%. The increase in peak vibration corresponding to moderate impact The peak vibration increase corresponding to severe impact ; The control module matches the pre-lubricating film thickness requirement of the bearing at the impact strength level. The higher the impact strength, the greater the pre-lubricating film thickness requirement. At the same time, it calculates the predictive grease replenishment amount to match the impact strength level by combining the size parameters of the bearing raceway. Specifically, the quantitative calculation of impact strength is achieved through the following algorithm formula: ； in, Instantaneous impact intensity This represents the peak value increase of the vibration signal during a momentary impact. This is the reference value for the peak vibration of the bearing under normal operating conditions. according to The calculation results are used to classify the impact level: when It was a mild impact, when At that time, it was a moderate impact, when It was a severe impact.

5. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 4, characterized in that, When the control module detects a predicted signal of an instantaneous impact condition, it generates a graded predictive fat replenishment control command. After receiving the graded predictive fat replenishment control command, the fat replenishment execution module adjusts the action parameters of its controllable execution units according to the impact intensity level. Under mild impact conditions, the control delivery pipeline unit delivers the first amount of grease at a first rate to form a thin pre-lubricating film on the bearing surface; Under moderate impact conditions, the control delivery pipeline unit delivers the second amount of grease at a second rate to form a medium-sized pre-lubricating film on the bearing surface; Under severe impact conditions, the control delivery pipeline unit delivers the third amount of grease at the third rate. The grease delivery module completes the laying of the pre-lubricating film before the vibration signal reaches its peak, so as to resist the squeezing and loss of lubricating medium caused by instantaneous impact. Specifically, the calculation of graded predictive fat supplementation is achieved through the following algorithm formula: ； according to The corresponding impact level matches different Value: Taken for mild impact Take during moderate impact Take during severe impact Then, the first amount of fat supplementation was calculated. Second amount of fat supplementation Third amount of fat supplementation ; in, For predictive fat supplementation, For fat supplementation coefficient, Instantaneous impact intensity Let be the circumference of the bearing raceway. This refers to the width of the bearing raceway.

6. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 5, characterized in that, After the instantaneous impact condition ends, the control module collects the bearing vibration decay rate signal after grease replenishment through the feedback verification module. If the vibration attenuation rate If the preset threshold is set, the pre-lubricating film will remain intact and the lubrication effect will meet the standard, without the need for additional grease replenishment. If the vibration attenuation rate A preset threshold indicates that the pre-lubricating film is damaged or the lubricating medium is lost, and the control module generates a graded repair-type grease replenishment control command. The graded repair-type grease replenishment control command determines the amount of grease replenishment based on the difference between the vibration decay rate and the preset threshold. The larger the difference, the more grease is replenished, thereby controlling the grease replenishment execution module to replenish the lubricating medium and ensuring the lubrication effectiveness of the bearing in subsequent operation. Specifically, the amount of fat replenishment for graded repair is calculated using the following algorithm formula: ； in, To restore fat intake, The repair coefficient is... This represents the difference in vibration decay rates. This is a predictive fat supplementation amount.

7. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 3, characterized in that, When the control module determines that the bearing is in a nonlinear transition condition, it first uses a curve fitting algorithm to fit the change rates of the temperature signal and the vibration signal into nonlinear change curves, and then identifies the "rate inflection point" on the nonlinear change curve. Based on the rate inflection point, the nonlinear transition condition is divided into multiple segmented conditions, including a rapid change condition in the first segment and a slow change condition in the second segment. The control module calculates the corresponding fat replenishment rate adjustment coefficient for each segment of the working condition. The fat replenishment rate adjustment coefficient for the rapidly changing working condition in the first segment is greater than the fat replenishment rate adjustment coefficient for the slowly changing working condition in the second segment, thereby generating a segmented gradient fat replenishment control command. Specifically, the fitting of the nonlinear change curve and the identification of the rate inflection point are achieved through the following algorithm formula: First, the rate of temperature change and vibration change rate By performing quadratic function fitting on each, we obtain: ； ； Secondly, the inflection point of the rate corresponds to the extreme point of the rate of change. The inflection point time can be calculated by taking the derivative and setting the derivative to 0: ； ； Pick As a segment node for nonlinear transient conditions, For the rapidly changing operating conditions in the previous stage, This refers to the later stage of slowly changing operating conditions; in, For the rate of temperature change, The rate of change of vibration, For time, , , The coefficients of the fitted curve for the rate of temperature change are... , , The coefficients are those of the fitted curve of the vibration rate change. The inflection point of the fitted curve of the rate of temperature change. The inflection point of the fitted curve of the vibration rate change is given. The point is the segmented node time for the nonlinear transient condition.

8. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 7, characterized in that, After receiving the segmented gradient fat replenishment control command, the fat replenishment execution module controls the controllable execution unit to gradually increase the amount of fat replenishment at a relatively fast rate when the working conditions change rapidly in the early stage; after reaching the rate inflection point, it switches to gradually increasing the amount of fat replenishment at a slower rate. Meanwhile, the feedback verification module collects the temperature signal and vibration signal changes in real time after grease replenishment. If the synchronicity of the two changes is improved to the preset range, it means that the current grease replenishment parameters are adapted to the segmented working conditions. If the synchronicity of the changes is not improved, the control module will correct the grease replenishment rate adjustment coefficient according to the synchronicity deviation to further optimize the grease replenishment rate in order to adapt to the dynamic lubrication requirements of nonlinear transition working conditions. Specifically, the calculation and correction of the fat replenishment rate adjustment coefficient is achieved through the following algorithm formula: First, calculate the fat replenishment rate adjustment factor for the rapidly changing operating conditions in the initial stage. : ； Secondly, calculate the fat replenishment rate adjustment factor for the later stage of slow-changing operating conditions. : ； Finally, if the temperature-vibration change synchronization deviation is The corrected fat replenishment rate adjustment factor is: ； ； in, This is an adjustment factor for the fat replenishment rate under rapidly changing operating conditions in the initial stage. For rate coefficient, This represents the maximum rate of temperature change during the rapid temperature change conditions described earlier. This represents the average rate of temperature change during the rapid temperature change conditions described earlier. This is the adjustment factor for the fat replenishment rate under the later, slowly changing operating conditions. The attenuation coefficient is... This is due to the synchronization deviation of temperature and vibration changes. This is the adjusted coefficient for the pre-operative fat replenishment rate. This is the adjustment factor for the corrected post-fat replenishment rate.

9. The bearing lubrication intelligent control and grease replenishment system based on temperature-vibration feedback according to claim 1, characterized in that, It also includes a working condition self-updating module, which is communicatively connected to the control module and the feedback verification module, and is used to record the entire chain of data from "working condition identification - grease replenishment adjustment - lubrication effect verification"; When the lubrication effect verification result for a certain working condition fails to meet the standard three times in a row, the working condition self-updating module triggers the parameter optimization process of the control module. The control module re-analyzes the correlation characteristics of temperature and vibration signals under the working condition, adjusts the working condition identification threshold and corresponding grease replenishment parameters, and updates the preset working condition feature template.

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