State supervision and life evaluation method based on minimally invasive technology

Abstract

The invention provides a state supervision and life evaluation method based on a minimally invasive technology, and belongs to the technical field of intelligent evaluation, and the method comprises the steps: carrying out the periodic minimally invasive sampling at a key part of target equipment based on a minimally invasive sampling machine, and obtaining a plurality of first samples; performing a multi-dimensional performance test on each first sample, controlling a pre-deployed sensor to periodically collect and monitor operation data of target equipment, and determining a first state of the target equipment in a corresponding period in combination with start-stop times; determining a first service life of the corresponding key part in the corresponding period according to the first state and the original state in the same period in combination with a performance test result; and based on the service life set of each key part and the determined latest service life of the key part, obtaining a service life danger value of the target equipment, and carrying out early warning reminding. Through the combination of the two modes, the accuracy of life determination is ensured, and the evaluation error is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power plant equipment detection, and particularly to a condition monitoring and life assessment method based on minimally invasive technology. Background Art

[0002] During the operation of a thermal power plant, its equipment is in a harsh environment of high temperature, high pressure, high corrosion, etc. for a long time, and the material properties of the equipment will gradually change, which will affect the safe and stable operation of the equipment and its service life. Accurately grasping the state of thermal power plant equipment and scientifically evaluating its life is of crucial significance for ensuring the safe operation of thermal power plants, reducing operating costs, and improving power generation efficiency. There are many drawbacks in traditional thermal power plant equipment detection and life assessment methods. For example, some methods require large-scale disassembly or pipe cutting and sampling of equipment, which not only consumes a large amount of manpower, material resources and time, but also causes great damage to the equipment and affects the subsequent normal operation of the equipment. Moreover, the data obtained by traditional methods is limited and it is difficult to comprehensively and accurately reflect the true state of the equipment material, resulting in inaccurate equipment condition monitoring and large errors in life assessment.

[0003] Therefore, the present invention proposes a condition monitoring and life assessment method based on minimally invasive technology. Summary of the Invention

[0004] The present invention provides a condition monitoring and life assessment method based on minimally invasive technology to solve the problems of large equipment detection damage, incomplete data acquisition, inaccurate condition monitoring and large life assessment errors existing in the prior art.

[0005] The present invention proposes a condition monitoring and life assessment method based on minimally invasive technology, including: Step 1: Periodically perform minimally invasive sampling on key parts of the target equipment based on a minimally invasive sampling machine to obtain a number of first samples; Step 2: Perform multi-dimensional performance tests on each first sample, where the multi-dimensional performance tests include: material mechanical property tests, microstructure analysis, and physical property detection; Step 3: Control pre-deployed sensors to periodically collect and monitor the operation data of the target equipment, and determine the first state of the target equipment in the corresponding period in combination with the start-stop times; Step 4: Determine 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: Based on the life set of each key part and the latest life of the determined key part, obtain the life risk value of the target equipment and give an early warning reminder.

[0006] Preferably, the key parts are the pipe elbow parts and weld parts of the target equipment; The number of sample blocks taken by minimally invasive sampling for each key part is at least 3.

[0007] Preferably, microstructural analysis is performed on each first sample, including: Determine the number of sample blocks in the first sample, and observe each sample block separately using a scanning electron microscope to obtain corresponding microstructural diagrams; Based on the contour structure of each grain in the microstructural diagram, determine the first difference degree, and construct a difference set corresponding to the first sample;

[0008]

[0009] Among them, represents the first difference degree based on the i-th microstructural diagram; represents the number of grains involved in the i-th microstructural diagram; represents the j-th grain in the i-th microstructural diagram and the original grain similarity function; represents the position comparison influence factor between the sample block of the i-th microstructural diagram and the target equipment, 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 sorting result of the position comparison influence factor between each sample block in the corresponding first sample and the target equipment, draw a curve for the difference set, and correct the first variance of the difference set to obtain the second variance; According to the second variance and combined with the corresponding difference set, obtain the micro-combination test result.

[0010] Preferably, correcting the first variance of the difference set to obtain the second variance includes: Perform linear fitting analysis on the drawn curve to obtain the intermediate value of the fitting line; Correct the first variance according to the intermediate value to obtain the second variance.

[0011]

[0012] Among them, represents the corresponding second variance; represents the corresponding first variance; represents the variance based on the difference set and combined with the intermediate value; represents the variance threshold, and the value is 0.08.

[0013] Preferably, determining the first state of the target device in a corresponding period includes: Obtaining the operation data in each period and performing data standardization. Meanwhile, obtaining the number of start-stop times within the corresponding period; When the number of start-stop times within the corresponding period is 0, perform the first calculation; When the number of start-stop times within the corresponding period is 1, perform the second calculation; When the number of start-stop times within the corresponding period is greater than 1, perform the third calculation, where represents the state function based on the total number of start-stop times before the current period and the influence factor of each start on the lifespan , and , represents the standard state at the factory time, with a value of 1; represents the number of operation indicators existing in the corresponding period; represents the judgment function of the h-th operation indicator, and , represents the standard operation range of the h-th operation indicator, ; represents the factorial symbol; represents the number of start-stop times within the corresponding period; represents the influence quantity of all start-stop times and equipment failures resulting in stop operations within the corresponding period ; represents the standardized operation value of the h-th operation indicator; Match the first state consistent with the calculation result from the result-state comparison table.

[0014] Preferably, determining the influence quantity includes: , represents a preset quantity, with a value of 1 / 3.

[0015] Preferably, determining the first lifespan of the corresponding key part in the corresponding period includes: Matching the lifespan analysis model from the model database according to the part type of the key part; Inputting the first state, the original state, and the corresponding performance test results into the lifespan analysis model in sequence to obtain the first lifespan of the corresponding key part.

[0016] Preferably, obtaining the lifespan risk value of the target device based on the lifespan set of each key part and the latest lifespan of the determined key part includes: Subtract the adjacent two values in the life concentration of each key part, obtain the attenuation set and conduct discrete analysis. If the result of the discrete analysis shows that there are no discrete points in the attenuation set, at this time, it is determined that the life attenuation law is satisfied, and the latest life of the corresponding key part is retained; Otherwise, it is determined that the life attenuation law is not satisfied, and the first quantity of discrete points above the analysis curve and the second quantity of discrete points below the analysis curve during the discrete analysis process are counted; According to the ratio of the first quantity to the second quantity, determine the life attenuation increase coefficient, and combine it with the corresponding latest life to obtain and retain the reference life of the corresponding key part; Based on all the retained lives and combined with the part weights of the corresponding key parts, obtain the final life of the target device; If the final life is greater than the set life threshold under all start-stop times before the current moment, it is determined that the life risk value is 0; Otherwise, determine the life risk value according to the final life and the set life threshold.

[0017] Compared with the prior art, the beneficial effects of the present application are as follows: Sampling based on the minimally invasive sampling machine avoids damage to the equipment, and through periodic sampling of key parts, the comprehensiveness of data acquisition can be ensured. Furthermore, by combining sensors to monitor the operating data of the equipment, the reliability of status supervision can be guaranteed. Finally, by combining the two methods, the accuracy of life determination is ensured, and the evaluation error is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a flowchart of the state supervision and life assessment method based on minimally invasive technology provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0021] The present invention provides a method for condition monitoring and life assessment based on minimally invasive technology, as Figure 1 shown, including: Step 1: Periodically perform minimally invasive sampling on key parts of the target device using a minimally invasive sampling machine to obtain a number of first samples; Step 2: Conduct multi-dimensional performance tests on each first sample. Among them, the multi-dimensional performance tests include: material mechanics performance tests, microstructure analysis, and physical property detection; Step 3: Control the pre-deployed sensors to periodically collect and monitor the operating data of the target device, and combine the start-stop times to determine the first state of the target device in the corresponding period; Step 4: According to the first state and the original state in the same period, and combined with the performance test results, determine the first life of the corresponding key part in the corresponding period; Step 5: Based on the life set of each key part and the latest life of the determined key part, obtain the life risk value of the target device and give a warning reminder.

[0022] Preferably, the key parts are the pipe elbow parts and weld parts of the target device; The number of sample blocks for each minimally invasive sampling of each key part is at least 3.

[0023] In this embodiment, the minimally invasive sampling machine can obtain micro-specimens of the device material with extremely small incisions. For example, for devices such as boiler pipes, micro-specimen blocks with a thickness of only 0.5 mm - 1 mm can be obtained, minimizing the damage to the device body to the greatest extent while ensuring the representativeness of the obtained specimens.

[0024] In this embodiment, the material mechanics performance test is carried out through micro-tensile tests, micro-creep fracture tests, etc. to obtain parameters such as the strength, toughness, and creep performance of the material, and judge whether the mechanical properties of the material meet the operating requirements of the device. For example, record that the yield strength of the boiler pipe material is [X] MPa, the tensile strength is [Y] MPa, and the creep deformation rate is within the normal range.

[0025] The microstructure analysis is to observe the microstructure morphology of the micro-specimen using equipment such as a scanning electron microscope (SEM), determine the tissue composition of the material, and analyze whether there are microstructure changes such as aging and spheroidization in the material.

[0026] In this embodiment, the physical property detection is to use non-destructive testing means, such as ultrasonic testing, X-ray testing, etc., to detect the internal defect conditions of the micro-specimen; at the same time, measure physical property parameters such as the hardness and resistance of the specimen, and infer the change of the material performance based on the change of these parameters.

[0027] In this embodiment, the operating data includes parameters such as temperature, pressure, vibration, and rotational speed.

[0028] In this embodiment, the number of starts and stops needs to be counted for each cycle, and the total number of starts and stops from the start of use to the present also needs to be counted. Before leaving the factory, each device will particularly estimate the service life (original state) and the amount of life attenuation because there will definitely be wear and tear during the operation of the device, and thus there will be life attenuation. The life set contains the test results of each key part in different cycles. It should be noted that different indicators are only measured once in each cycle.

[0029] The beneficial effects of the above technical solution are as follows: Sampling based on the minimally invasive sampling machine avoids damaging the device, and by periodically sampling key parts, the comprehensiveness of data acquisition can be ensured. Furthermore, by combining sensors to monitor the operating data of the device, the reliability of condition monitoring can be guaranteed. Finally, by combining the two methods, the accuracy of life determination is ensured, and the evaluation error is reduced.

[0030] The present invention proposes a condition monitoring and life assessment method based on minimally invasive technology, which performs microscopic tissue analysis on each first sample, including: Determine the number of sample blocks in the first sample, and use a scanning electron microscope to observe each sample block separately to obtain corresponding microscopic tissue images; Based on the contour structure of each grain in the microscopic tissue image, determine the first difference degree, and construct a difference set corresponding to the first sample;

[0031]

[0032] Wherein, represents the first difference degree based on the i-th microscopic tissue image; represents the number of grains involved in the i-th microscopic tissue image; represents the j-th grain in the i-th microscopic tissue image and the original grain similarity function; represents the position comparison influence factor between the sample block of the i-th microscopic tissue image 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 sorting result of the position comparison influence factors of each sample block in the corresponding first sample with respect to the target device, draw a curve for the difference set, and correct the first variance of the difference set to obtain a second variance; According to the second variance and in combination with the corresponding difference set, obtain the microscopic combined test result.

[0033] In this embodiment, the value of the number of sample blocks is 3. In this embodiment, the original crystal grains refer to those at the time when the device is put into use after leaving the factory, that is, the crystal grains in the original state, which are used as a reference.

[0034] In this embodiment, if the corresponding part is more affected by the impact of the device, the corresponding value is larger. For example, if the vibration impact is very large, at this time, the value is 0.1. That is, for the part where the sample block is located, the influence factor generated by the corresponding part is set in advance.

[0035] In this embodiment, the microscopic combination test results include the second variance and the difference set of the corresponding samples.

[0036] The beneficial effect of the above technical solution is that a microscope is used to observe each sample block to obtain a microscopic structure diagram, and then a difference set is constructed through comparative analysis with the standard crystal grains, and correction is achieved by combining the drawing of curves, ensuring the theoretical reliability of the test results.

[0037] The present invention proposes a state supervision and life assessment method based on minimally invasive technology, which corrects the first variance of the difference set to obtain a second variance, including: Performing linear fitting analysis on the drawn curve to obtain the intermediate value of the fitting line; Correcting the first variance according to the intermediate value to obtain the second variance.

[0038]

[0039] Among them, represents the corresponding second variance; represents the corresponding first variance; represents the variance based on the difference set and combined with the intermediate value; represents the variance threshold, and the value is 0.08.

[0040] The beneficial effect of the above technical solution is that the intermediate value is obtained through fitting, and the second variance is obtained by combining three variances.

[0041] The present invention proposes a state supervision and life assessment method based on minimally invasive technology, which determines the first state of the target device in the corresponding cycle, including: Obtaining the operation data in each cycle and performing data standardization. At the same time, obtaining the number of start-stop times in the corresponding cycle; When the number of start-stop times in the corresponding cycle is 0, perform the first calculation according to ; When the number of start-stop times in the corresponding cycle is 1, perform the second calculation according to ; When the number of start-stop cycles in the corresponding period is greater than 1, perform the third calculation according to where represents the total number of start-stop cycles before the current period and the impact factor of each start on the lifespan is the state function of, and , represents the standard state at the factory time, with a value of 1; represents the number of operating indicators existing in the corresponding period; represents the judgment function of the h-th operating indicator, and , represents the standard operating range of the h-th operating indicator, ; represents the factorial symbol; represents the number of start-stop cycles in the corresponding period; represents the total number of stops caused by all start-stop cycles and equipment failures involved in the corresponding period is the impact quantity; represents the standardized operating value of the h-th operating indicator; Match the first state consistent with the calculation result from the result-state comparison table.

[0042] Preferably, determining the impact quantity includes: , represents a preset quantity, with a value of 1 / 3.

[0043] In this embodiment, the result-state comparison includes different calculated values and the final state matching this value, mainly the lifespan state.

[0044] In this embodiment, has a value of 0.005 years / cycle.

[0045] The beneficial effects of the above technical solution are: facilitating mathematical calculations through data standardization, and ensuring the reliability of state calculations by performing different calculations on the number of start-stop cycles existing in the period, thereby obtaining the first state.

[0046] The present invention proposes a state supervision and lifespan evaluation method based on minimally invasive technology, determining the first lifespan of the corresponding key part in the corresponding period, including: Matching the lifespan analysis model from the model database according to the part type of the key part; Inputting the first state, the original state, and the corresponding performance test results into the lifespan analysis model in sequence to obtain the first lifespan of the corresponding key part.

[0047] In this embodiment, the part types are classified for key parts according to their functions, structural characteristics, etc. For example, boiler pipes can be classified into part types such as straight pipe sections, elbows, and welds; steam turbine components can be classified into rotating components (such as rotors, blades) and stationary components (such as cylinders, diaphragms), etc. Taking a boiler as an example, the elbow of a high-temperature superheater pipe belongs to the type of "pipe elbow", while the weld connecting the pipes belongs to the type of "weld".

[0048] In this embodiment, the model database stores a database of life analysis models established under various conditions such as different part types, different material properties, and different operating conditions. These models are constructed through the accumulation and analysis of a large amount of experimental data, theoretical research, and actual operating data. For example, the model database may store life analysis models for boiler pipe elbows made of different steels within different temperature and pressure ranges, and life analysis models for steam turbine blades made of different alloy materials under different rotational speeds and load conditions.

[0049] In this embodiment, for example, for the life analysis model of boiler pipes, factors such as the creep characteristics of the pipe material, the accumulation of fatigue damage, and the influence of temperature and pressure on material properties may be comprehensively considered, and a series of mathematical formulas and algorithms are used to calculate the remaining safe operating time of the pipe in the current state. For the life analysis model of steam turbine blades, the fatigue life of the blade material under alternating stress may be focused on, and parameters such as the vibration condition and temperature field distribution of the blade are combined to predict the remaining life of the blade.

[0050] In this embodiment, after calculation by the life analysis model, the predicted value of the remaining service life of the key parts of the equipment under the current operating conditions and state is the first life. For example, the first life of a key part of a certain boiler pipe is obtained as 8 years.

[0051] The beneficial effects of the above technical solution are: Retrieving a matching model from the model database facilitates targeted analysis and improves the analysis efficiency, thereby obtaining a reasonable first life.

[0052] The present invention proposes a state supervision and life assessment method based on minimally invasive technology. Based on the life set of each key part and the latest life of the determined key part, a life risk value of the target equipment is obtained, including: Subtract two adjacent values in the life set of each key part to obtain an attenuation set and perform discrete analysis. If the discrete analysis result shows that there are no discrete points in the attenuation set, at this time, it is determined that the life attenuation law is satisfied, and the latest life of the corresponding key part is retained; Otherwise, it is determined that the life attenuation law is not satisfied, and the first quantity of discrete points above the analysis curve and the second quantity of discrete points below the analysis curve during the discrete analysis process are counted; Determine the life attenuation increase coefficient according to the ratio of the first quantity to the sum of the first quantity and the second quantity, and combine it with the corresponding latest life to obtain and retain the reference life of the corresponding key part; Based on all the retained lives and combined with the part weights of the corresponding key parts, obtain the final life of the target device; If the final life is greater than the set life threshold under all start-stop times before the current moment, determine that the life risk value is 0; Otherwise, determine the life risk value according to the final life and the set life threshold.

[0053] In this embodiment, the set life threshold is, for example, 1 year. If the calculated final life is 0.8 year, at this time, the life risk value is (1 - 0.8) / 1.

[0054] In this embodiment, for example, for part 1, it is evaluated once every quarter, and the obtained life set is {8 years, 7.5 years, 7 years, 6.8 years}. At this time, the obtained attenuation set is {0.5, 0.5, 0.2}; In this embodiment, there are no discrete points: it means that in the chart drawn by discrete analysis, all data points of the attenuation set are within a reasonable error range and are distributed around a certain trend line, and there are no isolated data points that deviate significantly from the trend. For example, in the attenuation set {0.5, 0.5, 0.2} of the above boiler pipe elbow, after plotting the data points, it is found that they are all distributed around a mean line within a small fluctuation range, and there are no prominent abnormal points, which belongs to the situation of no discrete points.

[0055] In this embodiment, the life attenuation law is, for example, for the key parts of thermal power plant equipment, as the operation time increases, its life gradually attenuates uniformly without sudden abnormal changes.

[0056] In this embodiment, in the most recent life assessment, the remaining life value calculated for this key part through the life analysis model is the latest life.

[0057] In this embodiment, when there are discrete points in the attenuation set, it indicates that there are abnormal fluctuations in the life attenuation of the key part, 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 certain key part of a steam turbine blade, subtracting to obtain the attenuation set {0.2, 1.8, - 0.3}, it is found during discrete analysis that the data point 1.8 significantly deviates from the distribution trend of other points, which indicates that this key part of the blade does not meet the life attenuation law.

[0058] In this embodiment, when performing discrete analysis on the attenuation set of the key parts of a thermal power plant equipment, a trend line is drawn. It is found that there are 3 data points significantly above the trend line. Then the first quantity is 3. If there is 1 data point found below the trend line, then the second quantity is 1. At this time, the ratio is: 3 / 4.

[0059] In this embodiment, the reference life = the latest life × (1 - ln(2 + ratio)).

[0060] In this embodiment, the final life = the sum of the reserved lives of the corresponding parts × the weights of the corresponding parts, and the sum of the weights of all parts is 1.

[0061] The beneficial effects of the above technical solution are as follows: By analyzing the attenuation set to determine whether there are discrete points, the required reserved value is determined. Specifically, when there are no discrete points, the original value can be directly reserved. When there are discrete points, the ratio of the set quantity is used to adjust the life. Finally, by comparing with the threshold value, the dangerous value is determined, which is convenient for timely understanding the current life state of the equipment.

[0062] Through the description of the above implementation manners, those skilled in the art can clearly understand that each implementation manner can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the 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 invention.

Claims

1. A state monitoring and life assessment method based on minimally invasive technology, characterized in that, Including: Step 1: Conduct periodic minimally invasive sampling on the key parts of the target device using a minimally invasive sampling machine to obtain a number of first samples; Step 2: Conduct multi-dimensional performance tests on each first sample. Among them, the multi-dimensional performance tests include: material mechanics performance tests, microstructure analysis, and physical property detection; Step 3: Control the pre-deployed sensors to periodically collect and monitor the operation data of the target device, and combine the start-stop times to determine the first state of the target device in the corresponding period; Step 4: Determine 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 combine the performance test results; Step 5: Based on the life set of each key part and the latest life of the determined key part, obtain the life risk value of the target device and give a warning reminder.

2. The state monitoring and life assessment method based on minimally invasive technology according to claim 1, wherein The key parts are the pipe elbow parts and weld parts of the target device; The number of sample blocks for each minimally invasive sampling of each key part is at least 3 blocks.

3. The method for state monitoring and life assessment based on minimally invasive technology according to claim 1, characterized in that Conduct microstructure analysis on each first sample, including: Determine the number of sample blocks in the first sample, and use a scanning electron microscope to observe each sample block respectively to obtain the corresponding microstructure diagram; Based on the contour structure of each grain in the microstructure diagram, determine the first difference degree and construct a difference set corresponding to the first sample; Among them, represents the first difference degree based on the i-th microstructure diagram; represents the number of grains involved in the i-th microstructure diagram; represents the j-th grain in the i-th microstructure diagram and the original grain similarity function; represents the position comparison influence factor between the sample block of the i-th microstructure diagram and the target device, and the value range is (0.01, 0.1); is a constant with a value of 2.7; is a statistical function; According to the sorting result of the influence factor size of the position comparison between each sample block in the corresponding first sample and the target device, draw a curve for the difference set, and correct the first variance of the difference set to obtain the second variance; According to the second variance and combine the corresponding difference set to obtain the microstructure combination test result.

4. The state monitoring and life assessment method based on minimally invasive technology according to claim 3, characterized in that Correct the first variance of the difference set to obtain the second variance, including: Conduct linear fitting analysis on the drawn curve to obtain the intermediate value of the fitting line; Correct the first variance according to the intermediate value to obtain the second variance; Among them, represents the corresponding second variance; represents the corresponding first variance; represents the variance based on the difference set and combined with the median value; represents the variance threshold, with a value of 0.

08.

5. The state monitoring and life assessment method based on minimally invasive technology according to claim 1, characterized in that Determine the first state of the target device in the corresponding period, including: Obtain the operation data in each period and conduct data standardization. At the same time, obtain the start-stop times in the corresponding period; When the number of start / stop times within the corresponding period is 0, perform the first calculation according to ; When the number of start / stop times within the corresponding period is 1, perform the second calculation according to ; When the number of start-stop operations within the corresponding period is greater than 1, calculate according to for the third calculation, where represents the total number of start-stop operations before the current period and the impact factor of each start on the lifespan of the state function, and , represents the standard state at the factory time, with a value of 1; represents the number of operating indicators existing in the corresponding period; represents the judgment function of the h-th operating indicator, and , represents the standard operating range of the h-th operating indicator, ; represents the factorial symbol; represents the number of start-stop operations within the corresponding period; represents the total number of stop operations caused by all start-stop operations and equipment failures involved within the corresponding period of the impact quantity; represents the standardized operating value of the h-th operating indicator; Match the first state consistent with the calculation result from the result-state comparison table.

6. The state monitoring and life assessment method based on minimally invasive technology according to claim 5, characterized in that Determine the influence quantity, including: , represents a preset amount, with a value of 1 / 3.

7. The state monitoring and life assessment method based on minimally invasive technology according to claim 1, characterized in that Determine the first life of the corresponding key part in the corresponding period, including: Match the life analysis model from the model database according to the part type of the key part; Input the first state, the original state, and the corresponding performance test results into the life analysis model in sequence to obtain the first life of the corresponding key part.

8. The state monitoring and life assessment method based on minimally invasive technology according to claim 1, characterized in that Based on the life set of each key part and the latest life of the determined key part, obtain the life risk value of the target device, including: Subtract two adjacent values in the life set of each key part to obtain an attenuation set and conduct discrete analysis. If the discrete analysis result shows that there are no discrete points in the attenuation set, at this time, it is determined that the life attenuation 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 quantity of discrete points above the analysis curve and the second quantity of discrete points below the analysis curve during the discrete analysis process are counted; According to the ratio of the first quantity to the second quantity, a life decay increase coefficient is determined, and combined with the corresponding latest life, the reference life of the corresponding key part is obtained and retained; Based on all the retained lives and combined with the part weights of the corresponding key parts, the final life of the target device is obtained; If the final life is greater than the set life threshold at all start-stop times before the current moment, the life risk value is determined to be 0; Otherwise, the life risk value is determined according to the final life and the set life threshold.

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