Signal processing system and method for automatically adjusting gap between guide bearing bushes

Abstract

The invention relates to the field of guide bearing bush control, in particular to a signal processing system and method for guide bearing bush clearance automatic adjustment, and the system comprises a clearance metering module, a model boundary module, a fault learning module, a clearance adjustment module and an oil film lubrication module, the model boundary module is used for establishing a dynamic pressure lubrication model of the guide bearing bush and solving the gap of the guide bearing bush, the fault learning module is used for determining the gap adjustment amount, the gap adjustment module is used for adjusting gap distribution, and the oil film lubrication module is used for adjusting lubricating oil injection. And fault identification and automatic fault-tolerant adjustment are carried out, so that mechanical vibration of the bearing is reduced, operation stability of equipment is guaranteed, abnormal bearing bush gaps are avoided, mechanical efficiency of the bearing is improved, invalid power loss is reduced, service life of the equipment is prolonged, thickness and pressure distribution of a lubricating oil film are improved, and performance of bearing turbine equipment is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of guide bush control, in particular to a signal processing system and method for automatic adjustment of guide bush gap. BACKGROUND

[0002] The guide bush is a kind of sliding bearing component, which is used to support the rotation of the rotating shaft such as the crankshaft and camshaft in a fixed position and bear the load transmitted by the shaft, and is widely used in water turbine, steam turbine, water pump, machine tool and other equipment that need to support the rotating shaft. The working surface of the guide bush is designed with oil groove and oil hole structure, which can form a lubricating oil film between the shaft and the bush, play a guiding role for the rotating shaft, reduce the friction resistance of the bearing, and prevent the rotating shaft from producing excessive radial runout.

[0003] During the operation of the bearing, due to mechanical looseness, installation mismatch and other problems, the gap between the rotating shaft and the guide bush will gradually increase, which will affect the key indicators such as vibration, swing and bush temperature of the bearing during operation, so it is necessary to adjust the gap of the bush in real time. Direct measurement method and plastic gap gauge method are commonly used to measure the gap of the bush, but the measurement results obtained by these methods have certain hysteresis, and need to be measured during shutdown, which is not suitable for automatic adjustment of the gap during the operation of the bearing.

[0004] In addition, many external factors will affect the expansion range of the guide bush gap, making it difficult to achieve pre-adjustment of the gap. In multi-bearing motors, the inconsistent guide bush gap will also cause the rotating shaft to be eccentric and swing, increasing the cost of shutdown maintenance. Although the influence of the gap can be reduced by adjusting the bearing lubrication, oil pressure and oil leakage problems are still likely to occur. SUMMARY

[0005] The purpose of the present application is to provide a signal processing system and method for automatic adjustment of guide bush gap to solve the problems raised in the background.

[0006] In order to solve the above technical problems, the present application provides the following technical scheme: a signal processing system for automatic adjustment of guide bush gap, comprising: a gap measurement module, a model boundary module, a fault learning module, a gap adjustment module and an oil film lubrication module; The gap measurement module is used to embed a liquid level sensor in the internal oil circuit of the bush to monitor the change of oil film thickness under static and dynamic conditions, determine the total amount and distribution state of oil by measuring the pressure at different heights of the oil tank, obtain the bearing speed and load from the DCS or PLC system of the unit, detect the bearing bush by acoustic emission sensor and vibration sensor, measure the bush back pressure by strain gauge, and return the bush temperature by temperature sensor. All the collected data are stored in the database; The model boundary module is configured to adopt the Reynolds equation as a core mathematical model of dynamic pressure lubrication modeling, establish a mathematical model of dynamic pressure lubrication of a guide bush according to oil film pressure distribution, oil film thickness distribution, lubricating oil dynamic viscosity, shaft neck surface linear velocity and rotating speed, and set a pressure boundary condition, with the oil film thickness and injection amount representing the bearing gap, taking the bearing gap as an unknown parameter in the model, and using the recursive least square method or the extended Kalman filter algorithm to solve the guide bush gap in real time; The fault learning module is configured to take the time series of the bearing gap as training data, calculate the complexity features of the sequence at different scales by using the multi-scale permutation entropy algorithm, construct a high-dimensional feature vector, train and classify the extracted high-dimensional feature vector by using a pre-trained classifier, obtain a separable high-dimensional feature set, quantitatively analyze the high-dimensional feature set by using the multi-scale high-dimensional mapping entropy, and perform pattern recognition to output the fault type and determine the gap adjustment amount of the guide bush under different operating modes; The gap adjustment module is configured to convert the gap adjustment amount into a rotating parameter of the motor, compile a command and control a servo motor or a stepper motor to drive a locking nut, adjust the height of a wedge plate or the pre-tightening width of a feeler gauge, synchronously adjust all guide bushes at the same position, determine the gap distribution of different rotating shafts, and make the guide bushes at the same position evenly distributed on the same circumference, concentrically arranged, and with the center positions consistent with the rotating center. The oil film lubrication module is configured to simulate the oil film pressure distribution and the bearing capacity variation according to the liquid level meter parameters and the oil parameters, calculate the injection flow and the oil temperature when the pressure distribution and the bearing capacity variation are uniform according to the current unit load and the oil film thickness, and adjust the variable frequency oil pump to automatically inject and adjust the lubricating oil.

[0007] Further, the gap measurement module includes a liquid level meter unit and a bush detection unit. The liquid level meter unit is configured to use a dense frequency response magnetostrictive liquid level meter or a radar liquid level meter to obtain the oil film thickness variation and perform temperature and pressure compensation. The bush detection unit is configured to detect the bearing bush, monitor the macroscopic abnormal jitter and the microscopic crack state, and adjust the bush back pre-tightening force.

[0008] Further, the model boundary module includes a dynamic pressure lubrication unit, an environment boundary unit and a fast solving unit. The dynamic pressure lubrication unit is configured to use a mathematical model based on the two-dimensional Reynolds equation to describe the dynamic pressure lubrication state of the sliding bearing. The environment boundary unit is configured to take the starting and ending points of the oil film pressure as the environmental pressure, calculate the thrust bush deformation through thermal-mechanical coupling simulation as a correction parameter. The fast solving unit is configured to discretize the Reynolds equation by using the finite difference method or the finite element method, and substitute the bearing pressure, temperature and rotating speed into the equation as known quantities to solve the bearing gap.

[0009] Further, the fault learning module comprises a high-dimensional measurement unit, a feature extraction unit and a pattern recognition unit. The high-dimensional measurement unit is configured to take the bearing gap time series data as an analysis object, quantize the sequence based on high-dimensional mapping entropy, and construct a high-dimensional fault feature set. The feature extraction unit is configured to extract the mean, variance, skewness, kurtosis of the gap in the high-dimensional fault feature set, and the elliptical parameters of the shaft center trajectory. The pattern recognition unit is configured to train a classifier model based on historical operation data and cloud data, classify the operation mode, and output the gap adjustment amount.

[0010] Further, the gap adjustment module comprises an actuator unit and a cooperative adjustment unit. The actuator unit is configured to receive the gap adjustment amount and convert it into motor steps, and drive the locking nut to adjust the gap by using a servo motor or a stepper motor. The cooperative adjustment unit is configured to measure the radial runout of the main shaft at each guide bearing by using an eddy current displacement sensor, measure the concentricity of each bearing seat by using a laser alignment instrument, and adjust the multi-bearing gap.

[0011] Further, the oil film lubrication module comprises a pressure modeling unit and a lubrication injection unit. The pressure modeling unit is configured to obtain the bushing gap, oil cavity pressure, lubricating oil injection flow and oil temperature, and model the oil film distribution. The lubrication injection unit is configured to adjust the oil supply pressure and flow of the bushing in real time, and change the oil film thickness distribution in the bearing gap.

[0012] A signal processing method for automatic adjustment of guide bushing gap, comprising the following steps: Step S1. Embed a closed liquid level metering device in the internal oil circuit of the bushing, obtain the total amount of oil and the change in oil film thickness by measuring the pressure of different liquid levels in the oil tank, obtain the bearing rotating speed and load from the industrial control system, and perform bushing detection on the bearing; Step S2. According to the oil film pressure distribution, oil film thickness distribution, lubricating oil dynamic viscosity, shaft neck surface linear speed and rotating speed, a mathematical model based on the Reynolds equation is used to perform dynamic pressure lubrication modeling to obtain the dynamic pressure lubrication model of the guide bushing, and the model parameters are adjusted according to the environmental pressure and temperature; Step S3. Express the bearing gap in terms of oil film thickness and injection amount, take the bearing gap as an unknown parameter in the model, solve the guide bushing gap, quantize the time series of the gap based on high-dimensional mapping entropy, and construct a high-dimensional fault feature set. Step S4. Train the classifier based on historical operation data and cloud data, use the classifier to perform multi-scale pattern analysis on the fault feature set, identify the operation mode of the current bearing, and output the gap adjustment amount of the guide bush according to the operation mode; Step S5. Drive the motor to adjust the bush gap according to the gap adjustment amount, distribute the gap among all guide bushes in the same bearing part, arrange the guide bushes concentrically and uniformly, and simultaneously adjust the oil supply pressure and flow rate of the bush according to the liquid level meter parameters and oil parameters to simulate the oil film pressure distribution and load capacity variation.

[0013] Further, step S1 includes: Step S11. Use a dense frequency response magnetostrictive liquid level meter or a radar liquid level meter embedded in the bush internal oil circuit to monitor the oil film thickness variation under static and dynamic conditions, obtain the total amount and distribution state of the oil by measuring the pressure at different heights of the oil tank, and obtain the bearing speed and load from the unit DCS or PLC system; Step S12. Set temperature sensors at the oil inlet edge, middle, oil outlet edge and inside of the bush to return the bush temperature, use acoustic emission sensors and vibration sensors for bearing bush detection, use strain gauges to measure the bush back pressure, monitor macroscopic abnormal shaking and microscopic crack state, adjust the bush back pre-tightening force, and store the collected data in the database.

[0014] Further, step S2 includes: Step S21. Use a mathematical model based on two-dimensional Reynolds equation to describe the dynamic pressure lubrication state of the sliding bearing:

[0015] Where p is the oil film pressure distribution function, h is the oil film thickness distribution function, μ is the dynamic viscosity of the lubricating oil, U is the surface linear speed of the shaft journal, x and z are spatial position parameters, and V is the extrusion velocity term; Step S22. Take the starting and ending point pressure of the oil film as the environmental pressure, calculate the thrust bush deformation through thermal-mechanical coupling simulation, use it as a correction parameter to adjust the distribution functions of the oil film pressure and oil film thickness.

[0016] Further, step S3 includes: Step S31. Discretize the Reynolds equation using the finite difference method or the finite element method, substitute the bearing pressure, temperature and speed into the equation as known quantities, and solve the bearing gap using the recursive least squares method or the extended Kalman filter algorithm. Step S32. Take the time series of the bearing gap as training data, calculate the complexity features of the sequence at different scales using the multi-scale permutation entropy algorithm, construct a high-dimensional feature vector, and extract the mean, variance, skewness, kurtosis of the high-dimensional fault feature set and the elliptical parameters of the shaft center trajectory.

[0017] Further, step S4 comprises: Step S41. Training the classifier based on historical operation data and cloud data, training and classifying the extracted high-dimensional feature vectors, and obtaining a high-dimensional feature set with separability; Step S42. Quantitatively analyzing the high-dimensional feature set by using multi-scale high-dimensional mapping entropy and performing pattern recognition, outputting the fault type and determining the gap adjustment amount of the guide bush under different operation modes.

[0018] Further, step S5 comprises: Step S51. Receiving the gap adjustment amount and converting it into motor steps, driving the locking nut by using a servo motor or a stepper motor, and adjusting the height of the wedge plate or the pre-tightening width of the feeler gauge; Step S52. Measuring the radial runout of the main shaft at each guide bearing by using an eddy current displacement sensor, measuring the concentricity of each bearing seat by using a laser alignment instrument, adjusting the multi-bearing gap, and determining the gap distribution of different rotating shafts, so that the bushings of the guide bearings at the same part are uniformly distributed on the same circumference, and each guide bushing is concentrically arranged and the center position is consistent with the rotation center; Step S53. According to the parameters of the liquid level meter and the oil, the bushing gap, the oil cavity pressure, the lubricating oil injection flow and the oil temperature are obtained, the oil film distribution is modeled, the oil film pressure distribution and the bearing capacity change are simulated, the injection flow and the oil temperature when the pressure distribution and the bearing capacity change are uniform are calculated according to the current unit load and the oil film thickness, and the oil film thickness distribution in the bearing gap is changed.

[0019] Compared with the prior art, the beneficial effects achieved by the present application are: By setting the closed liquid level metering device in the guide bush gap, the distribution of the oil film pressure, temperature, thickness and thrust pad deformation is calculated, the mathematical model of the guide bush dynamic pressure lubrication is established, the thrust bearing gap is solved in real time, the real-time prediction of the guide bush gap can be realized, and the fault identification and automatic fault tolerance adjustment can be realized, thereby reducing the bearing mechanical vibration and ensuring the equipment operation stability.

[0020] The present application can extract features based on high-dimensional mapping entropy algorithm for real-time bearing gap, construct a good separability gap fault feature set, quantitatively analyze the fault feature set by using multi-scale high-dimensional mapping entropy and perform pattern recognition, complete the automatic adjustment of the gap, avoid the problems of main shaft bending and poor gear meshing caused by abnormal bushing gap, improve the mechanical efficiency of the bearing, reduce the invalid power loss, and prolong the service life of the equipment.

[0021] The application can make the guide bearings concentrically arranged and the center positions consistent with the rotation center, evaluate the influence of different oil cavity parameters on the gap oil film pressure, model the oil film instantaneous pressure field, adjust the lubricating oil injection amount, make the stable oil film formed in the gap, reduce the direct contact friction of metal, improve the thickness and pressure distribution of the lubricating oil film, ensure the maximum lubrication effect, and improve the performance of the bearing turbine equipment. BRIEF DESCRIPTION OF DRAWINGS

[0022] The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of the specification, illustrate embodiments of the application and are used to explain the application, and do not constitute a limitation on the application. In the drawings: Figure 1 is a structural schematic diagram of a signal processing system for automatic adjustment of guide bush gap of the application; Figure 2 is a step schematic diagram of a signal processing method for automatic adjustment of guide bush gap of the application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0024] As shown in the structure of Figure 1 The application provides a technical solution: a signal processing system for automatic adjustment of guide bush gap, specifically comprising: a gap metering module, a model boundary module, a fault learning module, a gap adjustment module and an oil film lubrication module. The gap metering module is used to embed a liquid level sensor in the internal oil way of the bush, monitor the oil film thickness change under static and dynamic conditions, determine the total amount and distribution state of the oil by measuring the pressure at different heights of the oil tank, obtain the bearing rotation speed and load from the DCS or PLC system of the unit, detect the bearing bushing by the acoustic emission sensor and the vibration sensor, measure the bush back pressure by the strain gauge, and return the bush temperature by the temperature sensor, and store all the collected data into the database. The gap metering module comprises a liquid level meter unit and a bushing detection unit. The liquid level meter unit is used to obtain the oil film thickness change by using a dense frequency response magnetostrictive liquid level meter or a radar liquid level meter, and perform temperature and pressure compensation. The bushing detection unit is used to detect the bearing bushing, monitor the macroscopic abnormal shaking and the microscopic crack state, and adjust the bush back pre-tightening force.

[0025] The model boundary module is configured to adopt the Reynolds equation as a core mathematical model of dynamic pressure lubrication modeling, establish a mathematical model of dynamic pressure lubrication of a guide bush according to an oil film pressure distribution, an oil film thickness distribution, a dynamic viscosity of lubricating oil, a surface linear velocity of a shaft journal, and a rotating speed, and set a pressure boundary condition, take the oil film thickness and an injection amount as a bearing gap, take the bearing gap as an unknown parameter in the model, and adopt a recursive least square method or an extended Kalman filtering algorithm to solve the guide bush gap in real time; The model boundary module comprises a dynamic pressure lubrication unit, an environment boundary unit, and a fast solving unit. The dynamic pressure lubrication unit is configured to adopt a mathematical model based on a two-dimensional Reynolds equation to describe a dynamic pressure lubrication state of a sliding bearing. The environment boundary unit is configured to take a starting and ending point pressure of an oil film as an environmental pressure, calculate a thrust pad deformation through a thermal-mechanical coupling simulation, and take the thrust pad deformation as a correction parameter. The fast solving unit is configured to discretize the Reynolds equation by using a finite difference method or a finite element method, take a bearing pressure, a temperature, and a rotating speed as known quantities, and substitute the known quantities into the equation to solve the bearing gap.

[0026] The fault learning module is configured to take a time sequence of the bearing gap as training data, calculate complexity features of the sequence at different scales by using a multi-scale permutation entropy algorithm, construct a high-dimensional feature vector, train and classify the extracted high-dimensional feature vector by using a pre-trained classifier to obtain a separable high-dimensional feature set, quantitatively analyze the high-dimensional feature set by using a multi-scale high-dimensional mapping entropy, and perform pattern recognition to output a fault type and determine a gap adjustment amount of the guide bush under different operating modes. The fault learning module comprises a high-dimensional measurement unit, a feature extraction unit, and a pattern recognition unit. The high-dimensional measurement unit is configured to take the time sequence of the bearing gap as an analysis object, quantize the sequence based on a high-dimensional mapping entropy, and construct a high-dimensional fault feature set. The feature extraction unit is configured to extract a mean value, a variance, a skewness, a kurtosis of the gap, and an elliptical parameter of an axis trajectory in the high-dimensional fault feature set. The pattern recognition unit is configured to train a classifier model based on historical operating data and cloud data, classify operating modes, and output a gap adjustment amount.

[0027] The gap adjustment module is configured to convert the gap adjustment amount into a rotating parameter of the motor, compile a command, and control a servo motor or a stepping motor to drive a locking nut, adjust a height of a wedge plate or a pre-tightening width of a plug gauge, synchronously adjust all guide bushes at the same part, determine a gap distribution of different rotating shafts, and make the guide bushes at the same part evenly distributed on the same circumference and concentrically arranged with the center positions consistent with the rotating center. The gap adjustment module comprises an actuator unit and a cooperative adjustment unit. The executor unit is used for receiving the gap adjustment amount and converting it into motor steps, and adopting a servo motor or a stepping motor to drive a locking nut to adjust the gap; The cooperative adjustment unit is used for measuring the radial runout of the main shaft at each guide bearing through an eddy current displacement sensor, measuring the concentricity of each bearing seat through a laser alignment instrument, and adjusting the multi-bearing gap.

[0028] The oil film lubrication module is used for simulating the oil film pressure distribution and the bearing capacity variation according to the liquid level meter parameters and the oil parameters, calculating the injection flow and the oil temperature when the pressure distribution and the bearing capacity variation are uniform according to the current unit load and the oil film thickness, and adjusting the variable frequency oil pump to automatically inject and adjust the lubricating oil.

[0029] The oil film lubrication module comprises a pressure modeling unit and a lubrication injection unit. The pressure modeling unit is used for obtaining the bearing bush gap, the oil cavity pressure, the lubricating oil injection flow and the oil temperature, and modeling the oil film distribution. The lubrication injection unit is used for adjusting the oil supply pressure and flow of the bearing bush in real time, and changing the oil film thickness distribution in the bearing gap.

[0030] As shown in Figure 2 A signal processing method for automatic adjustment of guide bearing bush gap, comprising the following steps: Step S1. Embed the closed liquid level meter device in the internal oil circuit of the bearing bush, obtain the total amount of oil and the change of oil film thickness by measuring the pressure of the oil tank at different liquid levels, obtain the bearing speed and load from the industrial control system, and perform bearing bush detection; Step S1 comprises: Step S11. Embed a dense frequency response magnetostrictive liquid level meter or a radar liquid level meter in the internal oil circuit of the bearing bush, monitor the change of oil film thickness under static and dynamic conditions, obtain the total amount of oil and the distribution state by measuring the pressure of the oil tank at different heights, and obtain the bearing speed and load from the unit DCS or PLC system; Step S12. Set temperature sensors at the oil inlet edge, the middle part, the oil outlet edge and the bush body inside the guide bearing bush, return the bush temperature, perform bearing bush detection through acoustic emission sensors and vibration sensors, measure the bush back pressure through strain gauges, monitor the macroscopic abnormal shaking and the microscopic crack state, adjust the bush back pre-tightening force, and store the collected data into a database.

[0031] Step S2. According to the oil film pressure distribution, the oil film thickness distribution, the lubricating oil dynamic viscosity, the shaft neck surface linear speed and the rotation speed, adopt a mathematical model based on the Reynolds equation to perform dynamic pressure lubrication modeling, obtain the dynamic pressure lubrication model of the guide bearing bush, and adjust the model parameters according to the environmental pressure and temperature; Step S2 comprises: Step S21. A mathematical model based on two-dimensional Reynolds equation is used to describe the hydrodynamic lubrication state of the sliding bearing:

[0032] where p is the oil film pressure distribution function, h is the oil film thickness distribution function, μ is the dynamic viscosity of the lubricating oil, U is the surface linear velocity of the journal, x and z are spatial position parameters, and V is the extrusion velocity term; Step S22. The starting and ending point pressures of the oil film are taken as the environmental pressure, and the thrust pad deformation is calculated through thermal-mechanical coupling simulation, which is used as a correction parameter to adjust the distribution functions of the oil film pressure and the oil film thickness.

[0033] Step S3. The bearing gap is expressed in terms of the oil film thickness and the injection amount, and the bearing gap is taken as an unknown parameter in the model to solve the journal bearing gap. The time series of the gap is quantified based on high-dimensional mapping entropy, and a high-dimensional fault feature set is constructed. Step S3 includes: Step S31. The Reynolds equation is discretized using the finite difference method or the finite element method, and the bearing pressure, temperature, and speed are substituted into the equation as known quantities. The recursive least squares method or the extended Kalman filter algorithm is used to solve the bearing gap. Step S32. The time series of the bearing gap is taken as training data, and the multiscale permutation entropy algorithm is used to calculate the complexity features of the sequence at different scales. A high-dimensional feature vector is constructed, and the mean, variance, skewness, kurtosis of the high-dimensional fault feature set, and the elliptical parameters of the shaft trajectory are extracted.

[0034] Step S4. The classifier is trained based on historical operation data and cloud data, and the classifier is used for multiscale pattern analysis of the fault feature set to identify the current bearing operation mode. The gap adjustment amount of the journal bearing is output according to the operation mode. Step S4 includes: Step S41. The classifier is trained based on historical operation data and cloud data, and the extracted high-dimensional feature vector is trained and classified to obtain a separable high-dimensional feature set. Step S42. The high-dimensional feature set is quantitatively analyzed and pattern recognized using multiscale high-dimensional mapping entropy, and the fault type is output and the gap adjustment amount of the journal bearing under different operation modes is determined.

[0035] Step S5. The gap adjustment amount is used to drive the motor to adjust the bearing gap, and the gap is distributed among all journal bearings at the same bearing site to make the journal bearings concentric and uniformly distributed. At the same time, according to the liquid level meter parameters and oil parameters, the oil film pressure distribution and the load capacity change are simulated, and the oil supply pressure and flow of the bearing are adjusted in real time.

[0036] Step S5 includes: Step S51. Receiving gap adjustment amount and converting into motor step number, using servo motor or stepper motor to drive locking nut, adjusting height of wedge plate or pre-tightening width of feeler gauge; Step S52. Measuring radial runout of main shaft at each guide bearing by eddy current displacement sensor, measuring concentricity of each bearing seat by laser alignment instrument, adjusting multi-bearing gap, determining gap distribution of different rotating shafts, making bearing bush of same part guide bearing evenly distributed on same circumference, and concentrically arranging each guide bearing bush with center position consistent with rotating center; Step S53. According to liquid level meter parameter and oil parameter, obtaining bearing bush gap, oil cavity pressure, lubricating oil injection flow and oil temperature, modeling oil film distribution, simulating oil film pressure distribution and bearing capacity change, calculating injection flow and oil temperature when pressure distribution and bearing capacity change are uniform according to current unit load and oil film thickness, changing oil film thickness distribution in bearing gap.

[0037] Embodiment: Ultrasonic liquid level meter is arranged in bearing, gap volume is determined according to injected oil amount and liquid level height, and observation value is adjusted through temperature data of temperature sensor, oil film pressure and oil film thickness distribution are simulated according to pressure of different height liquid level, actual gap is solved through two-dimensional Reynolds equation, and gap change sequence with time is outputted, gap space needing to be adjusted is determined after sequence is subjected to pattern recognition, and motor is automatically driven to adjust gap and oil amount.

[0038] It should be noted that the relational terms herein such as first and second and the like are used only to differentiate one entity or operation from another, and do not necessarily require or imply that any such actual relationship or order exists between or among the entities or operations. Also, the terms "comprising", "including", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0039] Finally, it should be noted that: the above only describes the preferred embodiments of the present application, and is not used to limit the present application, although the present application is described in detail with reference to the foregoing embodiments, for those skilled in the art, the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A signal processing method for automatic adjustment of the guide bushing clearance, characterized by, The method comprises the following steps: Step S1. Embed the closed liquid level metering device into the bearing bush internal oil circuit, obtain the total amount of oil and the change of oil film thickness by measuring the pressure of different liquid levels of the oil tank, obtain the bearing rotating speed and load from the industrial control system, and detect the bearing by bearing holding; Step S2. According to the oil film pressure distribution, the oil film thickness distribution, the dynamic viscosity of lubricating oil, the surface linear speed of the shaft neck and the rotating speed, a mathematical model based on the Reynolds equation is used for dynamic pressure lubrication modeling to obtain the dynamic pressure lubrication model of the guide bush, and the model parameters are adjusted according to the environmental pressure and temperature; Step S3. The bearing gap is expressed by the oil film thickness and the injection amount, the bearing gap is taken as an unknown parameter in the model, the guide bush gap is solved, the time sequence of the gap is quantified based on high-dimensional mapping entropy, and a high-dimensional fault feature set is constructed; Step S4. The classifier is trained based on historical operation data and cloud data, multi-scale pattern analysis is performed on the fault feature set by using the classifier, the running mode of the current bearing is identified, and the gap adjustment amount of the guide bush is output according to the running mode; Step S5. The motor is driven according to the gap adjustment amount to adjust the bearing gap, the gap is distributed among all guide bushes in the same bearing part, the guide bushes are arranged concentrically and uniformly distributed, and the oil film pressure distribution and the change of bearing capacity are simulated according to the liquid level meter parameters and the oil parameters, so as to adjust the oil supply pressure and flow of the bearing in real time.

2. A signal processing method for automatic adjustment of the guide bushing clearance according to claim 1, characterized in that: Step S1 comprises: Step S11. A dense frequency response magnetostrictive liquid level meter or a radar liquid level meter is used to embed the internal oil circuit of the bearing bush, to monitor the change of oil film thickness under static and dynamic conditions, to obtain the total amount of oil and the distribution state by measuring the pressure of different heights of the oil tank, and to obtain the bearing rotating speed and load from the unit DCS or PLC system; Step S12. Temperature sensors are arranged at the oil inlet edge, the middle part, the oil outlet edge and the bush body inside the guide bush, the bush temperature is returned, the bearing holding is detected by acoustic emission sensors and vibration sensors, the bush back pressure is measured by strain gauges, the macroscopic abnormal shaking and the microscopic crack state are monitored, the bush back pre-tightening force is adjusted, and the collected data are stored in the database.

3. A signal processing method for automatic adjustment of the guide bushing clearance according to claim 2, characterized in that: Step S2 comprises: Step S21. A mathematical model based on the two-dimensional Reynolds equation is used to describe the dynamic pressure lubrication state of the sliding bearing: where p is the oil film pressure distribution function, h is the oil film thickness distribution function, μ is the dynamic viscosity of the lubricating oil, U is the surface linear velocity of the journal, x and z are spatial position parameters, and V is the squeeze velocity term; Step S22. The starting and ending point pressures of the oil film are taken as the environmental pressure, the thrust bush deformation is calculated through thermal-mechanical coupling simulation, which is used as a correction parameter to adjust the distribution functions of the oil film pressure and the oil film thickness.

4. A signal processing method for automatic adjustment of the guide bushing clearance according to claim 3, characterized in that: Step S3 comprises: Step S31. The finite difference method or the finite element method is used to discretize the Reynolds equation, the bearing pressure, temperature and rotating speed are taken as known quantities and substituted into the equation, and the recursive least square method or the extended Kalman filter algorithm is used to solve the bearing gap; Step S32. The time sequence of the bearing gap is taken as the training data, the multi-scale permutation entropy algorithm is used to calculate the complexity characteristics of the sequence at different scales, a high-dimensional feature vector is constructed, and the mean, variance, skewness, kurtosis of the gap in the high-dimensional fault feature set and the elliptical parameters of the shaft center trajectory are extracted; Step S4 comprises: Step S41. The classifier is trained based on historical operation data and cloud data, the extracted high-dimensional feature vector is trained and classified, and a separable high-dimensional feature set is obtained; Step S42. Quantitatively analyze the high-dimensional feature set by using the multi-scale high-dimensional mapping entropy and perform pattern recognition, output the fault type and determine the gap adjustment amount of the guide bush under different operating modes.

5. A signal processing method for automatic adjustment of the guide bushing clearance according to claim 4, characterized in that: Step S5 includes: Step S51. Receive the gap adjustment amount and convert it into motor steps, drive the locking nut by using a servo motor or a stepper motor, and adjust the height of the wedge plate or the pre-tightening width of the feeler gauge; Step S52. Measure the radial runout of the main shaft at each guide bearing by using an eddy current displacement sensor, measure the concentricity of each bearing seat by using a laser alignment instrument, perform multi-bearing gap adjustment, determine the gap distribution of different rotating shafts, and make the bushings of the guide bearings at the same part uniformly distributed on the same circumference, and each guide bushing is concentrically arranged and the center position is consistent with the rotation center; Step S53. According to the parameters of the liquid level meter and the oil, obtain the bushing gap, oil cavity pressure, lubricating oil injection flow and oil temperature, model the oil film distribution, simulate the oil film pressure distribution and load capacity change, calculate the injection flow and oil temperature when the pressure distribution and load capacity change are uniform according to the current unit load and oil film thickness, and change the oil film thickness distribution in the bearing gap.

6. A signal processing system for automatic adjustment of the guide bushing clearance, characterized by The system comprises the following modules: a gap metering module, a model boundary module, a fault learning module, a gap adjustment module and an oil film lubrication module; The gap metering module is used to embed a liquid level sensor in the oil channel inside the bushing to monitor the oil film thickness change under static and dynamic conditions, determine the total amount and distribution state of the oil by measuring the pressure at different heights of the oil tank, obtain the bearing speed and load from the unit DCS or PLC system, detect the bearing bush by using acoustic emission sensors and vibration sensors, measure the bush back pressure by using strain gauges, and return the bush temperature by using temperature sensors, and store all collected data into a database; The model boundary module is used to use the Reynolds equation as the core mathematical model of dynamic pressure lubrication modeling, establish a mathematical model of guide bush dynamic pressure lubrication according to the oil film pressure distribution, oil film thickness distribution, lubricating oil dynamic viscosity, shaft neck surface linear speed and rotating speed, set the pressure boundary condition, express the bearing gap by using the oil film thickness and injection amount, take the bearing gap as an unknown parameter in the model, and solve the guide bush gap in real time by using the recursive least square method or the extended Kalman filter algorithm; The fault learning module is used to take the time series of the bearing gap as training data, calculate the complexity characteristics of the sequence at different scales by using the multi-scale permutation entropy algorithm, construct a high-dimensional feature vector, train and classify the extracted high-dimensional feature vector by using a pre-trained classifier, obtain a separable high-dimensional feature set, quantitatively analyze the high-dimensional feature set by using the multi-scale high-dimensional mapping entropy and perform pattern recognition, output the fault type and determine the gap adjustment amount of the guide bush under different operating modes; The fault learning module is used to take the time series of the bearing gap as training data, calculate the complexity characteristics of the sequence at different scales by using the multi-scale permutation entropy algorithm, construct a high-dimensional feature vector, train and classify the extracted high-dimensional feature vector by using a pre-trained classifier, obtain a separable high-dimensional feature set, quantitatively analyze the high-dimensional feature set by using the multi-scale high-dimensional mapping entropy and perform pattern recognition, output the fault type and determine the gap adjustment amount of the guide bush under different operating modes; The gap adjustment module is used for converting the gap adjustment amount into a rotation parameter of the motor, compiling a command, and controlling a servo motor or a step motor to drive a locking nut, so as to adjust the height of a wedge plate or the pre-tightening width of a feeler gauge, synchronize the adjustment of all guide bushings at the same position, determine the gap distribution of different rotation shafts, and make the bushings of the guide bearing at the same position uniformly distributed on the same circumference and concentrically arranged with the center position consistent with the rotation center. The oil film lubrication module is used for simulating the oil film pressure distribution and the bearing capacity variation according to the liquid level meter parameter and the oil parameter, calculating the injection flow and the oil temperature when the pressure distribution and the bearing capacity variation are uniform according to the current unit load and the oil film thickness, and adjusting the variable frequency oil pump to automatically inject and adjust the lubricating oil.

7. A signal processing system for automatic adjustment of the guide bushing clearance according to claim 6, characterized in that: The gap measurement module comprises a liquid level meter unit and a bushing detection unit. The liquid level meter unit is used for acquiring the oil film thickness variation by using a dense frequency response magnetostrictive liquid level meter or a radar liquid level meter, and performing temperature and pressure compensation. The bushing detection unit is used for bearing bushing detection, monitoring macroscopic abnormal jitter and microscopic crack state, and adjusting the bushing back pre-tightening force.

8. A signal processing system for automatic adjustment of the guide bushing clearance according to claim 7, characterized in that: The model boundary module comprises a dynamic pressure lubrication unit, an environment boundary unit and a fast solving unit. The dynamic pressure lubrication unit is used for describing the dynamic pressure lubrication state of the sliding bearing by using a mathematical model based on the two-dimensional Reynolds equation. The environment boundary unit is used for taking the oil film starting and ending point pressure as the environmental pressure, and taking the thrust pad deformation calculated by thermal-mechanical coupling simulation as a correction parameter. The fast solving unit is used for discretizing the Reynolds equation by using the finite difference method or the finite element method, taking the bearing pressure, temperature and rotation speed as known quantities, and substituting them into the equation to solve the bearing gap.

9. A signal processing system for automatic adjustment of the guide bushing clearance according to claim 8, characterized in that: The fault learning module comprises a high-dimensional measurement unit, a feature extraction unit and a pattern recognition unit. The high-dimensional measurement unit is used for taking the bearing gap time series data as an analysis object, quantizing the sequence based on high-dimensional mapping entropy, and constructing a high-dimensional fault feature set. The feature extraction unit is used for extracting the mean, variance, skewness, kurtosis of the gap in the high-dimensional fault feature set and the elliptical parameters of the shaft center trajectory. The pattern recognition unit is used for training a classifier model based on historical operation data and cloud data, classifying the operation mode, and outputting the gap adjustment.

10. A signal processing system for automatic adjustment of the guide bushing clearance according to claim 9, characterized in that: The gap adjustment module comprises an actuator unit and a cooperative adjustment unit. The actuator unit is used for receiving the gap adjustment amount and converting it into motor steps, and driving the locking nut by using a servo motor or a step motor to adjust the gap. The cooperative adjustment unit is used for measuring the radial runout of the main shaft at each guide bearing by using an eddy current displacement sensor, measuring the concentricity of each bearing seat by using a laser alignment instrument, and adjusting the gap of multiple bearings. The oil film lubrication module comprises a pressure modeling unit and a lubrication injection unit. The pressure modeling unit is used for acquiring the bushing gap, oil cavity pressure, lubricating oil injection flow and oil temperature, and modeling the oil film distribution. The lubrication injection unit is used for adjusting the oil supply pressure and flow of the bushing in real time, and changing the oil film thickness distribution in the bearing gap.

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