Method for determining evaluation index of spacecraft structure damage on-line and off-line detection capability

Abstract

The invention relates to a spacecraft structure damage on-line and off-line detection capability evaluation index determination method. The invention relates to the technical field of spacecraft structure health monitoring, and aims at identifying spacecraft damage on line, performing off-line detection, identifying a damage position and quantifying a damage degree. The method is suitable for long-term on-orbit and multi-time reciprocating spacecrafts when constructing a spacecraft structure damage off-line detection technical capability evaluation index system, and provides technical support for improving the spacecraft on-orbit damage real-time early warning capability and ground maintenance decision-making efficiency, reducing leak detection risk and maintenance cost, and realizing high-reliability spacecraft design and service life extension.

Description

Technical Field

[0001] The present invention relates to the technical field of spacecraft structural health monitoring, and is a method for determining an evaluation index of off-line detection capability of spacecraft structural damage. Background Art

[0002] Damage status detection of spacecraft is a core technology for ensuring the safety of major projects such as deep space exploration and manned lunar landing. With the widespread application of advanced materials such as composite materials and ceramic insulation tiles in spacecraft, their structural damage has shown characteristics such as multi-source, cross-scale, and highly concealed. At present, damage detection technologies are becoming increasingly diverse, and methods such as online identification and offline detection have been widely used. However, the existing technology evaluation system is fragmented and lacks a systematic detection credibility assessment method. It is difficult to quantify the technical capabilities of online identification and offline detection. On the one hand, this restricts the optimization and iteration of detection technology, and on the other hand, it leads to delayed maintenance decisions or excessive maintenance, which restricts the effectiveness of spacecraft life cycle management. Therefore, it is urgent to establish a detection capability evaluation system that covers the entire damage life cycle and is multi-dimensional and collaborative to solve the problems of fragmentation and low credibility of existing technologies and improve the accuracy, practicality and collaborative effectiveness of detection technologies. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention provides a method for determining evaluation indicators of the offline detection capability of spacecraft structural damage. The present invention aims to construct an evaluation indicator system for the offline detection technical capability of spacecraft structural damage, which is suitable for spacecraft that are in orbit for a long time and make multiple round trips. It provides technical support for improving the real-time early warning capability of spacecraft on-orbit damage and the efficiency of ground maintenance decision-making, reducing the risk of missed detection and maintenance costs, and realizing high-reliability spacecraft design and life extension.

[0004] The present invention provides the following technical solutions:

[0005] A method for determining an evaluation index of an offline detection capability of a spacecraft structure damage comprises the following steps:

[0006] Step 1: Online identification of spacecraft damage. Using the structural response data and load environment obtained from sensor monitoring, the damage location is identified and the damage extent is quantified.

[0007] Step 2: The online damage identification capability is determined by damage detection indicators, damage location indicators, and damage quantification indicators;

[0008] Step 3: Conduct offline testing after the spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, non-destructive testing methods are used to accurately measure the multi-dimensional scale and morphology of the damage.

[0009] Step 4: The offline damage detection capability is determined by the detection accuracy index and the detection practicality index.

[0010] Preferably, the damage detection index in step 2 is specifically:

[0011] The damage detection index characterizes the ability to detect damage of a certain form and degree. It divides the structure approximately evenly into several rule recognition areas and measures it by the detection rate and false alarm rate:

[0012] The detection rate is the ratio of the number of identified areas that are judged to have damage to the number of identified areas that actually have damage, that is,

[0013]

[0014] Among them, N D＝1 is the number of identified areas where damage occurs, N D＝1,ide＝1 The number of identified regions where damage is determined to exist in the sub-region where damage occurs;

[0015] The false alarm rate is the ratio of the number of identified areas that are judged to be damaged to the number of identified areas that are not damaged, that is,

[0016]

[0017] Among them, N D＝0 is the number of identified areas without damage, N D＝0,ide＝1 The number of recognition areas that are judged to be damaged among the recognition areas that are not damaged.

[0018] Preferably, the damage location indicator in step 2 is specifically:

[0019] Damage localization indicators include relative resolution, positioning accuracy, positioning error, and positioning time. The online damage identification area is further divided into several regular positioning sub-areas.

[0020] The relative resolution is the average value of the ratio of the area of ​​the damage localization sub-region to the total area of ​​the damage localization region, that is,

[0021]

[0022] Among them, N D,Net is the number of damage localization sub-regions, S D,part (i) is the area of ​​the i-th sub-region, S D∑ The total area of ​​the damage identification region;

[0023] The positioning accuracy is the ratio of the number of damages successfully located in the positioning sub-area where the damage is located to the actual number of damages, that is,

[0024]

[0025] Among them, n D is the number of damages, n D,right is the number of lesions successfully localized in the sub-region where the lesion is located;

[0026] The positioning error is the distance between the center position of the identified damage and the actual center position of the damage obtained by offline detection, that is,

[0027]

[0028] Among them, x D,pre To identify the x-coordinate and y-coordinate of the damage center D,pre To identify the y coordinate of the damage center, x D,real is the x-coordinate of the actual damage center position obtained by offline detection, and y D,real is the y coordinate of the actual damage center position obtained by offline detection;

[0029] Positioning time t pos It is the time from the initiation of damage to the identification and location of the damage.

[0030] Preferably, the damage quantification index in step 2 is specifically:

[0031] Damage quantification indicators include area quantification relative error, residual strength prediction error and quantification time;

[0032] The relative error of area quantification is the relative error between the damage area quantification identification value and the damage area obtained according to the offline detection result, that is,

[0033]

[0034] Among them, A D,mea A is the quantitative identification value of the damage area. D,con is the damage area obtained based on the offline detection results;

[0035] The residual strength prediction error is the relative error between the residual strength value obtained by progressive damage evolution analysis and the residual strength value obtained by strength testing of damaged structural components, that is,

[0036]

[0037] Among them, S D,mea is the residual strength value obtained through progressive damage evolution analysis, S D,con The residual strength value obtained by strength testing of damaged structural members;

[0038] Quantization time t qua The time required to measure the extent of damage for online monitoring.

[0039] Preferably, the detection accuracy index in step 4 includes:

[0040] Minimum detectable damage size, minimum detectable layer thickness h min , area S min , minimum detectable crack width b min , Minimum detectable crack length L min , minimum detectable crack depth w min ;

[0041] The success rate of key damage detection, the detection rate of short and narrow cracks, and the missed detection rate of through-hole crack damage, including:

[0042] The detection rate is the ratio of the number of detected cracks to the actual number of cracks, that is,

[0043]

[0044] Among them, N cra＝1 is the number of cracks, N cra＝1,ide＝1 To detect the number of cracks;

[0045] The missed detection rate is the ratio of the number of undetected cracks to the actual number of cracks, that is,

[0046]

[0047] Among them, N cra＝1,ide＝0 is the number of undetected cracks;

[0048] Resolution and detection accuracy, including structural shape and size measurement accuracy;

[0049] Repeatability error refers to the consistency of multiple test results for the same injury.

[0050] Preferably, the detection of the practicality index in step 4 includes:

[0051] Response speed, such as the time taken for a single detection T det ;

[0052] Thick wall structure penetration capability, such as the maximum detectable damage depth H max ;

[0053] Complex geometric adaptability, such as accessibility to hidden locations, applicability to curved surfaces, special-shaped structures, and bolt stress concentration areas;

[0054] Cost-effectiveness, such as device power consumption P det ,complexity of detection steps;

[0055] Intrusiveness, such as whether the detection method requires disassembly and whether secondary damage to the structure will be caused by contact.

[0056] Preferably, the method further comprises performing collaborative detection credibility:

[0057] Based on the damage identification capability characterization indicators, the online damage identification method capability is comprehensively evaluated, and the total score is obtained by weighted calculation:

[0058]

[0059] Among them, X D,mea is the number of indicators, λ D,mea (i) is the weight of the i-th indicator, G D,mea (i) is the score of the i-th indicator.

[0060] A system for determining an evaluation index of an offline detection capability of a spacecraft structure damage, the system comprising:

[0061] An online damage identification module, which identifies spacecraft damage online by identifying the damage location and quantifying the damage extent using structural response data and load environment monitored by sensors;

[0062] An online evaluation index determination module, wherein the online damage identification capability of the online evaluation index determination module is determined by a damage detection index, a damage location index, and a damage quantification index;

[0063] An offline damage identification module, which performs offline testing after the spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, the module uses non-destructive testing to accurately measure the multi-dimensional scale and morphology of the damage.

[0064] An offline evaluation index determination module, wherein the damage offline detection capability of the offline evaluation index determination module is determined by a detection accuracy index and a detection practicality index.

[0065] A computer-readable storage medium stores a computer program, which is executed by a processor to implement a method for determining an evaluation index of off-line detection capability of spacecraft structural damage.

[0066] A computer device comprises a memory and a processor, wherein the memory stores a computer program and the processor implements a method for determining an evaluation index of an offline detection capability of spacecraft structural damage when executing the computer program.

[0067] The present invention has the following beneficial effects:

[0068] Compared with the prior art, the present invention has the following advantages:

[0069] The present invention clarifies the reliability boundary of the online monitoring system by quantifying the detection rate, positioning error, quantization accuracy and response speed of online identification.

[0070] This invention combines the minimum detectable damage size, resolution, practicality and other indicators of offline detection to standardize the applicable scenarios and performance shortcomings of ground detection technology.

[0071] The present invention establishes a data closed loop between online and offline detection through comprehensive evaluation of detection credibility, providing a basis for optimizing sensor layout, algorithm iteration, and detection method selection, and promoting the upgrade of damage detection from coarse screening to precise judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0073] Figure 1 Shown is a schematic diagram of the online identification area of ​​the off-line detection technology capability evaluation index system for spacecraft structural damage according to the present invention;

[0074] Figure 2 Shown is a schematic diagram of the framework of the off-line detection technology capability evaluation index system for spacecraft structural damage according to the present invention. DETAILED DESCRIPTION

[0075] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0076] The present invention is described in detail below with reference to specific embodiments. Specific embodiment one:

[0078] according to Figures 1 to 2 As shown, the specific optimization technical solution adopted by the present invention to solve the above technical problems is: the present invention relates to a method for determining an evaluation index of offline detection capability of spacecraft structural damage.

[0079] The present invention provides a method for determining an evaluation index of an offline detection capability of a spacecraft structure damage, the method comprising the following steps:

[0080] Step 1: Online identification of spacecraft damage. Using the structural response data and load environment obtained from sensor monitoring, the damage location is identified and the damage extent is quantified.

[0081] Step 2: The online damage identification capability is determined by damage detection indicators, damage location indicators, and damage quantification indicators;

[0082] Step 3: Conduct offline testing after the spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, non-destructive testing methods are used to accurately measure the multi-dimensional scale and morphology of the damage.

[0083] Step 4: The offline damage detection capability is determined by the detection accuracy index and the detection practicality index. Specific embodiment two:

[0085] The difference between the second embodiment of the present application and the first embodiment is that:

[0086] The damage detection indicators in step 2 are specifically:

[0087] The damage detection index characterizes the ability to detect damage of a certain form and degree. It divides the structure approximately evenly into several rule recognition areas and measures it by the detection rate and false alarm rate:

[0088] The detection rate is the ratio of the number of identified areas that are judged to have damage to the number of identified areas that actually have damage, that is,

[0089]

[0090] Among them, N D＝1 is the number of identified areas where damage occurs, N D＝1,ide＝1 The number of identified regions where damage is determined to exist in the sub-region where damage occurs;

[0091] The false alarm rate is the ratio of the number of identified areas that are judged to be damaged to the number of identified areas that are not damaged, that is,

[0092]

[0093] Among them, N D＝0 is the number of identified areas without damage, N D＝0,ide＝1 The number of recognition areas that are judged to be damaged among the recognition areas that are not damaged. Specific embodiment three:

[0095] The only difference between the third embodiment of the present application and the second embodiment is that:

[0096] The damage location indicators in step 2 are specifically:

[0097] Damage localization indicators include relative resolution, positioning accuracy, positioning error, and positioning time. The online damage identification area is further divided into several regular positioning sub-areas.

[0098] The relative resolution is the average value of the ratio of the area of ​​the damage localization sub-region to the total area of ​​the damage localization region, that is,

[0099]

[0100] Among them, N D,Net is the number of damage localization sub-regions, S D,part (i) is the area of ​​the i-th sub-region, S D∑ The total area of ​​the damage identification region;

[0101] The positioning accuracy is the ratio of the number of damages successfully located in the positioning sub-area where the damage is located to the actual number of damages, that is,

[0102]

[0103] Among them, n D is the number of damages, n D,right is the number of lesions successfully localized in the sub-region where the lesion is located;

[0104] The positioning error is the distance between the center position of the identified damage and the actual center position of the damage obtained by offline detection, that is,

[0105]

[0106] Among them, x D,pre To identify the x-coordinate and y-coordinate of the damage center D,pre To identify the y coordinate of the damage center, x D,real is the x-coordinate of the actual damage center position obtained by offline detection, and y D,real is the y coordinate of the actual damage center position obtained by offline detection;

[0107] Positioning time t pos It is the time from the initiation of damage to the identification and location of the damage. Specific embodiment four:

[0109] The only difference between the fourth embodiment of the present application and the third embodiment is that:

[0110] The damage quantification index in step 2 is specifically:

[0111] Damage quantification indicators include area quantification relative error, residual strength prediction error and quantification time;

[0112] The relative error of area quantification is the relative error between the damage area quantification identification value and the damage area obtained according to the offline detection result, that is,

[0113]

[0114] Among them, AD,mea A is the quantitative identification value of the damage area. D,con is the damage area obtained based on the offline detection results;

[0115] The residual strength prediction error is the relative error between the residual strength value obtained by progressive damage evolution analysis and the residual strength value obtained by strength testing of damaged structural components, that is,

[0116]

[0117] Among them, S D,mea is the residual strength value obtained through progressive damage evolution analysis, S D,con The residual strength value obtained by strength testing of damaged structural members;

[0118] Quantization time t qua The time required to measure the extent of damage for online monitoring. Specific embodiment five:

[0120] The only difference between the fifth embodiment of the present invention and the fourth embodiment is that:

[0121] The detection accuracy index in step 4 includes:

[0122] Minimum detectable damage size, minimum detectable layer thickness h min , area S min , minimum detectable crack width b min , Minimum detectable crack length L min , minimum detectable crack depth w min ;

[0123] The success rate of key damage detection, the detection rate of short and narrow cracks, and the missed detection rate of through-hole crack damage, including:

[0124] The detection rate is the ratio of the number of detected cracks to the actual number of cracks, that is,

[0125]

[0126] Among them, N cra＝1 is the number of cracks, N cra＝1,ide＝1 To detect the number of cracks;

[0127] The missed detection rate is the ratio of the number of undetected cracks to the actual number of cracks, that is,

[0128]

[0129] Among them, N cra＝1,ide＝0 is the number of undetected cracks;

[0130] Resolution and detection accuracy, including structural shape and size measurement accuracy;

[0131] Repeatability error refers to the consistency of multiple test results for the same injury. Specific embodiment six:

[0133] The only difference between the sixth embodiment of the present invention and the fifth embodiment is that:

[0134] The practicality indicators detected in step 4 include:

[0135] Response speed, such as the time taken for a single detection T det ;

[0136] Thick wall structure penetration capability, such as the maximum detectable damage depth H max ;

[0137] Complex geometric adaptability, such as accessibility to hidden locations, applicability to curved surfaces, special-shaped structures, and bolt stress concentration areas;

[0138] Cost-effectiveness, such as device power consumption P det ,complexity of detection steps;

[0139] Intrusiveness, such as whether the detection method requires disassembly and whether secondary damage to the structure will be caused by contact. Specific embodiment seven:

[0141] The only difference between the seventh embodiment of the present invention and the sixth embodiment is that:

[0142] The method further comprises performing collaborative detection credibility:

[0143] Based on the damage identification capability characterization indicators, the online damage identification method capability is comprehensively evaluated, and the total score is obtained by weighted calculation:

[0144]

[0145] Among them, X D,mea is the number of indicators, λ D,mea (i) is the weight of the i-th indicator, G D,mea (i) is the score of the i-th indicator. Specific embodiment eight:

[0147] The only difference between the eighth embodiment of the present invention and the seventh embodiment is that:

[0148] The present invention provides a system for determining an evaluation index of an offline detection capability of a spacecraft structure damage, the system comprising:

[0149] An online damage identification module, which identifies spacecraft damage online by identifying the damage location and quantifying the damage extent using structural response data and load environment monitored by sensors;

[0150] An online evaluation index determination module, wherein the online damage identification capability of the online evaluation index determination module is determined by a damage detection index, a damage location index, and a damage quantification index;

[0151] An offline damage identification module, which performs offline testing after the spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, the module uses non-destructive testing to accurately measure the multi-dimensional scale and morphology of the damage.

[0152] An offline evaluation index determination module, wherein the damage offline detection capability of the offline evaluation index determination module is determined by a detection accuracy index and a detection practicality index. Specific embodiment nine:

[0154] The only difference between the ninth embodiment of the present invention and the eighth embodiment is that:

[0155] The present invention provides a computer-readable storage medium having a computer program stored thereon. The program is executed by a processor to implement a method for determining an evaluation index of an offline detection capability of spacecraft structural damage. Specific embodiment ten:

[0157] The only difference between the tenth embodiment of the present invention and the ninth embodiment is that:

[0158] The present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program and the processor implements a method for determining an evaluation index of an offline detection capability of spacecraft structural damage when executing the computer program. Specific embodiment eleven:

[0160] The only difference between the eleventh embodiment of the present invention and the tenth embodiment is that:

[0161] like Figure 1-Figure 2 As shown in the figure, an evaluation index system for the offline detection technology capability of spacecraft structural damage mainly covers two dimensions: online damage identification and offline damage detection. It is used to evaluate the online and offline damage detection technology capabilities and to guide the detection credibility assessment and iterative upgrade.

[0162] 1. Online damage identification

[0163] Online damage identification is the process of identifying damage locations and quantifying damage severity in spacecraft flight scenarios using structural response data and load conditions monitored by sensors. Online damage identification capabilities are characterized by detection, location, and quantification metrics, demonstrating the reliability and efficiency of the online monitoring system.

[0164] Assessment method: The indicator of online damage identification is obtained by comparing the online identification results with the offline non-destructive testing results.The results are compared to verify.

[0165] (1) Damage detection indicators

[0166] The damage detection index characterizes the ability to detect damage of a certain form and degree. The structure is roughly divided into several regular recognition areas and measured by the detection rate and false alarm rate.

[0167] 1) Detection rate. The detection rate is the ratio of the number of identified areas that are judged to have damage to the number of identified areas that actually have damage, that is,

[0168]

[0169] Among them, N D＝1 is the number of identified areas where damage occurs, N D＝1,ide＝1 The number of identified regions in the damaged sub-region where damage occurs is determined to exist.

[0170] 2) False alarm rate. The false alarm rate is the ratio of the number of identified areas that are judged to be damaged to the number of identified areas that are not damaged, that is,

[0171]

[0172] Among them, N D＝0 is the number of identified areas without damage, N D＝0,ide＝1 The number of recognition areas that are judged to be damaged among the recognition areas that are not damaged.

[0173] (2) Damage location indicators

[0174] The damage localization indicators include relative resolution, localization accuracy, localization error and localization time. The online damage identification area is further divided into several regular localization sub-areas.

[0175] 1) Relative resolution. The relative resolution is the average value of the ratio of the area of ​​the damage localization sub-region to the total area of ​​the damage localization region, that is,

[0176]

[0177] Among them, N D,Net is the number of damage localization sub-regions, S D,part (i) is the area of ​​the i-th sub-region, S D∑ is the total area of ​​the damage identification region.

[0178] 2) Positioning accuracy. The positioning accuracy is the ratio of the number of damages successfully located in the positioning sub-area where the damage is located to the actual number of damages, that is,

[0179]

[0180] Among them, n D is the number of damages, n D,right is the number of lesions successfully located in the sub-region where the lesion is located.

[0181] 3) Positioning error. Positioning error is the distance between the center of the identified damage and the actual center of the damage obtained by offline detection, that is,

[0182]

[0183] Among them, x D,pre To identify the x-coordinate and y-coordinate of the damage center D,pre To identify the y coordinate of the damage center, x D,real is the x-coordinate of the actual damage center position obtained by offline detection, and y D,real is the y coordinate of the actual damage center position obtained by offline detection.

[0184] 4) Positioning time. Positioning time t pos The time from damage initiation to identification and location of the damage is the time between damage initiation and identification and location of the damage. Since the spacecraft must quickly identify damage behavior and respond during its on-orbit flight, location time is a key indicator to characterize the system's response capability.

[0185] (3) Damage quantification index

[0186] Damage quantification indicators include area quantification error, residual strength prediction error and quantification time.

[0187] 1) Area quantification relative error. The area quantification relative error is the relative error between the damage area quantification identification value and the damage area obtained according to the offline detection result, that is,

[0188]

[0189] Among them, A D,mea A is the quantitative identification value of the damage area. D,con is the damage area obtained based on the offline detection results.

[0190] 2) Residual strength prediction error. The residual strength prediction error is the relative error between the residual strength value obtained by progressive damage evolution analysis and the residual strength value obtained by strength testing of damaged structural parts, that is,

[0191]

[0192] Among them, S D,mea is the residual strength value obtained through progressive damage evolution analysis, S D,con It is the residual strength value obtained from the strength test of the damaged structural member.

[0193] 3) Quantization time. Quantization time t qua The time required to measure the extent of damage for online monitoring.

[0194] 2. Offline damage detection

[0195] Offline damage detection involves using nondestructive testing methods after a spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, the damage is accurately measured in multiple dimensions and morphology, providing a basis for subsequent repair and maintenance. Offline damage detection capabilities are characterized by metrics such as accuracy and practicality.

[0196] Assessment method: The indicators of offline damage detection are verified by comparing the results of the detection technology (generally using laser, infrared, ultrasound, etc.) with the results of other detection technologies.

[0197] (1) Detection accuracy index

[0198] 1) Minimum detectable damage size. For example, the minimum detectable layer thickness h min , area S min , minimum detectable crack width b min , Minimum detectable crack length L min , minimum detectable crack depth w min wait.

[0199] 2) Success rate of key damage detection, such as the detection rate of short and narrow cracks, the missed detection rate of through-hole crack damage, etc.

[0200] The detection rate is the ratio of the number of detected cracks to the actual number of cracks, that is,

[0201]

[0202] Among them, N cra＝1 is the number of cracks, N cra＝1,ide＝1 The number of cracks detected.

[0203] The missed detection rate is the ratio of the number of undetected cracks to the actual number of cracks, that is,

[0204]

[0205] where N cra＝1,ide＝0 is the number of undetected cracks.

[0206] 4) Resolution and detection accuracy, such as the measurement accuracy of structural shape and size.

[0207] 5) Repeatability error, such as the consistency of multiple test results for the same damage.

[0208] (2) Detection practicality indicators

[0209] 1) Response speed. For example, a single test takes T det wait.

[0210] 2) Penetration capability of thick wall structures. For example, the maximum detectable damage depth H max wait.

[0211] 3) Adaptability to complex geometries, such as accessibility to hidden locations, and applicability to curved surfaces, special-shaped structures, bolts, and other stress concentration areas.

[0212] 4) Cost-effectiveness. For example, the power consumption of the equipment P det , complexity of detection steps, etc.

[0213] 5) Invasiveness. For example, whether the detection method requires disassembly, whether secondary damage to the structure will occur due to contact, etc.

[0214] 3. Credibility of collaborative testing

[0215] According to the damage identification capability characterization index, the ability of the online damage identification method is comprehensively evaluated, and the total score is obtained by weighted calculation.

[0216]

[0217] Among them, X D,mea is the number of indicators, λ D,mea (i) is the weight of the i-th indicator, G D,mea (i) is the score of the i-th indicator.

[0218] The above is merely a preferred embodiment of a method for determining an evaluation index for the offline detection capability of spacecraft structural damage. The scope of protection for a method for determining an evaluation index for the offline detection capability of spacecraft structural damage is not limited to the aforementioned embodiment; all technical solutions based on this concept fall within the scope of protection of the present invention. It should be noted that improvements and variations that do not depart from the principles of the present invention, as readily apparent to those skilled in the art, should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining evaluation indicators for off-line detection capability of spacecraft structural damage, characterized by: The method comprises the following steps: Step 1: Online identification of spacecraft damage. Using the structural response data and load environment obtained from sensor monitoring, the damage location is identified and the damage extent is quantified. Step 2: The online damage identification capability is determined by damage detection indicators, damage location indicators, and damage quantification indicators; Step 3: Conduct offline testing after the spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, non-destructive testing methods are used to accurately measure the multi-dimensional scale and morphology of the damage. Step 4: The offline damage detection capability is determined by the detection accuracy index and the detection practicality index.

2. The method according to claim 1, wherein: The damage detection indicators in step 2 are specifically: The damage detection index characterizes the ability to detect damage of a certain form and degree. It divides the structure approximately evenly into several rule recognition areas and measures it by the detection rate and false alarm rate: The detection rate is the ratio of the number of identified areas that are judged to have damage to the number of identified areas that actually have damage, that is, Among them, N D＝1 is the number of identified areas where damage occurs, N D＝1,ide＝1 The number of identified regions where damage is determined to exist in the sub-region where damage occurs; The false alarm rate is the ratio of the number of identified areas that are judged to be damaged to the number of identified areas that are not damaged, that is, Among them, N D＝0 is the number of identified areas without damage, N D＝0,ide＝1 The number of recognition areas that are judged to be damaged among the recognition areas that are not damaged.

3. The method according to claim 2, wherein: The damage location indicators in step 2 are specifically: Damage localization indicators include relative resolution, positioning accuracy, positioning error, and positioning time. The online damage identification area is further divided into several regular positioning sub-areas. The relative resolution is the average value of the ratio of the area of ​​the damage localization sub-region to the total area of ​​the damage localization region, that is, Among them, N D,Net is the number of damage localization sub-regions, S D,part (i) is the area of ​​the i-th sub-region, S D∑ The total area of ​​the damage identification region; The positioning accuracy is the ratio of the number of damages successfully located in the positioning sub-area where the damage is located to the actual number of damages, that is, Among them, n D is the number of damages, n D,right is the number of lesions successfully localized in the sub-region where the lesion is located; The positioning error is the distance between the center position of the identified damage and the actual center position of the damage obtained by offline detection, that is, Among them, x D,pre To identify the x-coordinate and y-coordinate of the damage center D,pre To identify the y coordinate of the damage center, x D,real is the x-coordinate of the actual damage center position obtained by offline detection, and y D,real is the y coordinate of the actual damage center position obtained by offline detection; Positioning time t pos It is the time from the initiation of damage to the identification and location of the damage.

4. The method according to claim 3, wherein: The damage quantification index in step 2 is specifically: Damage quantification indicators include area quantification relative error, residual strength prediction error and quantification time; The relative error of area quantification is the relative error between the damage area quantification identification value and the damage area obtained according to the offline detection result, that is, Among them, A D,mea A is the quantitative identification value of the damage area. D,con is the damage area obtained based on the offline detection results; The residual strength prediction error is the relative error between the residual strength value obtained by progressive damage evolution analysis and the residual strength value obtained by strength testing of damaged structural components, that is, Among them, S D,mea is the residual strength value obtained through progressive damage evolution analysis, S D,con The residual strength value obtained by strength testing of damaged structural members; Quantization time t qua The time required to measure the extent of damage for online monitoring.

5. The method according to claim 4, wherein: The detection accuracy index in step 4 includes: Minimum detectable damage size, minimum detectable layer thickness h min , area S min , minimum detectable crack width b min , Minimum detectable crack length L min , minimum detectable crack depth w min ; The success rate of key damage detection, the detection rate of short and narrow cracks, and the missed detection rate of through-hole crack damage, including: The detection rate is the ratio of the number of detected cracks to the actual number of cracks, that is, Among them, N cra＝1 is the number of cracks, N cra＝1,ide＝1 To detect the number of cracks; The missed detection rate is the ratio of the number of undetected cracks to the actual number of cracks, that is, Among them, N cra＝1,ide＝0 is the number of undetected cracks; Resolution and detection accuracy, including structural shape and size measurement accuracy; Repeatability error refers to the consistency of multiple test results for the same injury.

6. The method according to claim 5, wherein: The practicality indicators detected in step 4 include: Response speed, such as the time taken for a single detection T det ; Thick wall structure penetration capability, such as the maximum detectable damage depth H max ; Complex geometric adaptability, such as accessibility to hidden locations, applicability to curved surfaces, special-shaped structures, and bolt stress concentration areas; Cost-effectiveness, such as device power consumption P det ,complexity of detection steps; Intrusiveness, such as whether the detection method requires disassembly and whether secondary damage to the structure will be caused by contact.

7. The method according to claim 4, wherein: The method further comprises performing collaborative detection credibility: Based on the damage identification capability characterization indicators, the online damage identification method capability is comprehensively evaluated, and the total score is obtained by weighted calculation: Among them, X D,mea is the number of indicators, λ D,mea (i) is the weight of the i-th indicator, G D,mea (i) is the score of the i-th indicator.

8. A system for determining evaluation indicators for off-line detection capability of spacecraft structural damage, characterized by: The system comprises: An online damage identification module, which identifies spacecraft damage online by identifying the damage location and quantifying the damage extent using structural response data and load environment monitored by sensors; An online evaluation index determination module, wherein the online damage identification capability of the online evaluation index determination module is determined by a damage detection index, a damage location index, and a damage quantification index; An offline damage identification module, which performs offline testing after the spacecraft returns to Earth. Based on the approximate location and area of ​​damage identified online, the module uses non-destructive testing to accurately measure the multi-dimensional scale and morphology of the damage. An offline evaluation index determination module, wherein the damage offline detection capability of the offline evaluation index determination module is determined by a detection accuracy index and a detection practicality index.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method according to claims 1 to 7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method of claims 1-7 is implemented.

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