Condition monitoring and life assessment method based on minimally invasive technique

Abstract

The application provides a state supervision and life evaluation method based on minimally invasive technology, and belongs to the technical field of intelligent evaluation, and comprises the following steps: periodically performing minimally invasive sampling on key parts of a target device based on a minimally invasive sampling machine to obtain a plurality of first samples; performing multi-dimensional performance testing on each first sample, controlling a pre-deployed sensor to periodically collect and monitor operation data of the target device, and combining the number of start-stop times to determine a first state of the target device in a corresponding period; determining a first life of a corresponding key part in a corresponding period according to the first state and an original state in the same period and combining the performance testing result; obtaining a life risk value of the target device based on a life set of each key part and the latest life of the determined key part, and performing early warning and reminding. The combination of the two methods ensures the accuracy of life determination and reduces the evaluation error.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power plant equipment detection technology, and in particular to a state supervision and life assessment method based on minimally invasive technology. BACKGROUND

[0002] During the operation of a thermal power plant, the equipment is subjected to harsh environments such as high temperature, high pressure, and high corrosion for a long time. The material properties of the equipment gradually change, which affects the safe and stable operation of the equipment and its service life. Accurately grasping the state of the equipment in the thermal power plant and scientifically assessing its life are of great significance for ensuring the safe operation of the thermal power plant, reducing operating costs, and improving power generation efficiency.

[0003] Traditional methods of detecting and assessing the life of thermal power plant equipment have many drawbacks. For example, some methods require large-scale disassembly or pipe cutting for sampling, which not only consumes a lot of manpower, material resources, and time, but also causes significant damage to the equipment, affecting the normal operation of the equipment. Moreover, the data obtained by traditional methods are limited, making it difficult to accurately reflect the true state of the equipment material, resulting in inaccurate equipment state supervision and large errors in life assessment.

[0004] Therefore, the present application proposes a state supervision and life assessment method based on minimally invasive technology. SUMMARY

[0005] The present application provides a state supervision and life assessment method based on minimally invasive technology to solve the problems of large equipment detection damage, incomplete data acquisition, inaccurate state supervision, and large life assessment errors in the prior art.

[0006] The present application proposes a state supervision and life assessment method based on minimally invasive technology, comprising:

[0007] Step 1: Periodically sampling minimally invasive sampling machines at key positions of the target equipment to obtain a plurality of first samples;

[0008] Step 2: Perform multi-dimensional performance testing on each first sample, wherein the multi-dimensional performance testing includes material mechanics performance testing, microstructure analysis, and physical performance detection;

[0009] Step 3: Control the pre-deployed sensors to periodically collect and monitor the operating data of the target equipment, and determine the first state of the target equipment in the corresponding period in combination with the number of starts and stops;

[0010] Step 4: Determine the first life of the corresponding key position in the corresponding period based on the first state and the original state in the same period, and in combination with the performance test results;

[0011] Step 5: Based on the lifespan set of each critical component and the latest lifespan of the determined critical components, obtain the lifespan hazard value of the target equipment and issue an early warning.

[0012] Preferably, the key parts are the pipe bends and welds of the target equipment;

[0013] At least three samples should be taken from each key area using minimally invasive techniques.

[0014] Preferably, microstructural analysis is performed on each first sample, including:

[0015] The number of sample blocks in the first sample was determined, and each sample block was observed using a scanning electron microscope to obtain the corresponding microstructure diagram;

[0016] Based on the outline structure of each grain in the microstructure diagram, a first degree of difference is determined, and a difference set corresponding to the first sample is constructed.

[0017]

[0018]

[0019] in, This represents the first degree of difference based on the i-th microstructure diagram; This represents the number of grains involved in the i-th microstructure diagram; This represents the j-th grain in the i-th microstructure diagram. With the original grain The similarity function; The positional comparison factor between the sample block of the i-th microstructure map and the target equipment is represented, with a value range of (0.01, 0.1). It is a constant, with a value of 2.7; It is a statistical function;

[0020] Based on the ranking of the influence factors of the position of each sample block in the first sample relative to the target device, the difference set is plotted as a curve, and the first variance of the difference set is corrected to obtain the second variance;

[0021] Based on the second variance and the corresponding difference set, the micro-combination test results are obtained.

[0022] Preferably, the first variance of the difference set is corrected to obtain the second variance, including:

[0023] Perform a linear fitting analysis on the plotted curve to obtain the median value of the fitted line;

[0024] The first variance is corrected based on the intermediate value to obtain the second variance.

[0025]

[0026] in, This represents the corresponding second variance; This represents the corresponding first variance; This represents the variance based on the difference set and incorporating the median value. This represents the variance threshold, with a value of 0.08.

[0027] Preferably, determining the first state of the target device in the corresponding period includes:

[0028] Acquire the running data for each cycle and standardize the data. At the same time, obtain the number of start-stop cycles within the corresponding cycle.

[0029] When the number of start-stop cycles in the corresponding period is 0, according to Perform the first calculation;

[0030] When the number of start-stop cycles in the corresponding period is 1, according to Perform the second calculation;

[0031] When the number of start-stop cycles within the corresponding period is greater than 1, according to Perform the third calculation, in which, This indicates the total number of starts and stops prior to the current cycle. And the factors affecting lifespan each start-up The state function, and , This indicates the standard state at the time of manufacture, and its value is 1. This indicates the number of operating indicators that exist in the corresponding period; Let h represent the judgment function for the h-th operating indicator, and , This represents the standard operating range of the h-th operating indicator. ; Represents the factorial symbol; This indicates the number of starts and stops within the corresponding period; This indicates the total number of starts, shutdowns, and equipment failures that caused downtime within the corresponding period. The number of impacts; This represents the standardized operating value of the h-th operating indicator;

[0032] The first state that matches the calculation result is obtained by matching the result-state lookup table.

[0033] Preferably, the quantity of influence is determined, including:

[0034] , represents a preset quantity, and takes a value of 1 / 3.

[0035] Preferably, determining the first life of the corresponding key part in the corresponding period comprises:

[0036] matching a life analysis model from a model database according to the part type of the key part;

[0037] inputting the first state, the original state and the corresponding performance test result into the life analysis model in sequence to obtain the first life of the corresponding key part.

[0038] Preferably, based on the life set of each key part and the determined latest life of the key part, the life risk value of the target device is obtained, comprising:

[0039] subtracting two adjacent values in the life set of each key part to obtain a decay set and perform discrete analysis, if the discrete analysis result is that there is no discrete point in the decay set, at this time, it is determined that the life decay law is satisfied, and the latest life of the corresponding key part is retained;

[0040] otherwise, it is determined that the life decay law is not satisfied, and a first number of discrete points above the analysis curve and a second number of discrete points below the analysis curve in the discrete analysis process are counted;

[0041] determining a life decay increase coefficient according to the ratio of the first number and the second number, and obtaining a reference life of the corresponding key part combined with the corresponding latest life and retaining;

[0042] based on all the retained lives and combined with the part weight of the corresponding key part, obtaining the final life of the target device;

[0043] if the final life is greater than the set life threshold value under all start-stop times before the current time, determining that the life risk value is 0;

[0044] otherwise, determining the life risk value according to the final life and the set life threshold value.

[0045] Compared with the prior art, the beneficial effects of the present application are as follows:

[0046] Based on the minimally invasive sampling machine for sampling to avoid damage to the device, and by periodically sampling the key parts, the comprehensiveness of data acquisition can be ensured, and then the running data of the device is monitored by the sensor to ensure the reliability of state supervision, and finally the combination of the two ways ensures the accuracy of life determination, and reduces the evaluation error. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings described below are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0048] Figure 1 is a flowchart of the state supervision and life assessment method based on minimally invasive technology provided by the embodiments of the present application. DETAILED DESCRIPTION

[0049] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0050] The present application provides a state supervision and life assessment method based on minimally invasive technology, as shown in Figure 1 , comprising:

[0051] Step 1: periodically sampling minimally invasively at key parts of the target equipment based on a minimally invasive sampling machine to obtain a plurality of first samples;

[0052] Step 2: performing multi-dimensional performance testing on each first sample, wherein the multi-dimensional performance testing includes material mechanical performance testing, microstructure analysis and physical performance detection;

[0053] Step 3: controlling a pre-deployed sensor to periodically collect and monitor operation data of the target equipment, and combining the number of starts and stops to determine a first state of the target equipment in a corresponding period;

[0054] Step 4: determining a first life of the corresponding key part in the corresponding period according to the first state and the original state in the same period, and combining the performance test results;

[0055] Step 5: obtaining a life risk value of the target equipment based on the life set of each key part and the determined latest life of the key part, and performing early warning and reminding.

[0056] Preferably, the key parts are pipe elbow parts and weld parts of the target equipment.

[0057] The number of sample blocks for each key part to be sampled minimally invasively is at least 3.

[0058] In this embodiment, the minimally invasive sampling machine can obtain a micro sample of the equipment material with a very small wound, for example, for the equipment such as a boiler pipe, a micro sample with a thickness of only 0.5mm-1mm can be obtained, the damage to the equipment body is minimized, and the obtained sample is representative.

[0059] In this embodiment, the material mechanical property test is performed by a micro tensile test, a micro creep fracture test, and the like, to obtain parameters such as strength, toughness, and creep performance of the material, and to determine whether the mechanical properties of the material meet the equipment operation requirements, for example, the yield strength of the boiler pipe material is recorded as [X] MPa, the tensile strength is [Y] MPa, and the creep deformation rate is within a normal range.

[0060] Microstructure analysis is performed by using a scanning electron microscope (SEM) and the like to observe the microstructure of the micro sample, to determine the material organization composition, and to analyze whether the material has microstructure changes such as aging and spheroidization.

[0061] In this embodiment, the physical property detection is performed by using non-destructive testing methods such as ultrasonic testing, X-ray testing, and the like, to detect internal defects of the micro sample; at the same time, the hardness, resistance, and other physical performance parameters of the sample are measured, and the changes of the material performance are inferred according to the changes of these parameters.

[0062] In this embodiment, the operation data include parameters such as temperature, pressure, vibration, and rotation speed.

[0063] In this embodiment, the start-stop times are counted in each cycle, and the total start-stop times from the beginning of use to the present are also counted. Each equipment has a particularly estimated use mission (original state) and life attenuation before leaving the factory. Since the equipment is definitely damaged during operation, the life attenuation exists. The life set contains the test results of each key position in different cycles. It should be noted that each index is measured only once in each cycle.

[0064] The beneficial effects of the above technical solution are: based on the minimally invasive sampling machine, the sampling avoids damage to the equipment, and by periodically sampling the key positions, the comprehensiveness of data acquisition can be ensured, and then the running data of the equipment are monitored by the sensor to ensure the reliability of the state supervision, and finally the combination of the two ways ensures the accuracy of the life determination and reduces the evaluation error.

[0065] The present application provides a state supervision and life evaluation method based on minimally invasive technology, which performs microstructure analysis on each first sample, including:

[0066] The number of sample blocks in the first sample is determined, and a scanning electron microscope is used to observe each sample block to obtain a corresponding microstructure diagram;

[0067] Based on the contour structure of each grain in the microstructure map, a first difference degree is determined, and a difference set corresponding to the first sample is constructed;

[0068]

[0069]

[0070] wherein, represents the first difference degree based on the i-th microstructure map; represents the number of grains involved in the i-th microstructure map; represents the similarity function of the j-th grain in the i-th microstructure map with the original grain; represents the position comparison impact factor of the sample block of the i-th microstructure map with the target device, and the value range is (0.01, 0.1); is a constant, and the value is 2.7; is a statistical function;

[0071] According to the size of the position comparison impact factor of each sample block in the corresponding first sample with the target device, the difference set is curve-drawn, and the first variance of the difference set is corrected to obtain the second variance.

[0072] According to the second variance and in combination with the corresponding difference set, a micro-combination test result is obtained.

[0073] In this embodiment, the value of the number of sample blocks is 3.

[0074] In this embodiment, the original grain refers to the grain when the device is put into use, that is, the grain in the original state, which is used as a reference.

[0075] In this embodiment, the greater the impact of the corresponding part receiving the device impact, the greater the corresponding value, for example, receiving a large vibration impact, at this time, the value is 0.1, that is, the sample block is located in which part, and the impact factor of the corresponding part is set in advance.

[0076] In this embodiment, the micro-combination test result includes the second variance and the difference set of the corresponding sample.

[0077] The beneficial effects of the above technical solution are: a microscope is used to observe each sample block to obtain a microstructure map, and then a difference set is constructed by comparative analysis with a standard grain, and correction is realized by curve drawing, thereby ensuring the theoretical reliability of the test result.

[0078] ​​The application provides a state supervision and life evaluation method based on a minimally invasive technique, a first variance of the difference set is corrected to obtain a second variance, and the second variance comprises:

[0079] A straight line fitting analysis is performed on the drawn curve to obtain a middle value of the fitting straight line.

[0080] The first variance is corrected according to the middle value to obtain the second variance.

[0081]

[0082] wherein, represents the corresponding second variance; represents the corresponding first variance; represents a variance based on the difference set and combined with the middle value; represents a variance threshold, and the value is 0.08.

[0083] The beneficial effects of the above technical solution are that the middle value is obtained through fitting, and the second variance is obtained in combination with three variances.

[0084] The application provides a state supervision and life evaluation method based on a minimally invasive technique, a first state of the target device in a corresponding period is determined, and the method comprises the following steps:

[0085] Running data in each period is obtained and data standardization is performed, and meanwhile, the number of start-stop times in the corresponding period is obtained;

[0086] When the number of start-stop times in the corresponding period is 0, first calculation is performed according to ;

[0087] When the number of start-stop times in the corresponding period is 1, second calculation is performed according to ;

[0088] When the number of start-stop times in the corresponding period is greater than 1, third calculation is performed according to , wherein, represents a state function based on the total number of start-stop times before the current period and an influence factor of life of each start , and , represents a standard state at a factory time, and the value is 1; represents the number of running indexes existing in the corresponding period; represents a judgment function of the hth running index, and , represents a standard running range of the hth running index, ; represents a factorial symbol; represents the number of start-stop in the corresponding period; represents the number of all start-stop and the number of stop caused by equipment failure in the corresponding period ; represents the normalized running value of the hth running index;

[0089] The first state consistent with the calculation result is matched from the result-state table.

[0090] Preferably, the number of influences is determined, including:

[0091] , represents a preset amount, and the value is 1 / 3.

[0092] In this embodiment, the result-state table contains different calculation values and the last state matched with the value, mainly the life state.

[0093] In this embodiment, The value of is 0.005 years / time.

[0094] The beneficial effects of the above technical solutions are: the data is standardized for mathematical calculation, and the number of start-stop in the period is calculated in different cases to ensure the reliability of state calculation, so as to obtain the first state.

[0095] The present application provides a state supervision and life evaluation method based on minimally invasive technology, which determines the first life of the corresponding key part in the corresponding period, including:

[0096] According to the part type of the key part, a life analysis model is matched from a model database;

[0097] The first state, the original state and the corresponding performance test result are input into the life analysis model in sequence to obtain the first life of the corresponding key part.

[0098] In this embodiment, the part type is classified according to the function, structural characteristics and the like of the key part. For example, the boiler pipeline can be divided into straight pipe section, elbow, weld and the like; the steam turbine components can be divided into rotating components (such as rotor, blade), static components (such as cylinder, partition) and the like. Taking the boiler as an example, the elbow of the high-temperature superheater pipeline belongs to the “pipeline elbow” type, and the weld connecting the pipeline belongs to the “weld” type.

[0099] In this embodiment, the model database stores a plurality of life analysis models established under different conditions of different part types, different material properties, and different operating conditions. These models are constructed through a large amount of experimental data, theoretical research, and actual operation data accumulation and analysis. For example, the model database can store life analysis models for boiler pipe bends made of different steel materials under different temperature and pressure ranges, and life analysis models for turbine blade made of different alloy materials under different rotating speed and load conditions.

[0100] In this embodiment, for example, the life analysis model for the boiler pipe can comprehensively consider the creep characteristics of the pipe material, the fatigue damage accumulation, the influence of temperature and pressure on the material properties, and other factors, and calculate the safe operation time of the pipe under the current state through a series of mathematical formulas and algorithms. For the life analysis model of the turbine blade, the fatigue life of the blade material under alternating stress can be focused on, and the vibration condition and temperature field distribution of the blade can be combined to predict the remaining life of the blade.

[0101] In this embodiment, after the life analysis model is calculated, the remaining life prediction value of the key part of the equipment under the current operating condition and state is the first life, for example, the first life of the key part of the boiler pipe is 8 years.

[0102] The beneficial effects of the above technical solution are: retrieving the matching model from the model database facilitates targeted analysis and improves analysis efficiency, and then a reasonable first life is obtained.

[0103] The present application proposes a state supervision and life evaluation method based on minimally invasive technology, based on the life set of each key part and the determined latest life of the key part, the life risk value of the target equipment is obtained, including:

[0104] The adjacent two values in the life set of each key part are calculated by subtraction, and the decay set is obtained and discrete analysis is performed, if the discrete analysis result is that there is no discrete point in the decay set, at this time, it is determined that the life decay law is satisfied, and the latest life of the corresponding key part is retained;

[0105] Otherwise, it is determined that the life decay law is not satisfied, and the first number of discrete points above the analysis curve and the second number of discrete points below the analysis curve in the discrete analysis process are counted;

[0106] According to the ratio of the first number to the sum of the first number and the second number, the life decay increase coefficient is determined, and the reference life of the corresponding key part is obtained combined with the corresponding latest life and retained;

[0107] Based on all the retained lives and combined with the part weight of the corresponding key part, the final life of the target equipment is obtained.

[0108] If the final life is greater than the set life threshold value under all start-stop times before the current time, the life risk value is determined to be 0;

[0109] Otherwise, the life risk value is determined according to the final life and the set life threshold value.

[0110] In this embodiment, the set life threshold value is, for example, 1 year, and if the calculated final life is 0.8 years, then the life risk value is (1-0.8) / 1.

[0111] In this embodiment, for example, the key part 1 is evaluated every quarter, and the obtained life set is {8 years, 7.5 years, 7 years, 6.8 years}, and the obtained attenuation set is {0.5, 0.5, 0.2}.

[0112] In this embodiment, there is no discrete point: meaning that in the chart drawn by the discrete analysis, all data points of the attenuation set are within a reasonable error range, distributed around a certain trend line, and there is no isolated data point that deviates from the trend. For example, in the attenuation set {0.5, 0.5, 0.2} of the boiler pipe elbow mentioned above, it is found that after drawing the data points, they are distributed around a mean line within a small fluctuation range, and there is no outstanding abnormal point, which belongs to the case of no discrete point.

[0113] In this embodiment, the life attenuation law is, for example, that the key part of the thermal power plant equipment gradually and uniformly attenuates with the increase of the running time, without sudden abnormal changes.

[0114] In this embodiment, in the last life evaluation, the residual life value calculated by the life analysis model for the key part is the latest life.

[0115] In this embodiment, when there is a discrete point in the attenuation set, it means that the life attenuation of the key part has an abnormal fluctuation, which does not conform to the normal and expected attenuation mode. For example, for the life set {5 years, 4.8 years, 3 years, 4.5 years} of a key part of a steam turbine blade, the attenuation set {0.2, 1.8, -0.3} is obtained by subtraction, and it is found that the data point 1.8 deviates from the distribution trend of other points in the discrete analysis, which indicates that the key part of the blade does not meet the life attenuation law.

[0116] In this embodiment, when the attenuation set of a key part of a certain thermal power plant equipment is analyzed discretely, a trend line is drawn, and it is found that there are 3 data points obviously above the trend line, so the first number is 3. If there is 1 data point below the trend line, then the second number is 1, and the ratio is: 3 / 4.

[0117] In this embodiment, the reference life = the latest life x (1-ln(2+ratio)).

[0118] In this embodiment, the final life = the sum of the reserved life of the corresponding part x the weight of the corresponding part, and the sum of the weights of all parts is 1.

[0119] The beneficial effects of the above technical solution are: by analyzing the decay set to determine whether there are discrete points, to determine the required reserved value, specifically, when there is no discrete point value, the original value can be directly reserved, when there is a discrete point, the set number ratio is used to adjust the life, and finally by comparing with the threshold value, to determine the dangerous value, to facilitate timely understanding of the current life state of the equipment.

[0120] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and the necessary general hardware platform, and of course, they can also be realized by hardware. Based on such understanding, the above technical solutions, essentially or in the form of software products, can be embodied in a computer software product, which can be stored in a computer readable storage medium such as ROM / RAM, magnetic disk, optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, server, or network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0121] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for condition monitoring and life assessment based on minimally invasive techniques, characterized in that, The method comprises the following steps: Step 1: periodically performing micro-invasive sampling on key parts of the target equipment by using a micro-invasive sampling machine to obtain a plurality of first samples; Step 2: performing multi-dimensional performance testing on each first sample, wherein the multi-dimensional performance testing comprises material mechanics performance testing, microstructure analysis and physical performance detection; Step 3: periodically collecting and monitoring the running data of the target equipment by using a pre-deployed sensor, and determining the first state of the target equipment in the corresponding period in combination with the number of starts and stops; Step 4: determining the first life of the corresponding key part in the corresponding period according to the first state and the original state in the same period and in combination with the performance test results; Step 5: obtaining the life risk value of the target equipment based on the life set of each key part and the latest life of the determined key part, and performing early warning and reminding; The key parts are pipe elbow parts and weld parts of the target equipment; The number of sample blocks for each key part is at least 3; The microstructure analysis of each first sample comprises: Determining the number of sample blocks in the first sample, and observing each sample block by using a scanning electron microscope to obtain a corresponding microstructure graph; Based on the contour structure of each grain in the microstructure graph, a first difference degree is determined, and a difference set of the corresponding first sample is constructed; wherein, represents the first difference degree based on the i-th microstructure map; represents the number of grains involved in the i-th microstructure map; represents the j-th grain in the i-th microstructure map and the original grain a similarity function; represents the position matching influence factor of the i-th microstructure map and the target device, and the value range is (0.01, 0.1); is a constant, and the value is 2.7; is a statistical function; According to the size sorting result of the position influence factor of each sample block in the corresponding first sample and the target equipment, the difference set is curve-drawn, and the first variance of the difference set is corrected to obtain a second variance; The microstructure combination test result is obtained according to the second variance and in combination with the corresponding difference set; The first state of the target equipment in the corresponding period is determined, comprising: Obtaining the running data in each period and performing data standardization, and simultaneously obtaining the number of starts and stops in the corresponding period; When the number of start-stop times in the corresponding period is 0, the first calculation is performed according to ; When the number of start-stop times in the corresponding period is 1, the second calculation is performed according to ; When the number of start-stop in the corresponding period is greater than 1, the third calculation is performed according to , a state function based on the total number of start-stop before the current period and the impact factor of each start on the life , and , the standard state at the time of factory shipment, taking the value of 1; the number of running indicators existing in the corresponding period; the judgment function of the hth running indicator, and , the standard running range of the hth running indicator, ; the factorial symbol; the number of start-stop in the corresponding period; the number of impacts of all start-stop and the number of stop running caused by equipment failure involved in the corresponding period ; the normalized running value of the hth running indicator; Matching the first state consistent with the calculation result from a result-state matching table; The life risk value of the target equipment is obtained based on the life set of each key part and the latest life of the determined key part, comprising: The adjacent two values in the life set of each key part are subtracted to obtain a decay set and perform discrete analysis, if the discrete analysis result is that there is no discrete point in the decay set, at this time, it is determined that the life decay law is satisfied, and the latest life of the corresponding key part is retained; Otherwise, it is determined that the life decay law is not satisfied, and the first number of discrete points above the analysis curve and the second number of discrete points below the analysis curve in the discrete analysis process are counted; According to the ratio of the first number and the second number, a life decay increase coefficient is determined, and in combination with the corresponding latest life, a reference life of the corresponding key part is obtained and retained; The final life of the target equipment is obtained based on all the retained lives and in combination with the part weight of the corresponding key part; If the final life is greater than the set life threshold value before the current time and all the numbers of starts and stops, it is determined that the life risk value is 0; Otherwise, the life risk value is determined according to the final life and the set life threshold value.

2. The method for condition monitoring and life assessment based on minimally invasive techniques according to claim 1, characterized in that, The first variance of the difference set is corrected to obtain the second variance, comprising: Performing linear fitting analysis on the plotted curve to obtain a middle value of the fitting straight line; According to the middle value, the first variance is corrected to obtain a second variance; wherein, denotes the corresponding second variance; denotes the corresponding first variance; denotes the variance based on the set of differences and in combination with the intermediate value; denotes a variance threshold value, having a value of 0.

08.

3. The method of condition monitoring and life assessment based on minimally invasive techniques according to claim 1, wherein, Determining an influence quantity, comprising: , represents a preset quantity, and has a value of 1 / 3.

4. The method for condition monitoring and life assessment based on minimally invasive techniques according to claim 1, characterized in that, Determining a first life of the corresponding key part in the corresponding period, comprising: According to the part type of the key part, a life analysis model is matched from a model database; The first state, the original state and the corresponding performance test results are sequentially input into the life analysis model to obtain the first life of the corresponding key part.

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