High-cycle fatigue crack identification method based on temperature change

Abstract

The temperature change-based high-cycle fatigue crack identification method of the present application comprises: placing a test piece on a test platform of a fatigue testing machine, and arranging an infrared thermal imager on one side of the test platform; pre-processing temperature data of a surface of the test piece, extracting a plurality of maximum values of temperature in a monitoring area according to a frame number of collection, and constructing a data matrix M of temperature and time; performing sliding maximum value processing on the data matrix M by using a sliding window algorithm; calculating a first-order difference of a data matrix N to obtain a difference sequence matrix H, and determining a crack parameter of the test piece according to a thermal image corresponding to the time t; and determining a crack size of the test piece based on the crack parameter by using a pixel quantitative analysis method, so that the efficiency of the test is improved.

Description

Technical Field

[0001] This invention belongs to the technical field of fatigue identification methods, and particularly relates to a high-cycle fatigue crack identification method based on temperature changes. Background Technology

[0002] High-cycle fatigue is a fatigue phenomenon characterized by a failure cycle count in the range of 10⁵ to 10⁷, representing a long-life fatigue condition. It is a prevalent and critical issue in numerous fields such as aviation, aerospace, automotive, and machinery, particularly pronounced in aircraft gas turbine engines. Critical components like fans, compressors, and turbines are highly susceptible to fatigue cracks under prolonged alternating loads, potentially leading to premature engine failure and, in extreme cases, aircraft crashes with immeasurable loss of life and property. Therefore, reliable, timely, and early detection of high-cycle fatigue cracks, along with accurate identification and quantitative analysis, is crucial for ensuring the safe operation of critical components and preventing accidents. Traditional fatigue testing methods infer the fatigue performance of test specimens through big data simulation or by monitoring changes in specified parameters during testing. However, this method is prone to situations where actual cracks have already formed during testing but are not detected in real time by known methods, resulting in reduced testing efficiency.

[0003] In view of this, the present invention is hereby proposed. Summary of the Invention

[0004] The high-cycle fatigue crack identification method based on temperature variation provided by this invention solves the technical problem of low testing efficiency in existing fatigue testing methods. The technical solution of this invention has many beneficial effects, as described below: A method for identifying high-cycle fatigue cracks based on temperature changes, comprising: Step 1: The test piece is placed on the test platform of the fatigue testing machine, and an infrared thermal imager is set on one side of the test platform. The infrared thermal imager uses the test piece as the monitoring area and collects the temperature data of the test piece during the test. The frame rate of the infrared thermal imager is a preset multiple of the frame rate of the fatigue testing machine. Step 2: After the fatigue test, the temperature data of the test piece surface is preprocessed to improve the accuracy of the test data; multiple maximum values ​​of temperature in the monitoring area are extracted according to the number of acquisition frames, and a temperature-time data matrix M is constructed. Step 3: The data matrix M is processed using a sliding window algorithm to obtain the maximum temperature value, and the window value L of the sliding window is a preset value, so as to obtain the data matrix N with the maximum temperature value; Step 4: Calculate the first difference of the data matrix N to obtain the difference sequence matrix H, and determine the moment t when the crack initiation of the test piece changes abruptly based on the changing trend of the first difference value within a preset time before the fracture of the test piece. Determine the crack parameters of the test piece based on the heat map corresponding to the moment t. Step 5: The crack parameters are used to determine the crack size of the test piece based on a pixel-based quantitative analysis method.

[0005] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects: This method can monitor the temperature change of the structural surface in real time during high-cycle fatigue testing. By processing and analyzing the temperature data, it can determine the time and size of crack initiation, providing data support for life assessment based on fracture analysis. Attached Figure Description

[0006] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0007] Figure 1 A schematic diagram illustrating the sliding maximum value processing of the surface temperature maximum value; Figure 2 This is a schematic diagram of the first-order difference result of the sliding maximum value. Detailed Implementation

[0008] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0009] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this invention, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0010] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0011] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that aspects can be practiced without these specific details. To enable those skilled in the art to better understand the invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. 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 indicated technical features. Thus, features defined as "first" and "second" may explicitly or implicitly include one or more of that feature. In the description of the invention, unless otherwise stated, "a plurality of" means two or more.

[0012] like Figures 1 to 2 The high-cycle fatigue crack identification method based on temperature change shown employs a fatigue testing machine to conduct fatigue tests on the test piece. The method includes... Step 1: The test piece is placed on the test platform of the fatigue testing machine, and an infrared thermal imager is set up on one side of the test platform. The infrared thermal imager uses the test piece as the monitoring area and can collect the temperature data of the test piece during the test. The acquisition frame rate is a preset multiple of the frame rate of the fatigue testing machine, generally at least twice. A high-sensitivity and high-resolution infrared thermal imager is selected in the test to ensure that it can capture minute temperature changes. The parameters of the monitoring system are reasonably set, and the temperature measurement range should cover the highest temperature rise at the time of material fracture. In addition, in order to obtain more accurate temperature data, conventional settings are used to reduce the interference of ambient temperature fluctuations and thermal radiation. Then, a high-cycle fatigue crack infrared detection system is set up to monitor the temperature changes on the surface of the test piece in real time.

[0013] Step 2: After the fatigue test, the temperature data of the test piece surface is preprocessed, such as by screening and filtering to remove noise and outliers. The purpose is to improve the accuracy of the test data and the quality and reliability of the monitoring data. Extract multiple maximum values ​​of temperature within the monitoring area according to the number of acquisition frames (the maximum temperature value in the data acquired in each frame), and construct a "temperature-time" data matrix M in chronological order of all the maximum temperature values; Step 3: In order to highlight the trend and characteristics of temperature changes, and taking into account factors such as the material properties of the specimen, loading conditions and the performance of the monitoring system, the data matrix M uses a sliding window algorithm to process the sliding maximum value and presets the window value L. The window value L is determined according to the signal of the specimen under test, so as to obtain the data matrix N with the maximum temperature value. The purpose is to effectively smooth the data curve and remove local fluctuations and interference.

[0014] Step 4: Calculate the first-order difference of the data matrix N to obtain the difference sequence matrix H. Based on the changing trend of the first-order difference values ​​within a preset time period (generally five minutes) before the test piece fractures, determine the moment t when the crack initiation abruptly occurs in the test piece. Determine the parameters for crack appearance on the test piece based on the heat map corresponding to moment t. That is, find the location of the crack appearance through the heat map corresponding to moment t. Determining the moment t when the crack initiation abruptly occurs in the test piece includes... Select differential data during the temperature stabilization phase of the test piece (the temperature stabilization phase is when all temperature changes are within the threshold range, such as within 3°C), calculate the average value μ and standard deviation σ of the differential data, and preset the mutation threshold T=μ+nσ; A sliding window algorithm is used to sequentially scan the difference sequence matrix H. For example, analyzing the changing trends of the difference values ​​helps to capture the rate of temperature change and abrupt changes. The first-order difference of the data matrix N is calculated to form a new matrix H={h1,h2,...,h...}. k}; If at a certain moment m consecutive difference values ​​are all greater than the mutation threshold T, then that moment is determined to be the crack initiation moment t. That is, when the first consecutive m difference values ​​all exceed the threshold T, the starting moment of the continuous exceedance is determined to be the crack initiation moment t. Here, n is determined according to the sensitivity of the test piece, and m is determined according to the signal-to-noise ratio of the test piece.

[0015] Step 5: Determine the exact size of the crack on the test piece using a pixel-based quantitative analysis method, such as... Obtain the width dimension L (mm) of the test piece. Based on the number of pixels k occupied by the crack in the heat map at time t and the number of pixels q in the corresponding heat map, calculate the test crack parameter B = Lk / q of the test piece.

[0016] This method can monitor the temperature change of the structural surface in real time during high-cycle fatigue testing. By processing and analyzing the temperature data, it can determine the time and size of crack initiation, providing data support for life assessment based on fracture analysis.

[0017] For example, taking the LY12CZ aluminum alloy test piece as an example, the implementation process is as follows: 1) Establish an infrared monitoring system. Select a high-performance infrared thermal imager to ensure stable operation during high-cycle fatigue testing and accurate measurement of temperature changes on the specimen surface. Install the infrared thermal imager in a suitable location to fully cover the monitoring area of ​​the specimen. Set the imager parameters to a frame rate of 50Hz and a temperature measurement range of -20℃ to 150℃. In the testing environment, implement heat insulation and light-shielding measures to reduce environmental interference with temperature measurements.

[0018] 2) From the start to the end of the fatigue test, the surface temperature of the test piece is monitored in real time. Specifically, the surface temperature data of the test piece is preprocessed: The mean filtering algorithm is used to remove noise from the temperature data, then the maximum temperature value of the monitoring area is extracted, and a data matrix M is constructed in chronological order. A sliding maximum value processing method was applied to matrix M. After multiple trials and analyses, a sliding window of 5000 seconds was determined. The data matrix N was obtained through this sliding maximum value processing, as follows: Figure 1 The data matrices M and N were exported using MATLAB software, as shown below. Calculate the first-order difference of the data matrix N to form a new matrix P. Because the temperature change is significant during the initial loading stage due to the gradual increase in load, the difference values ​​change considerably. Therefore, we exclude the changes in the difference values ​​within the first five minutes before specimen fracture and focus on the changes in the difference values ​​after five minutes. We identify the moment when the difference values ​​begin to change frequently, t=1849s. Figure 2 As shown, by examining the corresponding heat map at that moment, the location where the crack appeared can be identified.

[0019] Based on the fact that the crack occupies 3 pixels on the heat map at time t=1849s, and given that the sample width W=30mm and the number of pixels q=66 in the heat map, the crack size is calculated to be L=k / W×q=1.35mm, and the crack location on the heat map at time t=1849s is also calculated. The fracture analysis results show that the fatigue crack appears on the left side of the specimen, which is consistent with the location of the crack in the thermal image. Furthermore, the crack length of 1.45 mm is within the 1.519 mm fatigue zone of the fracture analysis. Therefore, the fracture analysis results verify the accuracy of the above method in finding the location of the fatigue crack.

[0020] The product provided by this invention has been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the core ideas of this invention. It should be noted that those skilled in the art can make various improvements and modifications to the invention without departing from the principles of the invention, and these improvements and modifications also fall within the protection scope of the invention claims.

Claims

1. A method for identifying high-cycle fatigue cracks based on temperature changes, comprising conducting fatigue tests on the test piece at room temperature using a fatigue testing machine, characterized in that... Its methods include, Step 1: The test piece is placed on the test platform of the fatigue testing machine, and an infrared thermal imager is set on one side of the test platform. The infrared thermal imager uses the test piece as the monitoring area and collects the temperature data of the test piece during the test. The frame rate of the infrared thermal imager is twice the frame rate of the fatigue testing machine. Step 2: After the fatigue test, the temperature data of the test piece surface is preprocessed to improve the accuracy of the test data; multiple maximum values ​​of temperature in the monitoring area are extracted according to the number of acquisition frames, and a temperature-time data matrix M is constructed. Step 3: The data matrix M is processed using a sliding window algorithm to obtain the maximum temperature value, and the window value L of the sliding window is a preset value, so as to obtain the data matrix N with the maximum temperature value; Step 4: Calculate the first difference of the data matrix N to obtain the difference sequence matrix H, and determine the moment t when the crack initiation of the test piece changes abruptly after a preset time before the fracture of the test piece. Determine the crack parameters of the test piece based on the heat map corresponding to the moment t. Among them, the difference data of the temperature stabilization stage during the test of the test piece is selected, and the average value μ and standard deviation σ of the difference data are calculated. The abrupt change threshold T = μ + nσ is preset. The differential sequence matrix H is sequentially scanned using a sliding window algorithm. If at a certain moment m consecutive differential values ​​are all greater than the mutation threshold T, then the moment t is determined to be the crack initiation moment. Here, n is determined according to the sensitivity of the test piece, and m is determined according to the signal-to-noise ratio of the test piece. Step 5: The crack parameters are used to determine the crack size of the test piece based on a pixel-based quantitative analysis method, wherein, Obtain the width dimension L of the part to be measured; Based on the number of pixels k occupied by the crack in the corresponding heat map at time t and the number of pixels q in the corresponding heat map, the test crack parameter B = Lk / q of the test piece is calculated.

2. The high-cycle fatigue crack identification method according to claim 1, characterized in that, The preset duration in step 4 is 5 minutes.

Images