Low-pressure cylinder last-stage blade monitoring method, system, equipment and medium

Abstract

The invention relates to a low-pressure cylinder last-stage blade monitoring method, system and device and a medium, and the method comprises the steps: obtaining a blade vibration amplitude sequence based on an eddy current signal; and determining a blade vibration mode based on the root-mean-square correlation coefficient. And determining a blade vibration spectrum through a sparse reconstruction method according to a real blade vibration amplitude sequence and an ideal blade high-frequency vibration amplitude sequence which are obtained in advance. A relation function is established according to the inlet and outlet temperature of the last-stage blade, the flow boundary condition and the maximum equivalent thermal stress characteristic, and the current thermal stress of the last-stage moving blade is determined based on the relation function according to the actual boundary condition. And based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the final-stage moving blade thermal stress, a low-pressure cylinder final-stage blade monitoring result is determined. High-precision monitoring of the low-pressure cylinder last-stage blade is achieved, and safe operation of the low-pressure cylinder last-stage blade is guaranteed. The problem that low-pressure cylinder last-stage blade monitoring is low in accuracy in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the technical field of low-pressure cylinder last-stage blade monitoring, and in particular to a low-pressure cylinder last-stage blade monitoring method, system, equipment and medium. Background Art

[0002] At present, in order to cope with the increasing demand for deep peak regulation of cogeneration units, a large number of cogeneration units have undergone near-zero output transformation of low-pressure cylinders. However, long-term deviation from the initial design operating conditions has brought challenges to the safety of low-pressure cylinder operation.

[0003] When the low-pressure cylinder of the steam turbine is at zero output, the flow field of the last-stage blades is extremely complex. The steam cannot fill the flow channel and forms a complex vortex. It is easy to have flow separation, backflow, back suction and other phenomena, which cause the blade stress to increase sharply. Under the interaction of bending stress, centrifugal force, thermal stress, etc., the blades twist and deform. When the exciting force frequency and the natural frequency coincide or are close, the blades resonate and cause blade breakage accidents. When the current low-pressure cylinder is transformed at zero output, the safety of unit operation is judged only by monitoring the inlet and outlet steam temperatures of the last-stage blades. The monitoring accuracy is low, resulting in the problem often not being discovered until the blades break and the machine shuts down during actual operation.

[0004] Based on the above reasons, the monitoring of the last stage blades of the low-pressure cylinder in the existing related technology has the problem of low accuracy. Summary of the invention

[0005] The embodiments of the present application provide a method, system, device and medium for monitoring the last stage blades of a low-pressure cylinder, so as to at least solve the problem of low accuracy in monitoring the last stage blades of a low-pressure cylinder in the related art.

[0006] In a first aspect, an embodiment of the present application provides a method for monitoring a low-pressure cylinder last-stage blade, the method comprising:

[0007] The eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder is sampled by a high-frequency acquisition board, and a blade vibration amplitude sequence is obtained based on the eddy current signal;

[0008] Measuring the root mean square correlation coefficient of the angles between adjacent blade circles by multiple sensors, and determining the blade vibration mode based on the root mean square correlation coefficient;

[0009] According to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance, the blade vibration spectrum is determined by sparse reconstruction method;

[0010] Establishing a relationship function according to the inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determining the current thermal stress of the last-stage moving blades based on the relationship function according to the actual boundary conditions;

[0011] The monitoring result of the last-stage blade of the low-pressure cylinder is determined based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last-stage moving blade.

[0012] In one embodiment, the eddy current signal sampling of the last-stage moving blade diaphragm of the low-pressure cylinder by a high-frequency acquisition board and the acquisition of the blade vibration amplitude sequence based on the eddy current signal include:

[0013] The eddy current signal arranged on the last-stage moving blade diaphragm is sampled by a high-frequency acquisition board, and the continuous voltage signal of the eddy current is converted into a discrete digital signal;

[0014] Comparing the discrete digital quantity signal with a blade arrival reference threshold value to obtain a blade arrival sequence of the eddy current;

[0015] Obtaining a blade vibration time difference sequence according to the blade arrival sequence and a reference key phase signal of a main shaft of a steam turbine;

[0016] A blade vibration amplitude sequence is obtained according to the blade vibration time difference sequence and the reference angular velocity.

[0017] In one embodiment, the step of measuring the root mean square correlation coefficient of the angles between adjacent blade circles by using a plurality of sensors, and determining the blade vibration mode based on the root mean square correlation coefficient, comprises:

[0018] According to the blade tip timing principle, the first circle vibration sequence and the second circle vibration sequence measured by multiple sensors in adjacent circles are obtained;

[0019] According to the reference key phase signal sequence, the first circle vibration sequence is converted into a first circle blade angle sequence, and the second circle vibration sequence is converted into a second circle blade angle sequence;

[0020] Calculate the Pearson correlation coefficient of the first circle blade angle sequence and the second circle blade angle sequence to obtain the correlation coefficient of adjacent circle blade angle sequences;

[0021] The root mean square calculation is performed on the correlation coefficients of the adjacent circle blade angle sequences to determine the blade vibration mode.

[0022] In one embodiment, performing root mean square calculation on the correlation coefficient of the adjacent circle blade angle sequence to determine the blade vibration mode includes:

[0023] Performing root mean square calculation on the correlation coefficient of the adjacent blade angle sequence to obtain the root mean square coefficient;

[0024] When the root mean square coefficient is greater than or equal to the preset coefficient, determining that the blade vibration mode is a synchronous vibration mode;

[0025] When the root mean square coefficient is less than the preset coefficient, it is determined that the blade vibration mode is an asynchronous vibration mode.

[0026] In one embodiment, determining the blade vibration spectrum by a sparse reconstruction method based on a pre-acquired real blade vibration amplitude sequence and an ideal blade high-frequency vibration amplitude sequence includes:

[0027] According to the blade tip timing principle, the actual vibration amplitude sequence actually monitored by several sensors within a preset rotation period and the ideal vibration amplitude sequence under ideal conditions are obtained;

[0028] Calculating a sensing matrix according to the actual installation position of the sensor to obtain the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence;

[0029] According to the inverse matrix of Fourier transform, the relationship between the real vibration amplitude sequence and the ideal vibration spectrum is obtained;

[0030] According to the sparse reconstruction method, the characteristic spectrum is calculated with the minimum 1-norm of the ideal vibration spectrum to determine the blade vibration spectrum.

[0031] In one embodiment, the step of calculating the sensing matrix according to the actual installation position of the sensor to obtain the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence includes:

[0032] According to the installation angle of the eddy current sensor on the moving blade diaphragm, a sensing matrix is ​​constructed;

[0033] According to the perception matrix, a transfer matrix between the real vibration amplitude sequence and the ideal vibration amplitude sequence is established to obtain the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence.

[0034] In one embodiment, the step of establishing a relationship function according to the inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determining the current thermal stress of the last-stage moving blades based on the relationship function according to the actual boundary conditions includes:

[0035] According to the profiles of the last-stage stationary blades and moving blades, a three-dimensional model of the stationary blades and moving blades is established;

[0036] Meshing the three-dimensional model, encrypting the number of meshes at key flow-through locations of the blade, and verifying mesh independence, wherein the key locations are locations that produce greater flow effects;

[0037] Conduct fluid-solid coupling analysis to determine the maximum equivalent thermal stress characteristics of the last-stage moving blades under variable operating conditions;

[0038] Establishing a relationship function according to the maximum equivalent thermal stress characteristics and the actually measured inlet and outlet temperatures and flow boundary conditions of the last-stage blades;

[0039] According to the current actual boundary conditions and based on the relationship function, the current thermal stress of the last-stage moving blade is determined.

[0040] In a second aspect, an embodiment of the present application provides a low-pressure cylinder last-stage blade monitoring system, the system comprising a blade vibration amplitude sequence module, a blade vibration mode module, a blade vibration spectrum module, a last-stage moving blade thermal stress module and a monitoring result module, wherein:

[0041] The blade vibration amplitude sequence module is used to sample the eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder through a high-frequency acquisition board, and obtain the blade vibration amplitude sequence based on the eddy current signal;

[0042] The blade vibration mode module is used to measure the root mean square correlation coefficient of the angles between adjacent blade circles through multiple sensors, and determine the blade vibration mode based on the root mean square correlation coefficient;

[0043] The blade vibration spectrum module is used to determine the blade vibration spectrum through a sparse reconstruction method according to a pre-acquired real blade vibration amplitude sequence and an ideal blade high-frequency vibration amplitude sequence;

[0044] The last-stage moving blade thermal stress module is used to establish a relationship function according to the inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determine the current last-stage moving blade thermal stress based on the relationship function according to the actual boundary conditions;

[0045] The monitoring result module is used to determine the monitoring result of the last-stage blade of the low-pressure cylinder based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last-stage moving blade.

[0046] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a method for monitoring the last stage blades of a low-pressure cylinder is implemented as described in the first aspect above.

[0047] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for monitoring the last stage blades of a low-pressure cylinder as described in the first aspect above.

[0048] A low-pressure cylinder last-stage blade monitoring method, system, equipment and medium provided in the embodiments of the present application have at least the following technical effects.

[0049] The eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder is sampled through a high-frequency acquisition board, and the blade vibration amplitude sequence is obtained based on the eddy current signal. The root mean square correlation coefficient of the angle between adjacent ring blades is measured by multiple sensors, and the blade vibration mode is determined based on the root mean square correlation coefficient. According to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance, the blade vibration spectrum is determined by the sparse reconstruction method. According to the inlet and outlet temperature of the last-stage blade, the flow boundary conditions and the maximum equivalent thermal stress characteristics are established. According to the actual boundary conditions, based on the relationship function, the current thermal stress of the last-stage moving blade is determined. Based on the blade vibration amplitude sequence, blade vibration mode, blade vibration spectrum and thermal stress of the last-stage moving blade, the monitoring results of the last-stage blade of the low-pressure cylinder are determined. High-precision monitoring of the last-stage blade of the low-pressure cylinder is achieved to ensure the safe operation of the last-stage blade of the low-pressure cylinder. The problem of low accuracy in the monitoring of the last-stage blade of the low-pressure cylinder in related technologies is solved.

[0050] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0052] Figure 1 is a flow chart of a method for monitoring the last stage blades of a low pressure cylinder according to an embodiment of the present application;

[0053] Figure 2 is a flowchart of step S101 according to an exemplary embodiment;

[0054] Figure 3 is a flowchart of step S102 according to an exemplary embodiment;

[0055] Figure 4 is a flowchart of step S103 according to an exemplary embodiment;

[0056] Figure 5 is a flowchart of step S104 according to an exemplary embodiment;

[0057] Figure 6 is a block diagram of a system for monitoring the last stage blades of a low pressure cylinder according to an exemplary embodiment;

[0058] Figure 7 is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0060] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0061] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0062] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0063] In a first aspect, an embodiment of the present application provides a method for monitoring the last stage blades of a low pressure cylinder. Figure 1 This is a flow chart for monitoring the last stage blades of a low pressure cylinder. Figure 1 As shown, a method for monitoring the last stage blades of a low-pressure cylinder includes:

[0064] Step S101: sampling the eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder through a high-frequency acquisition board, and obtaining the blade vibration amplitude sequence based on the eddy current signal.

[0065] Step S102: measuring the root mean square correlation coefficient of the angles between adjacent blade circles by using a plurality of sensors, and determining the blade vibration mode based on the root mean square correlation coefficient.

[0066] Step S103: determining the blade vibration spectrum by a sparse reconstruction method according to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance.

[0067] Step S104, establishing a relationship function according to the inlet and outlet temperatures of the last stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determining the current thermal stress of the last stage moving blades based on the relationship function according to the actual boundary conditions.

[0068] Step S105: Determine the monitoring result of the last-stage blade of the low-pressure cylinder based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last-stage moving blade.

[0069] In summary, the embodiment of the application provides a method for monitoring the last-stage blades of a low-pressure cylinder. The eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder is sampled by a high-frequency acquisition board, and the blade vibration amplitude sequence is obtained based on the eddy current signal. The root mean square correlation coefficient of the angle between adjacent ring blades is measured by multiple sensors, and the blade vibration mode is determined based on the root mean square correlation coefficient. According to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance, the blade vibration spectrum is determined by the sparse reconstruction method. A relationship function is established according to the inlet and outlet temperature of the last-stage blade, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and the current thermal stress of the last-stage moving blade is determined based on the relationship function according to the actual boundary conditions. Based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last-stage moving blade, the monitoring results of the last-stage blades of the low-pressure cylinder are determined. High-precision monitoring of the last-stage blades of the low-pressure cylinder is achieved to ensure the safe operation of the last-stage blades of the low-pressure cylinder. The problem of low accuracy in the monitoring of the last-stage blades of the low-pressure cylinder in the related art is solved.

[0070] Figure 2 is a flowchart of step S101 according to an exemplary embodiment. Figure 2 As shown, step S101, sampling the eddy current signal of the last stage moving blade diaphragm of the low pressure cylinder through a high frequency acquisition board, and obtaining the blade vibration amplitude sequence based on the eddy current signal. Specifically, the following steps are included:

[0071] Step S1011, sampling the eddy current signal arranged on the last-stage moving blade partition through a high-frequency acquisition board, and converting the continuous voltage signal of the eddy current into a discrete digital signal.

[0072] Optionally, a number of eddy current probes are installed at intervals on the last-stage moving blade partition of the low-pressure cylinder. In the embodiment of the present application, three eddy current probes are installed. The high-frequency acquisition board samples the eddy current signal arranged on the last-stage moving blade partition, and converts the continuous voltage signal of the eddy current into a discrete digital signal. By sampling the eddy current signal through the high-frequency acquisition board, it is ensured that the tiny vibration details of the blade when it rotates at high speed are captured. By comparing the discrete digital signal with the reference threshold reached by the blade, it is possible to accurately determine when each blade passes the position of the eddy current probe.

[0073] Step S1012: compare the discrete digital signal with the blade arrival reference threshold to obtain the blade arrival sequence of the eddy current.

[0074] Optionally, the collected discrete digital signal is compared with the blade arrival reference threshold to obtain the blade arrival sequence t measured by the three eddy current sensors.1 , t 2 , t 3 Specifically, the discrete digital signal is compared with the reference threshold, and the digital point that is greater than or equal to the reference threshold is obtained as the blade arrival sequence point. By creating a time marker for each blade and recording the time point when it passes through the probe, basic data is provided for subsequent vibration analysis.

[0075] Step S1013: Obtain a blade vibration time difference sequence according to the blade arrival sequence and the reference key phase signal of the turbine main shaft.

[0076] Optionally, the blade arrival sequence t monitored by the eddy current sensor 1 , t 2 , t 3 Subtract the reference key phase signal t0 on the shaft to obtain the blade vibration time difference sequence Δt 1 , Δt 2 , Δt 3 By comparing the blade arrival times measured by the eddy-current sensors with the reference keyphase signal on the shaft (a fixed reference point), the deviation of each blade from the ideal position, i.e. the vibration time difference, can be calculated.

[0077] Step S1014: Obtain a blade vibration amplitude sequence according to the blade vibration time difference sequence and the reference angular velocity.

[0078] Optionally, the blade vibration time difference sequence is multiplied by the reference angular velocity to obtain the blade vibration amplitude sequence x 1 , x 2 , x 3 By multiplying the blade vibration time difference sequence with the reference angular velocity, the time difference can be converted into the actual vibration displacement, that is, the vibration amplitude. According to the vibration amplitude, it is helpful to diagnose whether the blade has imbalance, wear or other faults.

[0079] Step S101 implements real-time monitoring of blade vibration, which helps to promptly detect potential problems and prevent blade damage caused by excessive vibration. In addition, through multi-point vibration data, the location of the problem can be more accurately located to assist in fault diagnosis.

[0080] Figure 3 is a flowchart of step S102 according to an exemplary embodiment. Figure 3 As shown, step S102, measuring the root mean square correlation coefficient of the angles between adjacent blade circles by multiple sensors, and determining the blade vibration mode based on the root mean square correlation coefficient. Specifically, the following steps are included:

[0081] Step S1021: According to the blade tip timing principle, a first circle vibration sequence and a second circle vibration sequence measured by a plurality of sensors in adjacent circles are obtained.

[0082] Optionally, the first vibration sequence x measured by multiple sensors in adjacent circles is calculated based on the blade tip timing principle. 11 , x 21 , x 31 And the second vibration sequence x 12 , x 22 , x 32 The principle of tip timing is that by measuring the time it takes for the tip of the blade to pass the sensor, the vibration of the blade can be inferred. Measurements of adjacent circles can help analyze the vibration characteristics of the blade in different rotation cycles. Using multiple eddy current sensors (for example, 3) can obtain vibration data at multiple locations, improving the reliability and accuracy of the measurement. Obtaining the vibration sequence of the first and second circles can compare the vibration conditions in different rotation cycles, which helps to identify changes in vibration patterns.

[0083] Step S1022: according to the reference key phase signal sequence, convert the first circle vibration sequence into a first circle blade angle sequence, and convert the second circle vibration sequence into a second circle blade angle sequence.

[0084] Optionally, according to the reference key phase signal sequence, the first circle vibration sequence x 11 , x 21 , x 31 And the second vibration sequence x 12 , x 22 , x 32 Converted into the angle sequence between blades, the angle sequence of the first circle is θ 11 ,θ 21 ,θ 31 And the angle sequence θ of the second circle 12 ,θ 22 ,θ 32 The reference keyphase signal is a fixed reference point used to determine the initial position of the blade. By comparing the vibration sequence with the reference keyphase signal, the angle of each blade relative to the reference position can be calculated. The angle sequence of multiple sensors can provide more comprehensive vibration information and help identify the vibration mode of the blade.

[0085] Step S1023: Calculate the Pearson correlation coefficient of the first circle blade angle sequence and the second circle blade angle sequence to obtain the correlation coefficient of adjacent circle blade angle sequences.

[0086] Optionally, the Pearson correlation coefficient of the angle sequence of adjacent circles is calculated to obtain the correlation coefficient ρ of the angle sequence of adjacent circles of blades monitored by three eddy current sensors 1 , ρ 2 , ρ 3The Pearson correlation coefficient is a statistical indicator used to measure the degree of linear correlation between two variables. By calculating the correlation coefficient of the adjacent circle angle sequence, the similarity of the vibration mode between the two circles can be evaluated. Calculate the correlation coefficient ρ of the adjacent circle blade angle sequence 1 , ρ 2 , ρ 3 , can quantify the similarity of vibration modes between two turns. The angle series correlation coefficient of multiple sensors can provide a more comprehensive comparison of vibration modes, which helps to identify the vibration characteristics of the blade.

[0087] Step S1024, performing root mean square calculation on the correlation coefficients of the adjacent circle blade angle sequence to determine the blade vibration mode. In one embodiment, step S1024, performing root mean square calculation on the correlation coefficients of the adjacent circle blade angle sequence to obtain the root mean square coefficient. Specifically, when the root mean square coefficient is greater than or equal to the preset coefficient, determining that the blade vibration mode is a synchronous vibration mode; when the root mean square coefficient is less than the preset coefficient, determining that the blade vibration mode is an asynchronous vibration mode.

[0088] Optionally, the blade vibration mode is determined based on the root mean square coefficient, and the root mean square coefficient greater than or equal to the preset coefficient is synchronous vibration, and the root mean square coefficient less than the preset coefficient is asynchronous vibration. Root mean square is a statistical method used to calculate the average square root of a set of data. By calculating the root mean square of the correlation coefficient, the similarity of the vibration modes of multiple sensors can be comprehensively evaluated. A preset coefficient (for example, 0.5-0.9, which can be 0.9 in the embodiment of the present application) is set to distinguish between synchronous vibration and asynchronous vibration modes. When the root mean square coefficient is greater than or equal to 0.9, it indicates that the vibration modes of adjacent circles are highly similar, that is, the blade is in a synchronous vibration mode. Asynchronous vibration: When the root mean square coefficient is less than 0.9, it indicates that the vibration modes of adjacent circles are quite different, that is, the blade is in an asynchronous vibration mode.

[0089] Step S102: Through multi-sensor and multi-turn measurement, the vibration of the blade can be accurately monitored to improve the reliability and accuracy of the data. Through statistical analysis methods (such as Pearson correlation coefficient and root mean square calculation), the vibration mode of the blade can be effectively identified, and synchronous vibration and asynchronous vibration can be distinguished. The identification of vibration mode helps to detect abnormal vibration of the blade in time, prevent potential failures, and improve the operating safety and reliability of the turbine.

[0090] Figure 4 is a flowchart of step S103 according to an exemplary embodiment. Figure 4 As shown, step S103, according to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance, the blade vibration spectrum is determined by sparse reconstruction method. Specifically, the following steps are included:

[0091] Step S1031, according to the blade tip timing principle, obtain the actual vibration amplitude sequence actually monitored by several sensors within a preset rotation period, and the ideal vibration amplitude sequence under ideal conditions.

[0092] Optionally, based on the blade tip timing principle, a blade vibration amplitude sequence x[300,1] actually monitored by a plurality of sensors within a preset rotation period, and an ideal blade high-frequency vibration amplitude sequence y[2000,1] are obtained. In the embodiment of the present application, the plurality of sensors may be 3, and the preset rotation period may be 100 preset rotation periods. The blade tip timing principle means that the vibration amplitude of the blade can be calculated by measuring the time it takes for the tip of the blade to pass through the sensor. A preset rotation period range (e.g., 100 rotation periods) is selected, and real vibration data is collected within this range. Assuming the vibration condition of the blade under ideal conditions, an ideal vibration amplitude sequence is generated. The blade vibration amplitude sequence x[300,1] actually monitored by multiple sensors (e.g., 3) within 100 rotation periods can reflect the actual vibration condition of the blade. Generate an ideal blade high-frequency vibration amplitude sequence y[2000,1] for comparison and calibration of actual data.

[0093] Step S1032, calculate the perception matrix according to the actual installation position of the sensor, and obtain the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence. Specifically, it includes: constructing a perception matrix according to the installation angle of the eddy current sensor on the moving blade partition; according to the perception matrix, establishing a transfer matrix of the real vibration amplitude sequence and the ideal vibration amplitude sequence, and obtaining the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence.

[0094] Optionally, a sensing matrix Φ is constructed according to the installation angles of the three eddy current sensors on the moving blade partition; based on the sensing matrix Φ, a transfer matrix x[300,1]=Φ*y[2000,1] is established between the actual monitored blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence. The sensing matrix Φ reflects the influence of the sensor position on the vibration signal and can convert the ideal vibration amplitude sequence y into the actual monitored vibration amplitude sequence x. Through the transfer matrix x[300,1]=Φ*y[2000,1], the mathematical relationship between the actual vibration amplitude sequence and the ideal vibration amplitude sequence can be established, providing a basis for subsequent analysis.

[0095] Step S1033: Obtain the relationship between the real vibration amplitude sequence and the ideal vibration spectrum according to the inverse Fourier transform matrix.

[0096] Optionally, according to the inverse matrix ψ of Fourier transform, the relationship between the high-frequency vibration amplitude of the blade and the spectrum sequence f under ideal conditions is established: y[2000,1]=ψ*f[2000,1]. The relationship between the actual monitored blade vibration amplitude sequence x and the spectrum sequence f is established: x[300,1]=Φ*ψ*f[2000,1]. The ideal vibration amplitude sequence y is converted into the spectrum sequence f by Fourier transform. The relationship between the ideal vibration amplitude sequence y and the spectrum sequence f is established by the inverse matrix ψ of Fourier transform. Combining the perception matrix Φ and the inverse matrix ψ of Fourier transform, the relationship between the actual vibration amplitude sequence x and the spectrum sequence f is established: x[300,1]=Φ*ψ*f[2000,1]. The vibration amplitude sequence in the time domain is converted into the spectrum sequence in the frequency domain by Fourier transform, which is convenient for analyzing the frequency components of vibration. The mathematical relationship between the actual vibration amplitude sequence and the spectrum sequence is established, which provides a basis for subsequent sparse reconstruction.

[0097] Step S1034: According to the sparse reconstruction method, the characteristic spectrum is calculated with the minimum 1-norm of the ideal vibration spectrum to determine the blade vibration spectrum.

[0098] Optionally, based on the sparse reconstruction method, the ideal vibration spectrum f 0 The characteristic spectrum f is calculated by minimizing the 1 norm of the spectrum. Using the sparse reconstruction method (such as L1 norm minimization), the main characteristic spectrum f is extracted from the spectrum sequence f 1 By minimizing the 1-norm of the spectrum sequence f, the sparsest solution, i.e., the main vibration frequency component, is found. Through the sparse reconstruction method, the main characteristic spectra can be extracted from the complex spectrum. These characteristic spectra reflect the main vibration parameters of the blade. This helps to diagnose the health status and potential problems of the blade.

[0099] Step S103: Through multi-sensor and multi-cycle measurement, the vibration of the blade can be accurately monitored to improve the reliability and accuracy of the data. Through Fourier transform and sparse reconstruction, the main vibration spectrum can be effectively extracted from the complex vibration data, which helps to timely detect abnormal vibration of the blade, prevent potential failures, and improve the safety and reliability of blade operation.

[0100] Figure 5 is a flowchart of step S104 according to an exemplary embodiment. Figure 5 As shown, step S104, establish a relationship function according to the inlet and outlet temperature of the last stage blade, the flow boundary condition and the maximum equivalent thermal stress characteristics, and determine the current thermal stress of the last stage moving blade based on the relationship function according to the actual boundary conditions. Specifically, it includes the following steps:

[0101] Step S1041, establishing a three-dimensional model of the stationary blades and the moving blades according to the profiles of the last-stage stationary blades and the moving blades.

[0102] Optionally, the Blade Gen module of ANSYS software can be used to create an accurate three-dimensional geometric model based on the profile data of the stationary blades and moving blades. ANSYS software is a large-scale general-purpose finite element analysis (FEA) software developed by ANSYS, USA. BladeGen is a module in ANSYS software specifically used for blade design. Step S1041 ensures that the geometric parameters of the model are consistent with the actual blades, providing an accurate basis for subsequent simulation analysis. It can contain all the geometric details of the blades, such as the shape, size, angle, etc. of the blades, to ensure the authenticity and reliability of the model.

[0103] Step S1042, meshing the three-dimensional model, encrypting the number of meshes at key flow-through locations of the blades, and verifying the independence of the meshes, wherein the key locations are locations that produce greater flow effects.

[0104] Optionally, meshing is performed in the TurboGrid module, and the number of meshes in the key parts of the blade flow is encrypted to verify the independence of the mesh. The TurboGrid module can be used for meshing, especially for mesh encryption in the key parts of the blade flow (such as the blade tip, root, etc.) to improve the calculation accuracy. By adjusting the grid density, it is ensured that the calculation results do not change significantly due to changes in the grid. Through mesh encryption, the flow effect and stress distribution in key parts are accurately captured.

[0105] Step S1043: Perform fluid-solid coupling analysis to determine the maximum equivalent thermal stress characteristics of the last-stage moving blades under variable operating conditions.

[0106] Optionally, a fluid-structure interaction (FSI) analysis can be performed in ANSYS software to simulate the impact of fluid on blades and the structural response of blades under different operating conditions. The maximum equivalent thermal stress characteristics of the last-stage moving blades under variable operating conditions are calculated, and the effects of thermal stress and mechanical stress are comprehensively considered. The interaction between fluid flow and structural deformation is considered to provide a more realistic stress distribution.

[0107] Step S1044: Establish a relationship function based on the maximum equivalent thermal stress characteristics and the actually measured inlet and outlet temperatures and flow boundary conditions of the last-stage blades.

[0108] Optionally, a mathematical relationship model is established between the actual measured inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics. Through the relationship function, the maximum equivalent thermal stress of the blade can be quickly estimated when the actual operating conditions are given, without repeating complex CFD simulations. The relationship function can be directly applied to engineering practice to improve the efficiency of monitoring and diagnosis.

[0109] Step S1045: Determine the current thermal stress of the last-stage moving blade according to the current actual boundary conditions and based on the relationship function.

[0110] Optionally, according to the current actual boundary conditions (such as inlet and outlet temperatures, flow rate, etc.), the relationship function established in step S1044 is used to calculate and monitor the thermal stress of the last-stage moving blade in real time. The thermal stress state of the blade can be monitored in real time to detect potential problems in a timely manner. Through real-time monitoring, measures can be taken in advance to prevent blade damage caused by excessive thermal stress and ensure the safe and stable operation of the equipment.

[0111] Step S104 ensures the accuracy of simulation analysis through precise three-dimensional modeling and high-precision meshing. Through fluid-solid coupling analysis, the interaction between fluid and structure is fully considered to provide a more realistic stress distribution. By establishing a relationship function, the thermal stress of the blade can be quickly evaluated under actual operating conditions, improving the efficiency of monitoring and diagnosis. Real-time monitoring of blade thermal stress is achieved, potential problems are discovered in a timely manner, and the safe and stable operation of the equipment is guaranteed.

[0112] In summary, the embodiment of the application provides a method for monitoring the last-stage blades of a low-pressure cylinder. The eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder is sampled by a high-frequency acquisition board, and the blade vibration amplitude sequence is obtained based on the eddy current signal. The root mean square correlation coefficient of the angle between adjacent ring blades is measured by multiple sensors, and the blade vibration mode is determined based on the root mean square correlation coefficient. According to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance, the blade vibration spectrum is determined by the sparse reconstruction method. A relationship function is established according to the inlet and outlet temperature of the last-stage blade, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and the current thermal stress of the last-stage moving blade is determined based on the relationship function according to the actual boundary conditions. Based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last-stage moving blade, the monitoring results of the last-stage blades of the low-pressure cylinder are determined. High-precision monitoring of the last-stage blades of the low-pressure cylinder is achieved to ensure the safe operation of the last-stage blades of the low-pressure cylinder. The problem of low accuracy in the monitoring of the last-stage blades of the low-pressure cylinder in the related art is solved.

[0113] The beneficial effects of the present application also include: monitoring the vibration and thermal stress of the last-stage blades by installing eddy current sensors on the last-stage moving blade diaphragms for high-frequency sampling. Real-time monitoring of the vibration amplitude of the blades based on the tip timing principle, reducing measurement errors through multiple circumferentially arranged eddy current sensors; constructing an angle sequence between adjacent circles of blades, and using multiple sensors to measure the root mean square correlation coefficient of adjacent circles to determine the blade vibration mode, which not only has good anti-interference capabilities, but also has a high resolution for vibration mode recognition; based on the sparse reconstruction method, parameter recognition of undersampled blade vibration signals is performed, with good frequency division interval recognition and amplitude calculation. Computational fluid dynamics software is used to analyze the thermal stress characteristics of the unit under variable operating conditions, establish a relationship function model between the maximum equivalent thermal stress and key measurement parameters, and monitor blade thermal stress in real time.

[0114] In a second aspect, an embodiment of the present application provides a system for monitoring the last stage blades of a low-pressure cylinder. Figure 6 FIG. 1 is a block diagram of a system for monitoring the last blade of a low-pressure cylinder according to an exemplary embodiment. Figure 6 As shown, the system includes a blade vibration amplitude sequence module 610, a blade vibration mode module 620, a blade vibration spectrum module 630, a last stage moving blade thermal stress module 640 and a monitoring result module 650, wherein:

[0115] The blade vibration amplitude sequence module 610 is used to sample the eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder through a high-frequency acquisition board, and obtain the blade vibration amplitude sequence based on the eddy current signal;

[0116] A blade vibration mode module 620 is used to measure the root mean square correlation coefficient of the angles between adjacent blade circles through multiple sensors, and determine the blade vibration mode based on the root mean square correlation coefficient;

[0117] The blade vibration spectrum module 630 is used to determine the blade vibration spectrum by a sparse reconstruction method according to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance;

[0118] The last stage moving blade thermal stress module 640 is used to establish a relationship function according to the inlet and outlet temperatures of the last stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determine the current last stage moving blade thermal stress based on the relationship function according to the actual boundary conditions;

[0119] The monitoring result module 650 is used to determine the monitoring result of the last stage blade of the low pressure cylinder based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last stage moving blade.

[0120] In summary, the embodiment of the present application provides a low-pressure cylinder last-stage blade monitoring system, which solves the problem of low accuracy in the monitoring of the last-stage blades of the low-pressure cylinder in the related art through the blade vibration amplitude sequence module 610, the blade vibration mode module 620, the blade vibration spectrum module 630, the last-stage moving blade thermal stress module 640 and the monitoring result module 650. Specifically, the power prediction file is obtained based on the power prediction model according to the historical operation data, and the power prediction file upload request is triggered; in the process of uploading the power prediction file, the network connection status and the device status are monitored in real time to obtain the real-time monitoring results, and the power prediction file is uploaded according to the target transmission strategy in the transmission strategy library based on the real-time monitoring results; in response to receiving the power upload file, according to the confirmation signal of the dispatching department, it is judged whether the power prediction file is successfully uploaded; if not, the parameters of the target transmission strategy in the transmission strategy library are adjusted until the power prediction file is successfully uploaded. The efficient, accurate and stable upload of the power prediction file is realized. The problem of how to dynamically adjust the transmission strategy according to real-time data in the related art to improve the efficiency and stability of data transmission is solved.

[0121] It should be noted that the system for monitoring the last blade of a low-pressure cylinder provided in this embodiment is used to implement the above-mentioned implementation mode, and the descriptions that have been made will not be repeated. As used above, the terms "module", "unit", "subunit", etc. can implement a combination of software and / or hardware of predetermined functions. Although the device described in the above embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0122] In a third aspect, an embodiment of the present application provides an electronic device, Figure 7 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Figure 7 As shown, the electronic device may include a processor 71 and a memory 72 storing computer program instructions.

[0123] Specifically, the processor 71 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0124] Among them, the memory 72 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 72 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 72 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 72 may be inside or outside the data processing device. In a specific embodiment, the memory 72 is a non-volatile memory. In a specific embodiment, the memory 72 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (Erasable ProgrammableRead-Only Memory, EPROM for short), an electrically erasable PROM (Electrically Erasable ProgrammableRead-Only Memory, EEPROM for short), an electrically alterable ROM (Electrically Alterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0125] The memory 72 may be used to store or cache various data files required for processing and / or communication, as well as possible computer program instructions executed by the processor 71 .

[0126] The processor 71 implements any one of the low-pressure cylinder last-stage blade monitoring methods in the above-mentioned embodiments by reading and executing computer program instructions stored in the memory 72 .

[0127] In one embodiment, a device for monitoring the last blade of a low-pressure cylinder may further include a communication interface 73 and a bus 70. Figure 7 As shown, the processor 71, the memory 72, and the communication interface 73 are connected via a bus 70 and communicate with each other.

[0128] The communication interface 73 is used to implement communication between the modules, devices, units and / or equipment in the embodiment of the present application. The communication port 73 can also implement data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage, and image / data processing workstations.

[0129] The bus 70 includes hardware, software or both, and couples the components of a low-pressure cylinder last stage blade monitoring device to each other. The bus 70 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 70 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 70 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0130] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a program stored thereon, and when the program is executed by a processor, a low-pressure cylinder last-stage blade monitoring method provided in the first aspect is implemented.

[0131] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0132] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of a low-pressure cylinder last stage blade monitoring method provided in the first aspect.

[0133] Among them, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0134] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0135] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for monitoring the last blade of a low-pressure cylinder, characterized in that: The method comprises: The eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder is sampled by a high-frequency acquisition board, and a blade vibration amplitude sequence is obtained based on the eddy current signal; Measuring the root mean square correlation coefficient of the angles between adjacent blade circles by multiple sensors, and determining the blade vibration mode based on the root mean square correlation coefficient; According to the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance, the blade vibration spectrum is determined by sparse reconstruction method; Establishing a relationship function according to the inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determining the current thermal stress of the last-stage moving blades based on the relationship function according to the actual boundary conditions; Based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration parameter and the thermal stress of the last-stage moving blade, a monitoring result of the last-stage blade of the low-pressure cylinder is determined.

2. The method according to claim 1, characterized in that The method of sampling the eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder by a high-frequency acquisition board and obtaining the blade vibration amplitude sequence based on the eddy current signal includes: The eddy current signal arranged on the last-stage moving blade diaphragm is sampled by a high-frequency acquisition board, and the continuous voltage signal of the eddy current is converted into a discrete digital signal; Comparing the discrete digital quantity signal with a blade arrival reference threshold value to obtain a blade arrival sequence of the eddy current; Obtaining a blade vibration time difference sequence according to the blade arrival sequence and a reference key phase signal of a main shaft of a steam turbine; A blade vibration amplitude sequence is obtained according to the blade vibration time difference sequence and the reference angular velocity.

3. The method according to claim 1, characterized in that The step of measuring the root mean square correlation coefficient of the angles between adjacent blade circles by using a plurality of sensors and determining the blade vibration mode based on the root mean square correlation coefficient comprises: According to the blade tip timing principle, the first circle vibration sequence and the second circle vibration sequence measured by multiple sensors in adjacent circles are obtained; According to the reference key phase signal sequence, the first circle vibration sequence is converted into a first circle blade angle sequence, and the second circle vibration sequence is converted into a second circle blade angle sequence; Calculate the Pearson correlation coefficient of the first circle blade angle sequence and the second circle blade angle sequence to obtain the correlation coefficient of adjacent circle blade angle sequences; The root mean square calculation is performed on the correlation coefficients of the adjacent circle blade angle sequences to determine the blade vibration mode.

4. The method according to claim 3, characterized in that The step of performing root mean square calculation on the correlation coefficients of the adjacent blade angle sequences to determine the blade vibration mode comprises: Performing root mean square calculation on the correlation coefficient of the adjacent blade angle sequence to obtain the root mean square coefficient; When the root mean square coefficient is greater than or equal to the preset coefficient, determining that the blade vibration mode is a synchronous vibration mode; When the root mean square coefficient is less than the preset coefficient, it is determined that the blade vibration mode is an asynchronous vibration mode.

5. The method according to claim 1, characterized in that The method of determining the blade vibration spectrum by a sparse reconstruction method based on the real blade vibration amplitude sequence and the ideal blade high-frequency vibration amplitude sequence acquired in advance includes: According to the blade tip timing principle, the actual vibration amplitude sequence actually monitored by several sensors within a preset rotation period and the ideal vibration amplitude sequence under ideal conditions are obtained; Calculating a sensing matrix according to the actual installation position of the sensor to obtain the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence; According to the inverse matrix of Fourier transform, the relationship between the real vibration amplitude sequence and the ideal vibration spectrum is obtained; According to the sparse reconstruction method, the characteristic spectrum is calculated with the minimum 1-norm of the ideal vibration spectrum to determine the blade vibration spectrum.

6. The method according to claim 5, characterized in that The step of calculating the sensing matrix according to the actual installation position of the sensor to obtain the relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence includes: According to the installation angle of the eddy current sensor on the moving blade diaphragm, a sensing matrix is ​​constructed; According to the perception matrix, a transfer matrix between the real vibration amplitude sequence and the ideal vibration amplitude sequence is established to obtain a relationship between the real vibration amplitude sequence and the ideal vibration amplitude sequence.

7. The method according to claim 1, characterized in that The step of establishing a relationship function according to the inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determining the current thermal stress of the last-stage moving blades based on the relationship function according to the actual boundary conditions includes: According to the profiles of the last-stage stationary blades and moving blades, a three-dimensional model of the stationary blades and moving blades is established; Meshing the three-dimensional model, encrypting the number of meshes at key flow-through locations of the blade, and verifying mesh independence, wherein the key locations are locations that produce greater flow effects; Conduct fluid-solid coupling analysis to determine the maximum equivalent thermal stress characteristics of the last-stage moving blades under variable operating conditions; Establishing a relationship function according to the maximum equivalent thermal stress characteristics and the actually measured inlet and outlet temperatures and flow boundary conditions of the last-stage blades; According to the current actual boundary conditions and based on the relationship function, the current thermal stress of the last-stage moving blade is determined.

8. A low-pressure cylinder last stage blade monitoring system, characterized in that: The system includes a blade vibration amplitude sequence module, a blade vibration mode module, a blade vibration spectrum module, a last-stage moving blade thermal stress module and a monitoring result module, wherein: The blade vibration amplitude sequence module is used to sample the eddy current signal of the last-stage moving blade diaphragm of the low-pressure cylinder through a high-frequency acquisition board, and obtain the blade vibration amplitude sequence based on the eddy current signal; The blade vibration mode module is used to measure the root mean square correlation coefficient of the angles between adjacent blade circles through multiple sensors, and determine the blade vibration mode based on the root mean square correlation coefficient; The blade vibration spectrum module is used to determine the blade vibration spectrum through a sparse reconstruction method according to a pre-acquired real blade vibration amplitude sequence and an ideal blade high-frequency vibration amplitude sequence; The last-stage moving blade thermal stress module is used to establish a relationship function according to the inlet and outlet temperatures of the last-stage blades, the flow boundary conditions and the maximum equivalent thermal stress characteristics, and determine the current last-stage moving blade thermal stress based on the relationship function according to the actual boundary conditions; The monitoring result module is used to determine the monitoring result of the last-stage blade of the low-pressure cylinder based on the blade vibration amplitude sequence, the blade vibration mode, the blade vibration spectrum and the thermal stress of the last-stage moving blade.

9. An electronic device, characterized in that: The method comprises a memory and a processor, a computer program stored in the memory and executable on the processor, and the processor implements a low-pressure cylinder last-stage blade monitoring method as claimed in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a low-pressure cylinder last-stage blade monitoring method according to any one of claims 1 to 7 is implemented.

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