CN111105847B - Magnetic signal-based Cr-Ni-Fe alloy creep damage early and failure critical state judgment and early warning method - Google Patents

Magnetic signal-based Cr-Ni-Fe alloy creep damage early and failure critical state judgment and early warning method Download PDF

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CN111105847B
CN111105847B CN201911328137.9A CN201911328137A CN111105847B CN 111105847 B CN111105847 B CN 111105847B CN 201911328137 A CN201911328137 A CN 201911328137A CN 111105847 B CN111105847 B CN 111105847B
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吕运容
丛广佩
陈法林
段志宏
范志卿
李伟明
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Guangdong University of Petrochemical Technology
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Abstract

The invention provides a method for judging and early warning the creep damage early stage and the failure critical state of a Cr-Ni-Fe alloy based on a magnetic signal, which comprises the steps of measuring the coercive force, obtaining a magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy, obtaining an optimized Cr-Ni-Fe alloy magnetic signal characteristic rule curve and identifying and judging whether the Cr-Ni-Fe alloy has early creep damage or whether high-temperature damage enters the failure early stage critical state; the invention can determine whether creep damage occurs or not and whether the creep damage enters a failure critical state or not under the condition of not damaging the detected unit so as to remind production personnel to make a reasonable maintenance plan or replacement plan in advance, thereby reducing the safety risk caused by high-temperature damage failure to the maximum extent and meeting the requirements of high-temperature failure critical state diagnosis and maintenance plan alarm reminding in practical application.

Description

Magnetic signal-based Cr-Ni-Fe alloy creep damage early and failure critical state judgment and early warning method
Technical Field
The invention belongs to the field of high-temperature damage detection and monitoring of petroleum and petrochemical Cr-Ni-Fe alloy, and particularly relates to a method for judging and early warning the creep damage early stage and the failure critical state of Cr-Ni-Fe alloy based on a magnetic signal.
Background
High-temperature damage risks exist in many process links of petroleum and petrochemical industry, wherein carburization and creep damage are the most prominent, and the cracking failure of a high-temperature unit is often caused; secondly, once the combustible medium in the high-temperature unit is leaked and meets the open fire in the furnace, the high-temperature unit is often applied to the heating furnace, so that fire disasters and even explosion can be caused inevitably, and serious accidents or economic losses are caused, and in the case of petroleum and petrochemical industries, disaster cases caused by high-temperature failures of heating furnace tubes, cracking furnace tubes and the like of various process systems occur.
As for Cr-Ni-Fe alloy, carburization and creep deformation are often associated in the actual high-temperature Sun mountain process, and the carburization and creep deformation are related to the final material failure process, so that in practical application, in order to realize effective judgment of the critical failure state of a high-temperature unit and ensure continuous long-period operation, a technology and a method capable of comprehensively judging the influence of carburization and creep deformation are necessary, so that early and rapid in-situ identification and alarm of the critical state before material failure are realized, production personnel are reminded to make a reasonable maintenance plan or replacement plan in advance, and the safety risk caused by high-temperature damage failure is reduced to the maximum extent.
If and only after carburization occurs to a certain degree, relatively independent and fewer creep holes occur on an alloy grain boundary, creep begins to enter an initial development stage, and because the creep defect belongs to a relatively dangerous surface defect, an applicable quantitative detection method is greatly different from carburization, so that in practical application, in order to realize continuous long-period operation of a high-temperature unit, early and rapid in-situ identification and early warning of creep damage must be achieved, so that an inspection detection technology and a reasonable detection range are adopted according to the early warning result, and the safety risk brought by creep damage is reduced to the greatest extent. The requirements are difficult to meet by adopting the conventional ultrasonic, electromagnetic and ray technologies.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a method for judging and early warning the creep damage early stage and the failure critical state of the Cr-Ni-Fe alloy based on a magnetic signal.
The technical problem to be solved by the invention is realized by the following technical scheme:
a Cr-Ni-Fe alloy creep damage early stage and failure critical state judgment and early warning method based on magnetic signals is characterized by comprising the following steps:
step S1, carrying out regular coercivity in-situ detection on the Cr-Ni-Fe alloy used in the high-temperature environment, and obtaining coercivity measurement data of each period;
step S2, processing the obtained coercive force measurement data by using a data comprehensive analysis method to obtain a magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy;
s3, removing noise interference information in the coercivity measurement result of the step S1 to obtain coercivity data which is subjected to noise processing, and processing the obtained coercivity data which is subjected to noise processing by using a data comprehensive analysis method to obtain an optimized Cr-Ni-Fe alloy magnetic signal characteristic rule curve;
step S4, automatically identifying and judging whether the Cr-Ni-Fe alloy has early creep damage or not by using a characteristic identification algorithm according to the magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy in the step S2, if judging that the Cr-Ni-Fe alloy has early creep damage, and giving an early warning prompt that the Cr-Ni-Fe alloy is about to creep, automatically identifying and judging whether the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state in the early stage of failure or not according to the optimized Cr-Ni-Fe alloy magnetic signal characteristic rule curve in the step S3, and giving an early warning prompt that the Cr-Ni-Fe alloy is about to fail if judging that the high-temperature damage of the Cr-Ni-Fe alloy enters the critical state in the early stage of failure.
Further, in step S1, specifically, the step includes:
carrying out regular in-situ coercive force in-situ detection on the Cr-Ni-Fe alloy used in a high-temperature environment for N days, wherein m point positions are required to be measured on the unit structure of each Cr-Ni-Fe alloy in each detection, and each point position is used for measuring k data.
Further, in step S2, specifically, the step includes:
step S2.1, recording the j measurement result of the i point of the k measurement of each Cr-Ni-Fe alloy unit structure in the step S1 as dkijN, n is the total number of times of measurement, i is 1, 2, 3.. mu.u, u is the total number of points selected by each unit of measurement, and j is 1, 2, 3.. mu.v, v is the total number of coercive force data of each point;
step S2.2, calculating dkijAnd d(k-1)ijThe calculation formula is as follows:
Figure BDA0002328908190000021
wherein d iskij-lIs the l supplementary data of the k supplementary data set, Q is dkijAnd d(k-1)ijThe number of data to be supplemented;
step S2.3, Using dkijAnd dkij-lAnd performing original data processing calculation by taking M as the number of data windows to obtain intermediate data for data analysis
Figure BDA0002328908190000031
The calculation formula is as follows:
Figure BDA0002328908190000032
wherein M is less than n;
step S2.4, fitting d by adopting One-dimensional smoothening spline algorithmkijAnd a regular curve between the measurement time span t, wherein the fitting formula is as follows:
Figure BDA0002328908190000033
Figure BDA0002328908190000034
wherein, thetasFor the parameter set to fit the formula f (x), λ is the smooth fit parameter.
Further, the parameter θ in step S2.4sThe determination formula of (1) is as follows:
Figure BDA0002328908190000035
further, in step S3, removing noise interference information in the coercivity measurement result of step S3 specifically includes:
step S3.1, recording the jth measurement result of the ith point of the kth measurement of each Cr-Ni-Fe alloy unit structure in the step S1 as d'kijN, n is the total number of times of measurement, i is 1, 2, 3.. mu.u, u is the total number of points selected by each unit of measurement, and j is 1, 2, 3.. mu.v, v is the total number of coercive force data of each point;
step S3.2, utilizing the measured data to be d'kijAnd d'(k-1)ijInterpolation data for removing noise interference signals are supplemented, and the calculation formula is as follows:
Figure BDA0002328908190000036
wherein, d'kij-lIs the l supplemental data of the k supplemental data set, Q 'is d'kijAnd d'(k-1)ijThe number of interpolation data for removing noise interference signals which need to be supplemented;
step S3.3 of using d'kijAnd d'kij-lAnd performing original data processing calculation by taking M' as the number of data windows to obtain intermediate data for removing noise interference signals
Figure BDA0002328908190000041
The calculation formula is as follows:
Figure BDA0002328908190000042
wherein M' < n.
Step S3.4, realizing d 'by adopting One-dimensional Smoothing spline algorithm'kijSmoothing the curve with the measurement time span t to remove noise interference information, and fitting an algorithm formula such asThe following:
Figure BDA0002328908190000043
Figure BDA0002328908190000044
wherein, thetasFor the parameter set to fit the formula f (x), λ is the smooth fit parameter.
Further, in the step S4, a feature recognition algorithm is used to automatically recognize and judge whether the Cr-Ni-Fe alloy has an early creep damage according to the magnetic signal feature development rule curve of the Cr-Ni-Fe alloy in the step S2, specifically:
calculating an extreme point t of f (t)0The calculation formula is as follows:
Figure BDA0002328908190000045
if the extreme point t is to be determined0Satisfy the formula
Figure BDA0002328908190000046
Judging that the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state of early metastable state rapid development, starting to generate a small amount of independent creep holes, starting to generate creep damage on the material, needing to enlarge the detection range and the detection frequency, and adjusting the detection technology aiming at the creep damage, thereby optimizing the subsequent detection strategy.
Further, in the step S4, a feature recognition algorithm is used to automatically recognize and judge whether the high temperature damage of the Cr-Ni-Fe alloy enters the critical state of the early stage of failure according to the optimized Cr-Ni-Fe alloy magnetic signal feature rule curve in the step S3 in the step S3, specifically:
calculating the extreme point t of f (t)eAnd e 1, 2, 3, a.
Figure BDA0002328908190000051
Will all satisfy
Figure BDA0002328908190000052
Extreme point t ofeIs defined as a vector Te-UAll will be
Figure BDA0002328908190000053
Extreme point t ofeIs defined as a vector Te-U-inverse；
Respectively to vector Te-UAnd Te-U-inverseTo find out
Figure BDA0002328908190000054
And
Figure BDA0002328908190000055
time point t corresponding to the maximum value of (1)e-U-maxAnd te-U-inverse-maxThe calculation formula is as follows:
Figure BDA0002328908190000056
Figure BDA0002328908190000057
wherein the content of the first and second substances,
Figure BDA0002328908190000058
is composed of
Figure BDA0002328908190000059
If t is the inverse ofe-U-inverse-max>te-U-maxJudging that the high-temperature damage of the Cr-Ni-Fe alloy is close to the critical state before failure, beginning to generate creep holes connected into a chain, forming a coarse and large net structure by cementite, seriously embrittling the material, having cracking risk, needing to expand the inspection range, making maintenance and updatingAnd (6) changing the plan.
Compared with the prior art, the invention has the beneficial effects that:
the judging and early warning method provided by the invention can be used for carrying out in-situ detection on the Cr-Ni-Fe alloy element by using the coercive force measuring instrument during short shutdown periods such as blowing, scorching and the like of a production unit under the condition of not damaging a detected unit to obtain the coercive force data information of each detected unit, determining whether the alloy element generates creep damage or not by combining the data processing with the physical characteristics of a U-shaped inflection point of the coercive force of the Cr-Ni-Fe alloy at the early stage of creep damage, and guiding the selection of subsequent inspection technology and inspection range according to the physical characteristics, thereby meeting the requirements of creep early diagnosis and optimization inspection strategy in practical application; meanwhile, noise interference of original data can be eliminated through data processing, so that a coercivity fitting curve at a later stage can obviously present a U-shaped inflection point characteristic signal of early damage of the Cr-Ni-Fe alloy and an inverted U-shaped characteristic signal of a failure critical state in a characteristic manner, the two characteristic signals have obvious time arrangement precedence relationship, whether the alloy element enters the failure critical state can be determined, production personnel can be reminded to make a reasonable maintenance plan or replacement plan in advance, safety risks caused by high-temperature damage failure are reduced to the maximum extent, and the requirements of high-temperature failure critical state diagnosis and maintenance plan alarm reminding in practical application are met.
Drawings
FIG. 1 is a magnetic signal characteristic development law curve of Cr-Ni-Fe alloy;
FIG. 2 is a curve of the optimized Cr-Ni-Fe alloy magnetic signal characteristic development rule;
FIG. 3 is a schematic diagram showing the coercivity measurement data curve processing process and comparison of the coercivity measurement data curve processing effect.
Reference numerals: 1-1, early-stage U-shaped coercivity characteristic signals of high-temperature damage; 1-2, Cr-Ni-Fe alloy coercive force development rule curve; 1-3, an inverted U-shaped coercive force characteristic signal in a high-temperature damage failure critical state; 2-1, fitting data supplemented by a data processing algorithm; 2-2, curve fitted to raw data without treatment; 2-3, fitting the data curve after data processing.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
A Cr-Ni-Fe alloy creep damage early stage and failure critical state judgment and early warning method based on magnetic signals is characterized by comprising the following steps:
step S1, carrying out regular in-situ detection on the Cr-Ni-Fe alloy used in the high-temperature environment, and obtaining coercive force measurement data of each period, namely carrying out regular in-situ detection on the Cr-Ni-Fe alloy used in the high-temperature environment for N days, wherein each detection needs to measure m point positions on the unit structure of each Cr-Ni-Fe alloy, and each point position measures k data;
step S2, processing the obtained coercive force measurement data by using a data comprehensive analysis method to obtain a magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy, which specifically comprises the following steps:
step S2.1, recording the j measurement result of the i point of the k measurement of each Cr-Ni-Fe alloy unit structure in the step S1 as dkijN, n is the total number of times of measurement, i is 1, 2, 3.. mu.u, u is the total number of points selected by each unit of measurement, and j is 1, 2, 3.. mu.v, v is the total number of coercive force data of each point;
step S2.2, calculating dkijAnd d(k-1)ijThe calculation formula is as follows:
Figure BDA0002328908190000061
wherein d iskij-lIs the l supplementary data of the k supplementary data set, Q is dkijAnd d(k-1)ijThe number of data to be supplemented;
step S2.3, Using dkijAnd dkij-lAnd performing original data processing calculation by taking M as the number of data windows to obtain intermediate data for data analysis
Figure BDA0002328908190000071
The calculation formula is as follows:
Figure BDA0002328908190000072
wherein M is less than n;
step S2.4, fitting d by adopting One-dimensional smoothening spline algorithmkijAnd a regular curve between the measurement time span t, wherein the fitting formula is as follows:
Figure BDA0002328908190000073
Figure BDA0002328908190000074
wherein, thetasA parameter θ, which is a set of parameters to fit the formula f (x)sIs determined by the formula
Figure BDA0002328908190000075
λ is a smooth fit parameter;
s3, removing noise interference information in the coercivity measurement result of the step S1 to obtain coercivity data which is subjected to noise processing, and processing the obtained coercivity data which is subjected to noise processing by using a data comprehensive analysis method to obtain an optimized Cr-Ni-Fe alloy magnetic signal characteristic rule curve, wherein the method specifically comprises the following steps:
step S3.1, i-th measurement of k-th measurement of the cell structure of each Cr-Ni-Fe alloy in said step S1The jth measurement result of each point is recorded as d'kijN, n is the total number of times of measurement, i is 1, 2, 3.. mu.u, u is the total number of points selected by each unit of measurement, and j is 1, 2, 3.. mu.v, v is the total number of coercive force data of each point;
step S3.2, utilizing the measured data to be d'kijAnd d'(k-1)ijInterpolation data for removing noise interference signals are supplemented, and the calculation formula is as follows:
Figure BDA0002328908190000076
wherein, d'kij-lIs the l supplemental data of the k supplemental data set, Q 'is d'kijAnd d'(k-1)ijThe number of interpolation data for removing noise interference signals which need to be supplemented;
step S3.3 of using d'kijAnd d'kij-lAnd performing original data processing calculation by taking M' as the number of data windows to obtain intermediate data for removing noise interference signals
Figure BDA0002328908190000081
The calculation formula is as follows:
Figure BDA0002328908190000082
wherein M' < n.
Step S3.4, realizing d 'by adopting One-dimensional Smoothing spline algorithm'kijAnd smoothing a curve between the measurement time span t and the curve, removing noise interference information, wherein an algorithm fitting formula is as follows:
Figure BDA0002328908190000083
Figure BDA0002328908190000084
wherein, thetasIs a parameter set of the fitting formula f (x), and λ is a smooth fitting parameter;
step S4, automatically recognizing and judging whether the Cr-Ni-Fe alloy has early creep damage or not by using a characteristic recognition algorithm according to the magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy in step S2 as shown in fig. 1, and if it is judged that the Cr-Ni-Fe alloy has early creep damage, making an early warning prompt that the Cr-Ni-Fe alloy is about to creep, specifically:
calculating an extreme point t of f (t)0The calculation formula is as follows:
Figure BDA0002328908190000085
if the extreme point t is to be determined0Satisfy the formula
Figure BDA0002328908190000086
Judging that the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state of early metastable state rapid development, starting to generate a small amount of independent creep holes, starting to generate creep damage on the material, needing to enlarge the detection range and the detection frequency, and adjusting the detection technology aiming at the creep damage, thereby optimizing the subsequent detection strategy.
According to the optimized Cr-Ni-Fe alloy magnetic signal characteristic law curve in step S3, as shown in fig. 2, it is automatically identified and judged whether the high temperature damage of the Cr-Ni-Fe alloy enters the critical state of the early stage of failure, and if it is judged that the high temperature damage of the Cr-Ni-Fe alloy has entered the critical state of the early stage of failure, an early warning prompt that the Cr-Ni-Fe alloy is about to fail is specifically:
calculating the extreme point t of f (t)eAnd e 1, 2, 3, a.
Figure BDA0002328908190000091
All will beSatisfy the requirement of
Figure BDA0002328908190000092
Extreme point t ofeIs defined as a vector Te-UAll will be
Figure BDA0002328908190000093
Extreme point t ofeIs defined as a vector Te-U-inverse；
Respectively to vector Te-UAnd Te-U-inverseTo find out
Figure BDA0002328908190000094
And
Figure BDA0002328908190000095
time point t corresponding to the maximum value of (1)e-U-maxAnd te-U-inverse-maxThe calculation formula is as follows:
Figure BDA0002328908190000096
Figure BDA0002328908190000097
wherein the content of the first and second substances,
Figure BDA0002328908190000098
is composed of
Figure BDA0002328908190000099
If t is the inverse ofe-U-inverse-max>te-U-maxAnd judging that the high-temperature damage of the Cr-Ni-Fe alloy is close to the critical state before failure, starting to generate creep holes connected into a chain, forming a coarse and large net structure by cementite, seriously embrittling the material, having cracking risk, needing to expand the inspection range, and making a maintenance and replacement plan.
Example 2
When the Cr-Ni-Fe alloy is damaged at high temperature, the coercive force of the Cr-Ni-Fe alloy is changed from a gradual reduction to a gradual increase inflection point when a cementite crystal boundary becomes coarse and large, and meanwhile, more holes are concentrated on the coarse crystal boundary, so that fewer and relatively independent creep holes are generated, which is the characteristic of the early stage of creep damage, when the coercive force data is large enough in time dimension and sampling quantity, the characteristic inflection point can be identified through a reasonable data processing method, the early magnetic signal characteristic of the creep damage is identified, and finally, the active control of the creep damage risk is realized through adjusting a later inspection detection strategy. The method and the device realize that whether the alloy element is subjected to creep damage or not is determined by the in-situ coercive force of the Cr-Ni-Fe alloy element under the condition of not damaging the detected unit, and the selection of the subsequent inspection technology and the inspection range is guided by the in-situ coercive force, so that early creep diagnosis and risk early warning are realized.
As shown in fig. 1 and 3, carrying out coercivity in-situ detection with a period of f on a Cr-Ni-Fe alloy element used in a high-temperature environment by using a coercivity measuring instrument, and obtaining coercivity measurement data dij at different time points ti; simulating and supplementing the coercive force data 2-2 between two sampling intervals by utilizing ti and dij in combination with a data processing algorithm, and analyzing through logarithm of a mathematical curve fitting algorithm to accurately determine a coercive force change curve 2-3, so that a characteristic inflection point 1-1 of early damage of creep is reserved, and an interference inflection point in an original data curve 2-2 is eliminated; aiming at a coercivity fitting rule curve 1-2 after data processing, a data analysis algorithm is utilized to determine a U-shaped characteristic inflection point, if the U-shaped inflection point exists, the alloy element is judged to enter an early stage of creep damage, so that creep risk early warning is realized, the optimization of a follow-up inspection strategy and range is guided, and data between two coercivity detections are supplemented:
step 1, carrying out regular in-situ coercive force measurement on a Cr-Ni-Fe alloy material to be measured for N days, measuring m point positions of each unit (such as a furnace tube) in each measurement, and measuring k data of each point position;
step 2, the j-th measurement result of the i-th point measured by the unit at the k-th time is dkij, wherein k is 1, 2, 3.. n, wherein n is the total number of measurements, i is 1, 2, 3.. u, wherein u is the total number of the measured points selected by each unit for each measurement, and j is 1, 2, 3.. v, wherein v is the total number of the coercive force data of each measured point;
step 3, calculating dkijAnd d(k-1)ijThe complementary data in between, as shown in formula (1), wherein dkij-l is the l-th complementary data of the k-th group of complementary data, and Q is the number of the complementary data needed between dkij and d (k-1) ij;
Figure BDA0002328908190000101
2. obtaining a characteristic development rule of the alloy material magnetic signal after data processing;
step 1, using dkijAnd dkij-lAnd performing original data processing by taking M as the number of data windows to obtain intermediate data for data analysis
Figure BDA0002328908190000102
Wherein M is less than n, as shown in formula (2);
Figure BDA0002328908190000103
and 2, fitting a regular curve between dkij and the measurement time span t by adopting an One-dimensional Smoothing spline algorithm, wherein fitting formulas are shown as formulas (3) and (4), wherein theta is a parameter set of a fitting formula f (x), and lambda is a smooth fitting parameter, and the equation for determining the parameters is shown as a formula (5).
Figure BDA0002328908190000104
Figure BDA0002328908190000105
Figure BDA0002328908190000111
3. And identifying and judging whether the early creep damage of the Cr-Ni-Fe alloy occurs or not.
Step 1, solving an extreme point t0 of f (t) by using a formula (6);
Figure BDA0002328908190000112
step 2, if t corresponding to the extreme point corresponds to0If the formula (7) is satisfied, judging that the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state of early metastable state rapid development, starting to generate a small amount of independent creep holes, starting to generate creep damage on the material, needing to enlarge the detection range and the detection frequency, and adjusting the detection technology aiming at the creep damage, thereby optimizing the subsequent detection strategy;
Figure BDA0002328908190000113
the embodiment of the invention provides an in-situ early diagnosis and early warning method for creep damage of a petroleum and petrochemical Cr-Ni-Fe alloy material without damaging a tested element. In order to meet the requirements of quickly and early identifying and diagnosing creep damage of the Cr-Ni-Fe alloy material, the method discloses an online detection technology for automatically identifying and diagnosing early characteristics of creep based on magnetic signal (coercive force) in-situ detection data by a mathematical algorithm. The method utilizes regular coercive force in-situ detection data and obtains coercive force measurement data at different time points; then, carrying out data processing on the measurement time and the coercivity to simulate and supplement the coercivity data between two sampling intervals, and carrying out curve fitting by using the simulated data and the original data so as to eliminate interference signals in the original data and simultaneously reserve creep early damage characteristic signals; and finally, determining a U-shaped characteristic inflection point of the coercivity fitting rule curve subjected to data processing by using a data analysis algorithm, and if the U-shaped inflection point exists, judging that the alloy element enters an early stage of creep damage, so that creep risk early warning is realized, and optimization of a follow-up inspection strategy and range is guided.
Example 3
When Cr-Ni-Fe alloy is damaged at high temperature, the coercive force of the Cr-Ni-Fe alloy is continuously depleted, the U-shaped change process of a secondary cementite which is firstly reduced and then increased occurs at the early stage due to continuous depletion of Cr elements in the crystal, and the U-shaped change process of gradually reduced coercive force from continuous growth occurs at the later stage of defect development due to continuous deepening of depletion of Cr elements in the crystal, growth of the secondary cementite (weakened pinning) and continuous accumulation and growth of creep holes, so that a reticular crystal boundary is formed at the crystal boundary, namely, the failure critical state, and the reverse U-shaped change process of gradually reduced coercive force occurs, and the reverse U-shaped change process and the early U-shaped characteristic signal form an obvious time sequence, therefore, when the coercive force data is large enough in time dimension and sampling quantity, the two characteristic inflection points can be identified by a reasonable data processing method, therefore, the characteristic signal of the failure critical state is identified, and the alarm is given in advance to remind the production personnel to make targeted detection, maintenance and replacement plans as soon as possible and in time. The invention realizes that whether the alloy element enters a failure critical state or not is determined by the in-situ correcting and resisting force of the Cr-Ni-Fe alloy element under the condition of not damaging the detected unit, and production personnel are reminded to make a targeted detection, maintenance and replacement plan in time, thereby realizing early warning and effective control of high-temperature damage failure.
As shown in fig. 2 and 3, carrying out coercivity in-situ detection with a period of f on a Cr-Ni-Fe alloy element used in a high-temperature environment by using a coercivity measuring instrument, and obtaining coercivity measurement data dij at different time points ti; simulating and supplementing the coercive force data 2-2 between two sampling intervals by utilizing ti and dij in combination with a data processing algorithm, and analyzing by using a logarithm of a mathematical curve fitting algorithm to accurately determine a coercive force change curve 2-3, so that an early characteristic inflection point 1-1 and a failure critical state inflection point 1-3 of high-temperature damage are reserved, and simultaneously an interference signal (inflection point) in an original data curve 2-2 is eliminated; aiming at a coercivity fitting rule curve 1-2 after data processing, determining time te values corresponding to all extreme points by using a data analysis algorithm, defining the te value corresponding to the maximum value of the U-shaped characteristic inflection point change rate as te-U-max, defining the te value corresponding to the maximum value of the inverted U-shaped characteristic inflection point change rate as te-U-inverse-max, and judging that the alloy element enters a failure critical state if the te-U-inverse-max is greater than the te-U-max, thereby alarming in advance to remind production personnel to make targeted detection, maintenance and replacement plans as soon as possible and in time:
carrying out regular coercivity in-situ detection to obtain coercivity measurement data with different running times;
step 1, carrying out regular in-situ coercivity measurement on a Cr-Ni-Fe alloy material to be measured for N days, and measuring k data of m points of each point for each unit (such as a furnace tube) each time;
step 2, the j-th measurement result of the i-th point measured by the unit at the k-th time is dkij, wherein k is 1, 2, 3.. n, wherein n is the total number of measurements, i is 1, 2, 3.. u, wherein u is the total number of the measured points selected by each unit for each measurement, and j is 1, 2, 3.. v, wherein v is the total number of the coercive force data of each measured point;
2. supplementing data between two coercivity detections;
step 1, calculating d'kijAnd d'(k-1)ijThe complementary data in (c) is shown as formula (1), wherein d'kij-lIs the l supplemental data of the k supplemental data group, Q is d'kijAnd d'(k-1)ijThe number of the supplementary data required in the period;
Figure BDA0002328908190000121
3. processing the supplemented coercivity measurement data by adopting an optimization fitting algorithm to obtain a coercivity optimization fitting curve for removing noise interference;
step 1, using d'kijAnd d'kij-lAnd performing original data processing by taking M' as the number of data windows to obtain intermediate data for data analysis
Figure BDA0002328908190000131
Wherein M' is less than n, as shown in formula (2);
Figure BDA0002328908190000132
step 2, adopting One-dimensional Smoothing spline algorithm to fit d'kijThe fitting formula of the regular curve between the measured time span t and the measured time span is shown in the formulas (3) and (4), wherein thetasThe equation for fitting the parameter set of the formula f (x) and λ is the smooth fitting parameter, and determining the parameter is shown in formula (5).
Figure BDA0002328908190000133
Figure BDA0002328908190000134
Figure BDA0002328908190000135
4. Automatically identifying and judging whether the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state of a failure early stage by using a characteristic identification algorithm;
step 1, solving an extreme point te of f (t) by using a formula (6), wherein e is 1, 2, 3,. the.
Figure BDA0002328908190000136
Step 2, if all extreme points satisfying the formula (7) are defined as a vector Te-U, and all extreme points satisfying the formula (8) are defined as a vector Te-U-inverse;
Figure BDA0002328908190000137
Figure BDA0002328908190000138
step 3, respectively solving vectors Te-U and Te-U-inverse
Figure BDA0002328908190000139
And
Figure BDA00023289081900001310
the maximum values of (a) are corresponding to time points te-U-max and te-U-inverse-max, as shown in equations (9) and (10), where
Figure BDA00023289081900001311
Is composed of
Figure BDA00023289081900001312
If te-U-inverse-max>te-U-max, judging that the high-temperature damage of the Cr-Ni-Fe alloy is close to the critical state before failure, starting to generate chain-shaped creep holes, forming a coarse net structure by cementite, severely embrittling the material, having the risk of cracking, needing to expand the inspection range, and making a maintenance and replacement plan;
Figure BDA0002328908190000141
Figure BDA0002328908190000142
the embodiment of the invention provides a method for diagnosing and early warning a petroleum and petrochemical Cr-Ni-Fe alloy material high-temperature damage in-situ failure critical state without damaging a tested element. In order to meet the requirement of rapidly identifying and diagnosing whether the high-temperature damage of the Cr-Ni-Fe alloy material is close to the failure critical state, the method discloses an online detection technology for automatically identifying and diagnosing the characteristics of the failure critical state of the high-temperature damage based on magnetic signal (coercive force) in-situ detection data and by a mathematical algorithm. The method is characterized in that the measured element is not damaged, and belongs to an in-situ detection technology, and the method utilizes regular coercivity in-situ detection data and obtains coercivity measurement data at different time points; then, carrying out data processing on the measurement time and the coercive force so as to simulate and supplement the coercive force data between two sampling intervals, thereby eliminating interference signals in the original data and simultaneously keeping characteristic signals of high-temperature damage early stage and failure critical state; then, obtaining an optimized coercive force change fitting curve by using simulation data and original data and adopting an optimization fitting algorithm; and finally, finding out the detection time te-U-max corresponding to the maximum value of the change rate of the U-shaped characteristic inflection point and the detection time te-U-inverse-max corresponding to the maximum value of the change rate of the inverted U-shaped characteristic inflection point aiming at the coercivity change curve after optimization, judging that the alloy element enters a failure critical state if the te-U-inverse-max is greater than the te-U-max, and giving an alarm so as to warn production personnel to make targeted detection, maintenance and replacement plans as early as possible and in time.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (7)

1. A Cr-Ni-Fe alloy creep damage early stage and failure critical state judgment and early warning method based on magnetic signals is characterized by comprising the following steps:
step S1, carrying out regular coercivity in-situ detection on the Cr-Ni-Fe alloy used in the high-temperature environment, and obtaining coercivity measurement data of each period;
step S2, processing the obtained coercive force measurement data by using a data comprehensive analysis method to obtain a magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy;
s3, removing noise interference information in the coercivity measurement result of the step S1 to obtain coercivity data which is subjected to noise processing, and processing the obtained coercivity data which is subjected to noise processing by using a data comprehensive analysis method to obtain an optimized Cr-Ni-Fe alloy magnetic signal characteristic rule curve;
and step S4, automatically recognizing and judging whether the Cr-Ni-Fe alloy has early creep damage or not according to the magnetic signal characteristic development rule curve of the Cr-Ni-Fe alloy in the step S2 by using a characteristic recognition algorithm, if judging that the Cr-Ni-Fe alloy has early creep damage, giving an early warning prompt that the Cr-Ni-Fe alloy is about to creep, automatically recognizing and judging whether the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state before failure or not according to the optimized Cr-Ni-Fe alloy magnetic signal characteristic rule curve in the step S3, and if judging that the high-temperature damage of the Cr-Ni-Fe alloy enters a critical state before failure, giving an early warning that the Cr-Ni-Fe alloy is about to fail.
2. The method for judging and warning the early creep damage and the failure critical state of the Cr-Ni-Fe alloy based on the magnetic signal as claimed in claim 1, wherein the step S1 specifically comprises:
carrying out regular in-situ coercive force in-situ detection on the Cr-Ni-Fe alloy used in a high-temperature environment for N days, wherein m point positions are required to be measured for the unit structure of each Cr-Ni-Fe alloy in each detection, and k data are measured for each point position.
3. The method for judging and warning the early creep damage and the critical failure state of the Cr-Ni-Fe alloy based on the magnetic signal as claimed in claim 2, wherein the step S2 specifically comprises:
step S2.1, recording the j measurement result of the i point of the k measurement of each Cr-Ni-Fe alloy unit structure in the step S1 as dkijN, n is the total number of times of measurement, i is 1, 2, 3.. mu.u, u is the total number of points selected by each unit of measurement, and j is 1, 2, 3.. mu.v, v is the total number of coercive force data of each point;
step S2.2, calculating dkijAnd d(k-1)ijComplementary data, calculationThe formula is as follows:
Figure FDA0003502772550000021
wherein d iskij-lIs the l supplementary data of the k supplementary data set, Q is dkijAnd d(k-1)ijThe number of the supplementary data required in the period;
step S2.3, Using dkijAnd dkij-lAnd performing original data processing calculation by taking M as the number of data windows to obtain intermediate data for data analysis
Figure FDA0003502772550000022
The calculation formula is as follows:
Figure FDA0003502772550000023
wherein M is less than n;
step S2.4, fitting d by adopting One-dimensional smoothening spline algorithmkijAnd a regular curve between the measurement time span t, wherein the fitting formula is as follows:
Figure FDA0003502772550000024
Figure FDA0003502772550000025
wherein, thetasFor the parameter set to fit the formula f (x), λ is the smooth fit parameter.
4. The method for determining and warning the early creep damage and the critical failure state of Cr-Ni-Fe alloy based on magnetic signals as claimed in claim 3, wherein the parameter θ in the step S2.4sThe determination formula of (1) is as follows:
Figure FDA0003502772550000026
5. the method for determining and warning early creep damage and critical failure states of Cr-Ni-Fe alloy according to claim 1, wherein in step S3, removing noise interference information in the coercivity measurement result of step S3 includes:
step S3.1, recording the jth measurement result of the ith point of the kth measurement of each Cr-Ni-Fe alloy unit structure in the step S1 as d'kijN, n is the total number of times of measurement, i is 1, 2, 3.. mu.u, u is the total number of points selected by each unit of measurement, and j is 1, 2, 3.. mu.v, v is the total number of coercive force data of each point;
step S3.2, utilizing the measured data to be d'kijAnd d'(k-1)ijInterpolation data for removing noise interference signals are supplemented, and the calculation formula is as follows:
Figure FDA0003502772550000031
wherein, d'kij-lIs the first supplemental data of the kth set of supplemental data, Q 'is d'kijAnd d'(k-1)ijThe number of interpolation data for removing noise interference signals which need to be supplemented;
step S3.3 of using d'kijAnd d'kij-lAnd performing original data processing calculation by taking M' as the number of data windows to obtain intermediate data for removing noise interference signals
Figure FDA0003502772550000032
The calculation formula is as follows:
Figure FDA0003502772550000033
wherein M' < n;
step S3.4, realizing d 'by adopting One-dimensional Smoothing spline algorithm'kijAnd smoothing a curve between the measurement time span t and the measurement time span t to remove noise interference information, wherein an algorithm fitting formula is as follows:
Figure FDA0003502772550000034
Figure FDA0003502772550000035
wherein, thetasFor the parameter set to fit the formula f (x), λ is the smooth fit parameter.
6. The method as claimed in claim 1, wherein in step S4, a feature recognition algorithm is used to automatically recognize and determine whether the Cr-Ni-Fe alloy has the early creep damage according to the magnetic signal feature development rule curve of the Cr-Ni-Fe alloy in step S2, specifically:
calculating an extreme point t of f (t)0The calculation formula is as follows:
Figure FDA0003502772550000036
if the extreme point t is to be determined0Satisfy the formula
Figure FDA0003502772550000037
Judging that the high-temperature damage of the Cr-Ni-Fe alloy enters the critical state of early metastable state rapid development, a small amount of independent creep holes begin to appear, the material begins to creep damage, and extensive inspection is neededMeasuring range and frequency, and adjusting detection technology aiming at creep damage, thereby optimizing subsequent detection strategy.
7. The method for judging and warning the early creep damage and the failure critical state of the Cr-Ni-Fe alloy based on the magnetic signal as claimed in claim 1, wherein in the step S4, a feature recognition algorithm is used to automatically recognize and judge whether the high temperature damage of the Cr-Ni-Fe alloy enters the failure early critical state according to the optimized magnetic signal feature rule curve of the Cr-Ni-Fe alloy in the step S3, and the method comprises the following specific steps:
calculating the extreme point t of f (t)eAnd e 1, 2, 3, a.
Figure FDA0003502772550000041
Will all satisfy
Figure FDA0003502772550000042
Extreme point t ofeIs defined as a vector Te-UAll will be
Figure FDA0003502772550000043
Extreme point t ofeIs defined as a vector Te-U-inverse；
Respectively to vector Te-UAnd Te-U-inverseTo find out
Figure FDA0003502772550000044
And
Figure FDA0003502772550000045
time point t corresponding to the maximum value of (1)e-U-maxAnd te-U-inverse-maxThe calculation formula is as follows:
Figure FDA0003502772550000046
Figure FDA0003502772550000047
wherein the content of the first and second substances,
Figure FDA0003502772550000048
is composed of
Figure FDA0003502772550000049
Is the inverse function of (f), if te-U-inverse-max>te-U-maxAnd judging that the high-temperature damage of the Cr-Ni-Fe alloy is close to the critical state before failure, creep holes connected into a chain form begin to appear, cementite forms a coarse and large net structure, the material is seriously embrittled, the cracking risk exists, the inspection range needs to be expanded, and a maintenance and replacement plan is made.
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