Gas turbine test bed thrust bearing monitoring system, method and medium

Abstract

The application discloses a monitoring system, method and medium for a gas turbine test bed thrust bearing, which comprises a lubricating oil supply path, a lubricating oil return path, a return oil tank, a thrust bearing, a bearing temperature measuring device, an axial thrust load ring and a control module; wherein the lubricating oil supply path comprises an oil supply temperature measuring device; the lubricating oil return path comprises a first metal chip measuring device and a return oil temperature measuring device; the return oil tank comprises a second metal chip measuring device; the bearing temperature measuring device is arranged at any interface close to the thrust bearing, the axial thrust load ring is used for measuring the axial thrust on the bearing thrust surface; and the control module is used for combining the received various measurement data to judge the current working state of the thrust bearing and to perform protection control according to the working state. The system can systematically monitor the real working state of the thrust bearing, and improve the comprehensiveness and accuracy of the thrust bearing monitoring result.

Description

Technical Field

[0001] The present application relates to the technical field of gas turbine monitoring, and in particular to a monitoring system, method, and medium for a thrust bearing of a gas turbine test bench. Background Art

[0002] Gas turbine thrust bearings are critical components of gas turbines. During testing of compressor and turbine components, thrust bearings support the rotor. These bearings are subject to high speeds and heavy loads, placing high demands on bearing performance. Burning and wear are the primary failure modes of thrust bearings. Bearing failure during testing can compromise the safety of test equipment. Therefore, monitoring and early warning of bearing failures are crucial.

[0003] In the prior art, during testing of gas turbine components such as the compressor and turbine, monitoring methods are relatively limited, typically only monitoring the temperature of the thrust bearing. Furthermore, due to current technological limitations, it is impossible to directly measure the temperature of the thrust bearing's moving parts. Consequently, these monitoring methods fail to fully and accurately determine the operating status of the thrust bearing. Summary of the Invention

[0004] The purpose of this application is to solve one of the above technical problems at least to a certain extent.

[0005] Therefore, the first objective of this application is to provide a monitoring system for a gas turbine test bench thrust bearing. The system can fully monitor the working status of the thrust bearing to obtain the true working status of the thrust bearing, avoiding the monitoring failure caused by a single bearing temperature monitoring method.

[0006] A second objective of the present application is to provide a method for monitoring a thrust bearing of a gas turbine test bench.

[0007] A third object of the present application is to provide a non-transitory computer-readable storage medium.

[0008] To achieve the above-mentioned purpose, the first aspect of the present application proposes a monitoring system for a thrust bearing of a gas turbine test bench, comprising: a lubricating oil supply line, a lubricating oil return line, an oil return tank, a thrust bearing, a bearing temperature measuring device, an axial thrust force measuring ring, and a control module; wherein,

[0009] The lubricating oil supply circuit includes an oil supply temperature measuring device, and the oil supply temperature measuring device is used to measure the lubricating oil supply temperature;

[0010] The lubricating oil return line includes a first metal debris measuring device and a return oil temperature measuring device, wherein the first metal debris measuring device is used to measure the mass change of metal debris in the bearing return oil line, and the return oil temperature measuring device is used to measure the lubricating oil return temperature;

[0011] The oil return tank includes a second metal debris measuring device, which is used to measure the mass change of metal debris in the bearing oil return tank;

[0012] The bearing temperature measuring device is arranged at any interface adjacent to the thrust bearing, and is used to measure the bearing temperature. The axial thrust force measuring ring is used to measure the axial thrust on the thrust surface of the bearing.

[0013] The control module is respectively communicated with each measuring device. The control module is used to combine the received multiple temperature measurement values, metal debris detection values ​​and the axial thrust, judge the current working state of the thrust bearing based on multi-parameter correlation analysis, and perform protection control according to the working state.

[0014] In addition, the monitoring system for the thrust bearing of the gas turbine test bench of the present application also has the following additional technical features:

[0015] Optionally, the system further includes: a rotor and a stator, the axial thrust force measuring ring is an elastic ring, and the axial thrust force measuring ring is arranged on the rotor or the stator.

[0016] Optionally, the bearing temperature measuring device is arranged on the bearing thrust surface, or is arranged near the interface between the rotor and the thrust bearing, or is arranged near the interface between the stator and the thrust bearing.

[0017] Optionally, the control module is specifically configured to calculate an average value of mass changes of metal debris in the bearing oil return pipeline and mass changes of metal debris in the bearing oil return tank, and use the average value as the metal debris detection value.

[0018] To achieve the above-mentioned object, the second aspect of the present application provides a method for monitoring a thrust bearing of a gas turbine test bench, which is applied to the monitoring system for the thrust bearing of the gas turbine test bench of the first aspect. The method comprises:

[0019] Acquiring multiple parameters collected in real time by a monitoring system of the thrust bearing of the gas turbine test bench, wherein the multiple parameters include lubricating oil supply temperature, lubricating oil return temperature, bearing temperature, metal debris detection value, and axial thrust;

[0020] Determining multiple correlation thresholds for the multiple parameters through the trained multi-parameter coupling relationship model;

[0021] performing an integration operation on the multiple parameters continuously collected within a preset time period, comparing each integral value used to characterize parameter changes with the associated threshold value, determining whether the thrust bearing meets any fault mode in a fault library, and, if so, performing protection control on the thrust bearing based on fault information of any fault mode obtained from the fault library;

[0022] In the case of not meeting each fault mode in the fault library, a risk index is calculated based on the dynamic weights of temperature parameters and mechanical parameters and the associated threshold, and protection control of the thrust bearing is performed according to the risk index.

[0023] Optionally, the multiple correlation thresholds include timing correlation thresholds and data calculation thresholds, and the judgment of whether the thrust bearing meets any fault mode in the fault library includes: when the lubricating oil supply temperature and the lubricating oil return temperature remain stable, and the increasing rates of the bearing temperature, the metal debris detection value and the axial thrust are respectively greater than the corresponding timing correlation thresholds, judging that the thrust bearing is in the first fault mode; when the lubricating oil supply temperature, the bearing temperature and the axial thrust remain stable, and the increasing rates of the lubricating oil return temperature and the metal debris detection value are respectively greater than the corresponding timing correlation thresholds, judging that the thrust bearing is in the second fault mode; when the lubricating oil return temperature, the metal debris detection value and the axial thrust remain stable, and the increasing rate of the lubricating oil supply temperature is greater than the corresponding timing correlation threshold, and the temperature difference between the lubricating oil supply temperature and the bearing temperature is less than the corresponding correlation threshold, judging that the thrust bearing is in the third fault mode.

[0024] Optionally, the determining whether the thrust bearing is in any fault mode in the fault library further includes: when the lubricating oil supply temperature, the bearing temperature, the axial thrust and the metal debris detection value remain stable, and the rate of increase of the lubricating oil return temperature is greater than the corresponding time-series correlation threshold, determining that the thrust bearing is in the fourth fault mode; when the lubricating oil supply temperature, the lubricating oil return temperature, the axial thrust and the metal debris detection value remain stable, and the rate of increase of the bearing temperature is greater than the corresponding time-series correlation threshold, determining that the thrust bearing is in the fifth fault mode. Formula; when the lubricating oil supply temperature, the axial thrust and the metal debris detection value remain stable, and the increasing rate of the bearing temperature is greater than the corresponding time-series correlation threshold, and the decreasing amplitude of the lubricating oil return temperature is greater than the corresponding time-series correlation threshold, it is determined that the thrust bearing is in the sixth fault mode; when the lubricating oil supply temperature and the lubricating oil return temperature remain stable, and the increasing rate of the bearing temperature, the increasing amplitude of the axial thrust and the increasing rate of the metal debris detection value are respectively greater than the corresponding time-series correlation thresholds, it is determined that the thrust bearing is in the seventh fault mode.

[0025] Optionally, the calculation of the risk index includes: calculating the risk coefficient of each parameter according to the measured value of each parameter and the data operation threshold; dynamically allocating weight coefficients to the temperature parameters and the mechanical parameters according to the type of abnormal parameters; and calculating the risk index by combining the risk coefficient of each parameter and the measured value and the weight coefficient of each type of parameter.

[0026] Optionally, the fault information includes the fault cause and the fault type, and the protection control of the thrust bearing includes: determining the fault severity and protection measures based on the fault cause and the fault type; determining the early warning method based on the fault severity, and executing the protection measures on the thrust bearing.

[0027] To achieve the above-mentioned objectives, the third aspect of the present application proposes a non-temporary computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the monitoring method of the thrust bearing of the gas turbine test bench as described in any one of the above-mentioned second aspects.

[0028] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0029] This application utilizes a combined monitoring method for multiple parameters, including oil supply temperature, oil return temperature, bearing temperature, axial thrust, and metal debris, to comprehensively and systematically monitor the true operating status of the thrust bearing. Combined with the thrust bearing fault judgment logic, it can accurately determine whether the thrust bearing is currently faulty, and determine the specific fault type and cause of the thrust bearing, thereby facilitating timely protection and control in the early stages of the bearing failure. Furthermore, the placement of the axial thrust and bearing temperature measurement points in this application is not limited to being fixed in one location; they can be placed on the stator or the rotor, and can be adjusted according to on-site needs, enriching the monitoring methods for thrust bearings and improving the applicability of thrust bearing monitoring. The axial thrust and bearing temperature measurements obtained in this application are closer to the actual values, improving the authenticity of the monitoring data. Furthermore, the use of a multi-parameter monitoring method avoids false alarms for thrust bearing faults caused by single temperature monitoring, and can implement corresponding protection measures for different fault types. As a result, this application improves the comprehensiveness and accuracy of thrust bearing monitoring results, enabling timely and accurate protection and control when thrust bearing faults occur, which is conducive to ensuring the safe and stable operation of thrust bearings.

[0030] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0032] Figure 1 A schematic structural diagram of a monitoring system for a thrust bearing of a gas turbine test bench proposed in an embodiment of the present application;

[0033] Figure 2 This is a flow chart of a method for monitoring a thrust bearing of a gas turbine test bench proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0035] It should be noted that in the relevant embodiments, when monitoring the thrust bearing of a gas turbine test bench, only the thrust bearing temperature is typically monitored. However, the thrust bearing temperature depends on the oil supply temperature and its own heat generation. This heat generation is closely related to the thrust bearing's rotational speed, load, and other factors. Therefore, monitoring only the thrust bearing temperature does not fully and accurately reflect the thrust bearing's operating status. Furthermore, due to current technological limitations, it is impossible to directly measure the temperature of the thrust bearing's moving components. The actual thrust bearing temperature can only be represented by measuring the temperature of the stator, which is closest to the thrust bearing's working surface. When the thrust bearing's oil supply temperature is low, the thrust bearing may be severely damaged but still have not reached the alarm temperature. By the time the system alarm sounds and the test is stopped, the test equipment may already be severely damaged.

[0036] To this end, the present application proposes a monitoring system and method for the thrust bearing of a gas turbine test bench, which can systematically monitor the working status of the thrust bearing to obtain a comprehensive and true working status of the thrust bearing, thereby avoiding the failure of a single bearing temperature monitoring method.

[0037] The following describes a monitoring system and method for a thrust bearing of a gas turbine test bench according to an embodiment of the present application with reference to the accompanying drawings.

[0038] Figure 1 This is a schematic diagram of the structure of a monitoring system for a gas turbine test bench thrust bearing proposed in an embodiment of the present application, as shown in FIG. Figure 1 As shown, the system includes: a lubricating oil supply line 1, a lubricating oil return line 2, an oil return tank 3, a thrust bearing 5, a bearing temperature measuring device 7, an axial thrust force measuring ring 8 and a control module 9.

[0039] The lubricating oil supply circuit 1 includes an oil supply temperature measuring device 1.1, which is used to measure the lubricating oil supply temperature.

[0040] Specifically, the present application configures a lubricating oil supply temperature measuring point on the thrust bearing oil supply line, and sets an oil supply temperature measuring device 1.1 at the measuring point to measure the lubricating oil supply temperature T1.

[0041] The lubricating oil return line 2 includes a first metal chip measuring device 2.1 and a return oil temperature measuring device 2.2. The first metal chip measuring device 2.1 is used to measure the mass change of metal chips in the bearing return oil pipeline, and the return oil temperature measuring device 2.2 is used to measure the lubricating oil return temperature.

[0042] Specifically, this application deploys a metal debris detection device on the thrust bearing oil return line to detect metal debris G1 in the bearing oil return line. An oil return temperature measurement point is also deployed on the thrust bearing oil return line, where an oil return temperature measurement device 2.2 is installed to measure the lubricating oil return temperature T2.

[0043] The oil return tank 3 includes a second metal chip measuring device 3.1, which is used to measure the mass change of metal chips in the oil return tank of the bearing.

[0044] Specifically, another metal debris inspection device is configured in the oil return collection box of the present application to detect metal debris G2 in the oil return tank 3 of the bearing.

[0045] The bearing temperature measuring device 7 is arranged at any interface adjacent to the thrust bearing 5 , and is used to measure the bearing temperature. The axial thrust force ring 8 is used to measure the axial thrust on the bearing thrust surface.

[0046] Specifically, the present application arranges a temperature measuring point at any interface near the thrust bearing 5 in the system, and sets a bearing temperature measuring device 7 at the temperature measuring point to measure the temperature T5, which can represent the temperature of the thrust bearing 5. Figure 1 As shown, the present application further configures an axial thrust force measuring ring 8 on the thrust surface of the thrust bearing 5 to measure the axial thrust F generated by the rotor of the bearing.

[0047] In one embodiment of the present application, the system further includes: a rotor and a stator, the axial thrust force measuring ring is an elastic ring, and the axial thrust force measuring ring is arranged on the mover or the stator.

[0048] Specifically, this embodiment can measure the axial thrust F by measuring the deformation of the elastic ring. The axial thrust force ring can be as follows Figure 1 As shown, it is provided on the thrust surface of the rotor 4, but it can also be provided on the stator 6. Since the force generated by the rotor 4 can be transmitted to the stator 6, the present embodiment can also provide an axial thrust force measuring ring 8 on the stator 6, thereby enriching the layout of the monitoring system and being able to adapt to the layout requirements of the monitoring system in different working scenarios.

[0049] In one embodiment of the present application, the bearing temperature measuring device is arranged on the bearing thrust surface, or is arranged near the interface between the rotor and the thrust bearing, or is arranged near the interface between the stator and the thrust bearing.

[0050] Specifically, the present application sets the bearing temperature measuring device 7 in the area adjacent to the thrust bearing 5. Figure 1 As shown, the bearing temperature measuring device 7 is arranged at the interface between the stator 6 and the bearing, or at the interface between the rotor 4 and the bearing, or on the thrust surface of the bearing.

[0051] For example, taking a rolling ball bearing as an example, the measuring point is close to the rolling element. Since the temperature of the rolling element cannot be measured directly, the temperature of the bearing outer ring close to the rolling element is measured; taking a sliding bearing as an example, the measuring point is located on the bearing shell. Since the temperature on the thrust contact surface of the bearing shell cannot be measured directly, the temperature of the bearing shell close to the thrust contact surface is measured.

[0052] The control module 9 is respectively connected to each measuring device for communication. The control module 9 is used to combine the received multiple temperature measurement values, metal debris detection values ​​and axial thrust, judge the current working state of the thrust bearing based on multi-parameter correlation analysis, and perform protection control according to the working state.

[0053] Specifically, such as Figure 1 As shown, control module 9 is communicatively connected to oil supply temperature measuring device 1.1, first metal chip measuring device 2.1, return oil temperature measuring device 2.2, second metal chip measuring device 3.1, bearing temperature measuring device 7, and axial thrust force ring 8. Each measuring device is equipped with a communication unit for remote measurement, transmitting measured data to control module 9 via wireless or wired communication. Control module 9 controls data acquisition from the measuring devices, performs computational analysis on the measured data, determines the operating status of thrust bearing 5, and implements protective control in the event of a thrust bearing 5 failure.

[0054] In one embodiment of the present application, the control module is specifically configured to calculate an average value of metal debris in the bearing oil return line and the metal debris in the bearing oil return tank, and use the average value as a metal debris detection value.

[0055] Specifically, the control module 9 calculates the average value of the mass change G1 of the metal debris in the bearing oil return line and the mass change G2 of the metal debris in the oil return tank 3 as the metal debris detection value G, thereby comprehensively monitoring the metal debris in different areas.

[0056] It is understood that because control module 9 receives multiple types of monitoring data, axial thrust and metal debris monitoring data are not used alone to determine bearing failure, but are used in conjunction with temperature measurement data. Control module 9 uses a method based on multi-parameter correlation analysis to accurately monitor the operating status of thrust bearing 5.

[0057] In summary, the monitoring system for the thrust bearing of the gas turbine test bench of the embodiment of the present application adopts a combined monitoring method for multiple parameters such as oil supply temperature, return oil temperature, bearing temperature, axial thrust and metal debris, which can fully and systematically monitor the real working status of the thrust bearing. The arrangement position of the axial thrust measurement point and the bearing temperature measurement point of the system is not limited to being fixed in one place, and can be arranged on the stator or on the rotor, and can be adjusted according to on-site needs, thereby enriching the monitoring method of the thrust bearing and improving the applicability of thrust bearing monitoring. The measurements of axial thrust and bearing temperature obtained by the system are closer to the real values, which improves the authenticity of the monitoring data, and adopts a multi-parameter monitoring method to avoid the false alarm of thrust bearing failure caused by a single temperature monitoring. As a result, the system improves the comprehensiveness and accuracy of the thrust bearing monitoring results.

[0058] To more clearly illustrate the specific implementation process of determining the current operating state of a thrust bearing based on multi-parameter correlation analysis and performing protective control on the thrust bearing based on the current operating state, the following describes in detail a method for monitoring a thrust bearing of a gas turbine test bench, as proposed in an embodiment of the present application. This method is applied to the monitoring system for the thrust bearing of the gas turbine test bench in the aforementioned embodiment, namely, the method of this embodiment is implemented by performing correlation operations using data monitored by the monitoring system in the aforementioned embodiment. The method can be executed by the control module in the aforementioned embodiment.

[0059] Figure 2 This is a flow chart of a method for monitoring a thrust bearing of a gas turbine test bench proposed in an embodiment of the present application, as shown in FIG. Figure 2 As shown, the method includes the following steps:

[0060] Step S101: Acquire multiple parameters collected in real time by a monitoring system of a thrust bearing of a gas turbine test bench, wherein the multiple parameters include lubricating oil supply temperature, lubricating oil return temperature, bearing temperature, metal debris detection value, and axial thrust.

[0061] Specifically, the monitoring system for the thrust bearing of the gas turbine test bench in the above-described embodiment continuously collects multiple monitoring parameters, thereby obtaining parameters related to the operating status of the thrust bearing in real time, facilitating subsequent processing and analysis of the real-time data. The specific implementation process for monitoring multiple parameters and the parameters obtained are described in the above-described system embodiment and will not be repeated here.

[0062] Step S102: Determine multiple correlation thresholds for multiple parameters through the trained multi-parameter coupling relationship model.

[0063] Specifically, this application pre-analyzes the mechanisms by which various thrust bearing failures cause parameter changes and acquires a large amount of historical operating data from the gas turbine test bench thrust bearing, including operating data under normal operating conditions and under various failure modes. This historical operating data is used as training data, and combined with the analyzed parameter change mechanisms, the constructed neural network model is trained and adjusted. After training, a multi-parameter coupling relationship model is obtained. This multi-parameter coupling relationship model can be used to determine various baseline correlation thresholds for lubricating oil supply temperature T1, bearing temperature T5, lubricating oil return temperature T2, axial thrust F, and metal debris G.

[0064] The associated threshold is the threshold that each parameter should meet when the thrust bearing is in a certain working state. The threshold corresponding to each parameter may be different, so the associated threshold can be used to determine the current working state of the thrust bearing.

[0065] For example, when the thrust bearing is in normal working condition, the temperature difference of T5 minus T1 should be greater than 20°C and the fluctuation amplitude of F should be less than 10% of the rated value. Then the associated thresholds under this working condition include the temperature difference threshold of T5 minus T1 and the fluctuation amplitude threshold of F. This application analyzes the principle of parameter change so that the constructed network model learns the coupling relationship between multiple parameters. For example, this embodiment analyzes that the heat generated by the thrust bearing is due to the friction between the bearing sliding body and the inner and outer rings of the bearing during operation; at the same time, the friction state is aggravated because the thrust bearing is subjected to axial force, and the friction appears in the form of energy loss, resulting in an increase in the bearing temperature T5 and the return oil temperature T2. The friction of the bearing will produce metal debris, especially when the bearing is mechanically damaged, the metal debris detection value rises sharply.

[0066] It should be noted that this application can use long short-term memory networks (LSTM) and Transformer models to construct multi-parameter coupling relationship models. The specific model training process can refer to the implementation methods in related technologies, and this application does not impose any restrictions on this.

[0067] Step S103: perform integration operations on the various parameters continuously collected within a preset time period, compare the various integral values ​​used to characterize parameter changes with the associated thresholds, and determine whether the thrust bearing meets any fault mode in the fault library. If so, perform protection control on the thrust bearing based on the fault information of any fault mode obtained from the fault library.

[0068] Specifically, when determining the current operating state of a thrust bearing based on multi-parameter correlation analysis, the present application first performs a time-series correlation analysis on the multiple parameters acquired. This involves integrating the parameters continuously acquired over a preset time period to determine the changing trends of each parameter within that time period, including the rate of increase and decrease of the parameter values. The calculated integral values ​​representing the parameter changes are then compared with corresponding correlation thresholds. Through correlation threshold analysis, it is determined whether the current parameters meet the conditions of any typical fault mode stored in a pre-built fault library. If so, the thrust bearing's current fault mode is detected.

[0069] In one embodiment of the present application, the multi-parameter coupling relationship model determines multiple correlation thresholds, including time-series correlation thresholds and data calculation thresholds. The fault library includes feature vectors for seven typical fault modes. Fault type identification is achieved by matching the calculated combined features of each parameter with the feature vectors (composed of time-series correlation thresholds) of each typical fault mode in the fault library. In this embodiment, correlation threshold analysis is used to determine whether the thrust bearing is in any of the fault modes in the fault library, including the following situations:

[0070] As a first example, when the lubricating oil supply temperature and the lubricating oil return temperature remain stable, and the increasing rates of the bearing temperature, metal debris detection value and axial thrust are respectively greater than the corresponding timing correlation thresholds, it is determined that the thrust bearing is in the first fault mode.

[0071] For example, if T1 is stable, T2 is stable, T5 rises slowly, F increases and G exceeds the threshold but the rising rate remains stable, and by comparing the associated thresholds, it is determined that the T5 rising rate is greater than 5°C / 30min, the F rising rate is greater than 15% / 30min and the G rising rate is greater than 50% / 30min, then the thrust bearing is determined to be in the first fault mode.

[0072] Among them, the timing correlation thresholds in this example are the rising rate thresholds of T5, F and G. This example calculates the temperature rise of T5 and the rising amplitudes of F and G per unit time, thereby obtaining the changing trends of these three parameters and comparing them with the corresponding correlation thresholds respectively.

[0073] It should be noted that the calculation method of the time series correlation threshold and the change trend of each correlation parameter in the subsequent examples can refer to the determination method of this example and will not be repeated here.

[0074] As a second example, when the lubricating oil supply temperature, bearing temperature and axial thrust remain stable, and the increasing rates of the lubricating oil return temperature and metal debris detection value are respectively greater than the corresponding timing correlation thresholds, it is determined that the thrust bearing is in the second fault mode.

[0075] For example, if T1 is stable, F is stable, and T5 is stable, and T2 temperature rise rate and G rise rate exceed certain thresholds, 3 °C / min and 0.3 mg / min respectively, then the thrust bearing is determined to be in the second failure mode.

[0076] As a third example, in the case where the oil return temperature, metal debris detection value, and axial thrust remain stable, and the oil supply temperature rise rate is greater than a corresponding temporal correlation threshold, and the oil supply temperature and bearing temperature difference is less than a corresponding correlation threshold, the thrust bearing is determined to be in the third failure mode.

[0077] For example, if T2 is stable, F is stable, and G is stable, and T1 rise rate is greater than a certain threshold, and T1 and T5 temperature difference is reduced to less than a certain threshold, T1 rise rate > 5 °C / min and T5 and T1 temperature difference < 30 °C in this example, then the thrust bearing is determined to be in the third failure mode.

[0078] As a fourth example, in the case where the oil supply temperature, bearing temperature, axial thrust, and metal debris detection value remain stable, and the oil return temperature rise rate is greater than a corresponding temporal correlation threshold, the thrust bearing is determined to be in the fourth failure mode.

[0079] For example, if T1 is stable, T5 is stable, F is stable, and G is stable, and T2 temperature rise rate exceeds a certain threshold, 10 °C / min in this example, then the thrust bearing is determined to be in the fourth failure mode.

[0080] As a fifth example, in the case where the oil supply temperature, oil return temperature, axial thrust, and metal debris detection value remain stable, and the bearing temperature rise rate is greater than a corresponding temporal correlation threshold, the thrust bearing is determined to be in the fifth failure mode.

[0081] For example, if T1 is stable, T2 is stable, F is stable, and G is stable, and T5 temperature rise rate exceeds a certain threshold, 5 °C / min in this example, then the thrust bearing is determined to be in the fifth failure mode.

[0082] As a sixth example, in the case where the oil supply temperature, axial thrust, and metal debris detection value remain stable, and the bearing temperature rise rate is greater than a corresponding temporal correlation threshold, and the oil return temperature reduction rate is greater than a corresponding temporal correlation threshold, the thrust bearing is determined to be in the sixth failure mode.

[0083] For example, if T1 is stable, F is stable, and G is stable, and T5 and T2 temperature changes are opposite and exceed a certain threshold, T5 rise rate > 2 °C / min and T2 reduction rate > 3 °C / min in this example, then the thrust bearing is determined to be in the sixth failure mode.

[0084] As a seventh example, when the lubricating oil supply temperature and the lubricating oil return temperature remain stable, and the rate of increase of the bearing temperature, the increase amplitude of the axial thrust and the rate of increase of the metal debris detection value are respectively greater than the corresponding timing correlation thresholds, it is determined that the thrust bearing is in the seventh fault mode.

[0085] For example, if T1 is stable and T2 is stable, and the T5 temperature rise rate, F rise amplitude and G rise rate exceed certain thresholds, which in this example are 10°C / minute, 150% and 0.3 mg / minute respectively, then the thrust bearing is determined to be in the seventh fault mode.

[0086] Furthermore, after determining the current fault mode of the thrust bearing, relevant fault information about the fault mode is obtained from the fault library, and then the thrust bearing is protected and controlled using the fault information.

[0087] In one embodiment of the present application, the acquired fault information includes the cause of the fault and the type of fault, and protection control is performed on the broken thrust bearing, including: determining the fault severity and protection measures based on the cause of the fault and the type of fault; determining the early warning method based on the fault severity, and executing protection measures on the thrust bearing.

[0088] Specifically, when pre-building a fault library, this embodiment first acquires multi-dimensional thrust bearing fault knowledge. This knowledge is then structured based on ontology theory to construct a fault library. This fault library contains information such as the fault cause and type corresponding to each fault mode in the aforementioned examples. Furthermore, the fault cause and type corresponding to the currently determined fault mode can be directly obtained from the fault library.

[0089] Continuing with the above example, the cause of the first fault mode is that the lubricating oil emulsification causes the viscosity to decrease, and the bearing preload relaxes with the running time, causing the friction pair clearance to change; the fault type is lubricating oil deterioration, natural wear expansion of bearing clearance or attenuation of installation preload.

[0090] The cause of the second failure mode mentioned above is wear and fatigue peeling of the bearing rolling elements, sliding elements or raceways; the failure type is bearing wear or surface peeling, and has not yet spread to deep materials.

[0091] The cause of the third failure mode mentioned above is that the sudden increase in oil supply temperature causes the lubrication viscosity to decrease, the bearing oil film thickness is insufficient, the friction heat cannot be effectively removed, and the heat dissipation efficiency is sharply reduced, resulting in a decrease in temperature difference; the failure type is lubrication system cooling failure (such as oil cooler scaling, insufficient cooling water flow) or oil supply pipeline throttling failure.

[0092] The cause of the fourth fault mode mentioned above is abnormal heat exchange in the lubricating oil system or obstruction of oil circulation, which causes heat accumulation inside the warning bearing, and then causes lubrication deterioration or local overheating; the fault type is blockage of the lubricating oil circuit or cooling failure.

[0093] The cause of the fifth fault mode mentioned above is that the clearance is too small, the roller is skewed or the lubrication is poor, resulting in a sharp increase in friction heat, or the temperature rise is too fast, causing bearing annealing, hardness reduction or cage deformation; the fault type is local damage to the bearing or worsening of friction.

[0094] The cause of the sixth fault mode mentioned above is a sudden decrease in the amount of lubricating oil circulation (such as oil pump failure or oil circuit leakage), which results in the inability to effectively remove the friction heat of the bearing (the decrease in return oil temperature can indicate this cause), and the return oil does not fully absorb heat (the continuous increase in bearing temperature T5 can indicate this cause); the fault type is leakage in the lubricating oil supply pipeline or rupture and leakage in the return oil pipeline.

[0095] The cause of the seventh failure mode mentioned above is large-scale peeling of the bearing or burning of the thrust pad, which causes the bearing to get stuck or break instantly; the failure type is severe fatigue peeling or severe over-limit of axial load.

[0096] Furthermore, this embodiment can combine multiple factors, such as the determined fault cause, the actual conditions on the gas turbine test bench site, and the actual state of the thrust bearing, to determine protective measures for different fault modes, and then implement these protective measures to protect the thrust bearing. Furthermore, based on the determined fault type and site conditions, the fault severity corresponding to each fault mode is determined, and the fault severity reflects the severity and warning urgency of each fault mode.

[0097] Furthermore, a corresponding warning method is determined based on the degree of the fault, and a warning is issued to the staff according to the warning method, and the staff is reminded to implement relevant protection measures for the thrust bearing.

[0098] Continuing with the above example, if the fault severity of the first fault mode is a minor fault, the warning urgency level is determined to be a minor warning, and this warning method includes sending text and voice alarm messages to the staff's mobile terminal. Protective measures for the thrust bearing in the first fault mode include: lubricant quality inspection and replacement; and rechecking and adjusting the bearing preload.

[0099] If the fault severity of the second fault mode is a minor fault, the warning urgency level is determined to be a minor warning. Protective measures for the thrust bearing in the second fault mode include: lubricant quality testing and lubricant replacement; locating damaged components through vibration spectrum analysis; and repairing and replacing the bearing.

[0100] If the third fault mode is considered moderate, the warning urgency level is determined to be moderate. This warning includes sending text and voice alarms to personnel's mobile devices and controlling the gas turbine test bench to generate audible and visual alarms. Protective measures for the thrust bearing in this third fault mode include: immediately switching to a backup oil cooler, checking cooling water pressure and temperature, cleaning the oil supply filter, and checking for abnormal throttle valve opening.

[0101] The fourth fault mode is considered a moderate fault, and the warning urgency level is determined to be a moderate warning. Protective measures for the thrust bearing in this fourth fault mode include: immediately inspecting the cooling system (e.g., oil cooler, filter), clearing the oil lines; strengthening lubrication flow monitoring; and, if the condition persists within 10 minutes, reducing load and preparing for shutdown for maintenance.

[0102] If the fifth fault mode is moderate to severe, the warning urgency level is determined to be moderate to severe. This warning includes sending text and voice alarms to personnel's mobile devices, controlling the gas turbine test bench to emit audible and visual alarms, and sending alarm information to the remote monitoring center. Protective measures for the thrust bearing in this fifth fault mode include adjusting clearance or preload, checking installation accuracy, and initiating an emergency shutdown to prevent burnout if the temperature continues to rise for more than five minutes.

[0103] If the sixth fault mode is severe, the warning urgency level is severe, and the warning method is the same as the moderate and severe warning method. Protective measures for the thrust bearing in the sixth fault mode include: immediately starting the backup oil pump, checking the main oil pump outlet pressure, and shutting down the machine to check for leaks in the oil return line.

[0104] If the seventh fault mode is classified as a severe fault, the warning urgency level is determined to be a severe warning. Protective measures for the thrust bearing in this seventh fault mode include: immediate emergency shutdown, prohibiting any adjustments; inspecting the axial thrust system (e.g., balance chamber, seals); disassembly and replacement of the bearing and associated damaged components; and checking the alignment accuracy of the equipment's shafting.

[0105] Step S104: When the fault mode does not conform to the fault library, a risk index is calculated based on the dynamic weights and associated thresholds of the temperature parameters and mechanical parameters, and protection control is performed on the thrust bearing according to the risk index.

[0106] Specifically, if the correlation threshold analysis in the previous step determines that none of the current parameters meet any typical failure modes in the fault library, the correlation between multiple parameters is used to calculate the risk index R. The calculation of the risk index R includes dynamic weight analysis of temperature and mechanical parameters, as well as calculation of the coefficients of each parameter based on the aforementioned data operation thresholds determined by the multi-parameter coupling relationship model.

[0107] Among them, the temperature parameters include the above-mentioned lubricating oil supply temperature, lubricating oil return temperature and bearing temperature, and the mechanical parameters include the above-mentioned metal debris detection value and axial thrust.

[0108] In one embodiment of the present application, the risk index is calculated, including the following steps: first, the risk coefficient of each parameter is calculated separately according to the measured value and data operation threshold of each parameter; then, according to the type of abnormal parameter, weight coefficients are dynamically assigned to temperature parameters and mechanical parameters; finally, the risk index is calculated by combining the risk coefficient and measured value of each parameter and the weight coefficient of each type of parameter.

[0109] Specifically, the failure mode determined in this embodiment is not typical, and the risk index R is calculated based on the correlation between multiple parameters. The calculation formula is as follows:

[0110] R=α(δ1T1+δ2T2+δ3T5)+β(δ4F+δ5G)

[0111] Among them, α is the weight of temperature parameters, β is the weight of mechanical parameters, α+β=1, δ i is the risk coefficient of the i-th parameter, i=1,2…5.

[0112] α and β are determined through a dynamic weight analysis mechanism, automatically assigning weight coefficients based on the type of parameter anomaly. For example, if a mechanical parameter is determined to be abnormal, the weight of temperature parameters will be set to 40% and that of mechanical parameters to 60%. For another example, if a temperature parameter is determined to be abnormal, α will be set to 0.6 and β to 0.4.

[0113] In the above formula, when calculating the risk coefficient δ of each parameter i When , first subtract the corresponding data operation threshold from the measured value of the parameter, and then divide the difference by the corresponding data operation threshold, that is, δ = (measured value - threshold) / threshold.

[0114] Then, according to the value of the currently calculated risk index R, the current fault degree of the thrust bearing and the corresponding protection measures are determined.

[0115] For example, when R > 0.8, it's considered a severe fault and the system is shut down immediately for processing. When 0.8 ≥ R ≥ 0.5, it's considered a moderate fault and the changes in each monitoring value are continuously observed. The subsequent processing method is then determined based on the changes. When 0.5 > R > 0.3, it's considered a minor fault and processing is performed after the system is shut down.

[0116] It is understandable that after executing step S103 and step S104, if it is determined that neither of the above failure modes is met, it can be determined that the thrust bearing is currently in a normal working state.

[0117] Therefore, this application breaks through the limitations of traditional single-parameter threshold alarms by introducing parameter correlation analysis (including calculations and analysis of temperature differences, fluctuation amplitudes, and trend integration). Furthermore, a weighting mechanism enables precise location of fault types. For example, coupled analysis of temperature and mechanical parameters can distinguish between different faults such as lubrication failure and mechanical wear. Furthermore, a time-series trend integration algorithm can capture progressive faults (such as lubricant deterioration). Compared to sudden rise threshold judgment, this method can provide earlier warning time and issue timely alarms at the early stages of a fault.

[0118] In summary, the method for monitoring the thrust bearing of a gas turbine test bench implemented in this application, combined with multiple monitoring parameters and the judgment logic of thrust bearing faults, can accurately determine whether the thrust bearing is currently faulty, and determine the specific fault type and cause of the thrust bearing, thereby facilitating timely protection and control in the early stages of the bearing failure. The method adopts a multi-parameter monitoring method to avoid single temperature monitoring that causes false alarms for thrust bearing faults, and can implement corresponding protection measures for different fault types. As a result, the method improves the comprehensiveness and accuracy of the thrust bearing monitoring results, and can timely and accurately perform reasonable protection and control when a thrust bearing fault occurs, which is conducive to ensuring the safe and stable operation of the thrust bearing.

[0119] In order to implement the above-mentioned embodiments, the present application also proposes a non-temporary computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements a method for monitoring the thrust bearing of a gas turbine test bench as described in any one of the above-mentioned second aspect embodiments of the present application.

[0120] It should be noted that it should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logical functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0121] In addition, in the description of this application, the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they should not be understood as limiting the present invention.

[0122] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0123] In the present invention, unless otherwise specified or limited, the terms "installed," "connected," "connect," "fixed," etc. should be understood in a broad sense. For example, they can refer to fixed connection, detachable connection, or integration; mechanical connection, electrical connection; direct connection, or indirect connection through an intermediate medium; internal communication between two components, or interaction between two components, unless otherwise specified. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0124] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0125] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for monitoring a thrust bearing of a gas turbine test bench, characterized in that: The method comprises the following steps: Acquiring multiple parameters collected in real time by a monitoring system of the thrust bearing of the gas turbine test bench, wherein the multiple parameters include lubricating oil supply temperature, lubricating oil return temperature, bearing temperature, metal debris detection value, and axial thrust, wherein the metal debris detection value is an average of a mass change of metal debris in the bearing return oil pipeline and a mass change of metal debris in the bearing return oil tank; Determining multiple correlation thresholds for the multiple parameters using the trained multi-parameter coupling relationship model, wherein the multiple correlation thresholds are thresholds that the multiple parameters should meet under a certain working state of the thrust bearing, and the multiple correlation thresholds include a time series correlation threshold and a data operation threshold; performing an integration operation on the multiple parameters continuously collected within a preset time period, comparing each integral value used to characterize parameter changes with the time sequence correlation threshold, determining whether the thrust bearing meets any fault mode in a fault library, and, if so, performing protection control on the thrust bearing based on fault information of any fault mode obtained from the fault library; In the case of not meeting each fault mode in the fault library, a risk index is calculated based on the dynamic weights of the temperature parameters and the mechanical parameters and the associated threshold, and the thrust bearing is protected and controlled according to the risk index. The mechanical parameters include the axial thrust of the metal debris detection value. The calculation of the risk index includes: calculating the risk coefficient of each parameter according to the measured value of each parameter and the data operation threshold; dynamically allocating weight coefficients to the temperature parameters and the mechanical parameters according to the type of abnormal parameters; and calculating the risk index by combining the risk coefficient and the measured value of each parameter and the weight coefficient of each type of parameter.

2. The method according to claim 1, characterized in that The step of determining whether the thrust bearing meets any fault mode in the fault library includes: When the lubricating oil supply temperature and the lubricating oil return temperature remain stable, and the increasing rates of the bearing temperature, the metal debris detection value, and the axial thrust are respectively greater than corresponding time-series correlation thresholds, it is determined that the thrust bearing is in the first fault mode; When the lubricating oil supply temperature, the bearing temperature, and the axial thrust remain stable, and the increasing rates of the lubricating oil return temperature and the metal debris detection value are respectively greater than corresponding time series correlation thresholds, it is determined that the thrust bearing is in the second fault mode; When the lubricating oil return temperature, the metal debris detection value and the axial thrust remain stable, the increase rate of the lubricating oil supply temperature is greater than the corresponding timing correlation threshold, and the temperature difference between the lubricating oil supply temperature and the bearing temperature is less than the corresponding correlation threshold, it is determined that the thrust bearing is in the third fault mode.

3. The method according to claim 2, characterized in that The step of determining whether the thrust bearing is in any fault mode in the fault library further includes: When the lubricating oil supply temperature, the bearing temperature, the axial thrust, and the metal debris detection value remain stable, and the rate of increase of the lubricating oil return temperature is greater than the corresponding time-series correlation threshold, it is determined that the thrust bearing is in the fourth fault mode; When the lubricating oil supply temperature, the lubricating oil return temperature, the axial thrust, and the metal debris detection value remain stable, and the increasing rate of the bearing temperature is greater than the corresponding time series correlation threshold, it is determined that the thrust bearing is in the fifth fault mode; When the lubricating oil supply temperature, the axial thrust, and the metal debris detection value remain stable, and the rate of increase of the bearing temperature is greater than the corresponding time-series correlation threshold, and the magnitude of decrease of the lubricating oil return temperature is greater than the corresponding time-series correlation threshold, it is determined that the thrust bearing is in the sixth fault mode; When the lubricating oil supply temperature and the lubricating oil return temperature remain stable, and the increasing rate of the bearing temperature, the increasing amplitude of the axial thrust, and the increasing rate of the metal debris detection value are respectively greater than the corresponding timing correlation thresholds, it is determined that the thrust bearing is in the seventh fault mode.

4. The method according to claim 2, characterized in that The fault information includes the fault cause and the fault type, and the protection control of the broken thrust bearing includes: Determine the fault severity and protection measures based on the fault cause and the fault type; An early warning method is determined based on the fault degree, and the protective measures are performed on the thrust bearing.

5. A monitoring system for a gas turbine test bench thrust bearing, applied to the method according to any one of claims 1 to 4, characterized in that: include: Lubricating oil supply line, lubricating oil return line, oil return tank, thrust bearing, bearing temperature measuring equipment, axial thrust force measuring ring and control module; among which, The lubricating oil supply circuit includes an oil supply temperature measuring device, which is used to measure the lubricating oil supply temperature and obtain multiple parameters collected in real time by the monitoring system of the thrust bearing of the gas turbine test bench, wherein the multiple parameters include lubricating oil supply temperature, lubricating oil return temperature, bearing temperature, metal debris detection value and axial thrust; The lubricating oil return line includes a first metal debris measuring device and a return oil temperature measuring device, wherein the first metal debris measuring device is used to measure the mass change of metal debris in the bearing return oil line, and the return oil temperature measuring device is used to measure the lubricating oil return temperature; The oil return tank includes a second metal debris measuring device, which is used to measure the mass change of metal debris in the bearing oil return tank; The bearing temperature measuring device is arranged at any interface adjacent to the thrust bearing, and is used to measure the bearing temperature. The axial thrust force measuring ring is used to measure the axial thrust on the thrust surface of the bearing. The control module is respectively communicated with each measuring device. The control module is used to combine the received multiple temperature measurement values, metal debris detection values ​​and the axial thrust, determine the current working state of the thrust bearing based on multi-parameter correlation analysis, and perform protection control based on the working state. The control module is specifically used to: calculate the average value of the mass change of the metal debris in the bearing oil return pipeline and the mass change of the metal debris in the bearing oil return tank, and use the average value as the metal debris detection value.

6. The system according to claim 5, characterized in that Also includes: The rotor and the stator, the axial thrust force measuring ring is an elastic ring, and the axial thrust force measuring ring is arranged on the rotor or the stator.

7. The system according to claim 6, characterized in that The bearing temperature measuring device is arranged on the bearing thrust surface, or is arranged near the interface between the rotor and the thrust bearing, or is arranged near the interface between the stator and the thrust bearing.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for monitoring a thrust bearing of a gas turbine test bench according to any one of claims 1 to 4 is implemented.

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