An off-line detection device for the health state of a bonding structure of a vehicle and its detection method

Abstract

The present invention discloses an off-line detection device for the health state of a bonding structure of a vehicle, comprising: at least one acceleration sensor, a force sensor, a swept-frequency exciter, an exciter drive module, an acceleration acquisition and conversion module, an exciting force acquisition and conversion module, a main controller and a computer analysis system. The present invention also discloses an off-line detection method for the health state of a bonding structure of a vehicle. The main principle is to first test the dynamic characteristics of the local bonding structure of vehicles, ships, aircraft and other vehicles in a healthy state as the determination criterion for the healthy state, and then regularly detect the dynamic characteristics of the local bonding structure of the vehicle during the service period of the vehicle, and compare them with the dynamic characteristics of the local bonding structure in the healthy state, and judge the health state of the bonding structure according to the change situation.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle safety, and more specifically, the present invention relates to an off-line detection device for the health state of a bonded structure of a vehicle and a detection method thereof. Background Art

[0002] As a new type of connection process, bonding has been increasingly widely used in various modern vehicles with the rapid development of materials science. For example, the front and rear windshields of passenger cars, the windows of highway buses and rail trains, and various composite material components on vehicles and aircraft generally adopt bonding or composite connection processes based on bonding.

[0003] Although bonding as a new type of connection process has a series of unique advantages, most of the current adhesives are polymer materials. The biggest difference from traditional metal materials is that they will age with the accumulation of use time, resulting in varying degrees of decline in various performance indicators. During the service process of vehicles, the failure of the bonded structure at the bonding interface occurs frequently, which has varying degrees of impact on the safe operation of vehicles, especially for high-speed trains, airplanes and other high-speed vehicles, which may cause serious consequences.

[0004] Therefore, there is an urgent need to develop a health monitoring and detection device for bonded structures that can monitor or detect the bonded structures of vehicles in real time or regularly during the service period of vehicles, which is of great significance for ensuring the safe operation of vehicles containing bonded structures. Summary of the Invention

[0005] The object of the present invention is to design and develop an off-line detection device for the health state of a bonded structure of a vehicle, which can realize off-line detection of the health state of the bonded structure of the vehicle during the service period of the vehicle, improve the practicability and achieve non-destructive detection at the same time.

[0006] The present invention also designs and develops an off-line detection method for the health state of a bonded structure of a vehicle. Based on the local dynamic characteristics of the bonded structure, it can realize off-line detection of the health state of the bonded structure of the vehicle without causing any damage to the bonded structure.

[0007] The technical solution provided by the present invention is as follows:

[0008] An off-line detection device for the health state of a bonded structure of a vehicle, comprising:

[0009] At least one acceleration sensor, which is arranged on the bonded structure of the measured vehicle;

[0010] An acceleration acquisition and conversion module, which is connected to the at least one acceleration sensor and is used for signal conversion and operation processing of multiple parameters;

[0011] A frequency-sweeping exciter;

[0012] A force sensor, one end of which is fixed to the excitation head of the frequency-sweeping exciter, and the other end of which is optionally arranged on the bonded structure of the measured vehicle or at least one acceleration sensor;

[0013] An excitation force acquisition and conversion module, which is connected to the force sensor;

[0014] An exciter drive module, which is connected to the frequency-sweeping exciter and is used to provide a frequency-sweeping drive signal for the frequency-sweeping exciter;

[0015] A main controller, which is connected to the acceleration acquisition and conversion module, the excitation force acquisition and conversion module, and the exciter drive module, and is used for signal transmission and instruction issuance;

[0016] A computer analysis system, which is connected to the main controller and is used for data storage and query;

[0017] Wherein, the at least one acceleration sensor is arranged on the bonded structure of the measured vehicle through a magnetic buckle, a non-trace adhesive or a vacuum suction cup.

[0018] Preferably, the at least one acceleration sensor and the force sensor are both side-outlet sensors.

[0019] Preferably, it further includes:

[0020] A buffer member, which is arranged between the force sensor and the bonded structure of the measured vehicle.

[0021] Preferably, the loading method of the frequency-sweeping exciter is hand-held loading or robotic arm loading.

[0022] An off-line detection method for the health state of a vehicle bonded structure, using the off-line detection device for the health state of a vehicle bonded structure, includes the following steps:

[0023] Step 1: Select n reference samples, and select the same m detection points on the n reference samples;

[0024] Step 2: Apply excitations with different frequencies to the detection points separately in sequence, and calculate the amplitude-frequency characteristic data of all detection points on the n reference samples respectively:

[0025] δ ij (f) = U ij (f) / F ij (f);

[0026] In the formula, δ ij (f) is the amplitude-frequency characteristic data of the jth detection point on the ith reference sample, U ij(f) is the variation law of the displacement amplitude of the j-th detection point on the i-th reference sample with the swept frequency f, F ij (f) is the variation law of the excitation load amplitude of the j-th detection point on the i-th reference sample with the swept frequency f, i = 1 to n, j = 1 to m;

[0027] Step 3: Divide the amplitude-frequency characteristic data into m groups according to the detection points. Each group contains the amplitude-frequency characteristic data of n reference samples. Establish m swept frequency coordinate systems, and extract the upper envelope C j (f) and the lower envelope D j (f), and [D j (f) - Δ j , C j (f) + j Δ] is the amplitude-frequency characteristic health interval of the j-th detection point;

[0028] Among them, Δ j is the envelope offset. The swept frequency coordinate system is a two-dimensional rectangular coordinate system, with the abscissa being the swept frequency and the ordinate being the amplitude-frequency characteristic data;

[0029] Step 4: Select the same detection points on the bonded structure of the vehicle in actual application as those on the reference sample, and obtain the real-time amplitude-frequency characteristic data of all detection points:

[0030] If the real-time amplitude-frequency characteristic data of all detection points are within the amplitude-frequency characteristic health interval, the bonded structure of the vehicle is in a healthy state;

[0031] If 0 < x t < 10% x s and Δr k < 10% Δf, there are potential safety hazards in the bonded structure of the vehicle. Shorten the detection period to half of the initial detection period and continue the detection;

[0032] Among them, x t is the number of detection points exceeding the amplitude-frequency characteristic health interval, x s is the total number of detection points, Δr k is the exceeding amplitude of the k-th detection point exceeding the amplitude-frequency characteristic health interval, and Δf is the difference between the upper envelope and the lower envelope of the corresponding swept frequency:

[0033] Δf = D j (f) - C j (f);

[0034] If x t ≥ 10% x s or Δr kIf ≥ 10% Δf, then the adhesive structure of the vehicle is in a situation of failure risk.

[0035] Preferably, the selection of the detection points specifically includes:

[0036] Divide the boundary of the adhesive structure of the vehicle to be measured into straight line segments and curved line segments, select the centroid of the adhesive structure, the midpoint of each straight line segment, and the midpoint of each curved line segment as the detection points, and when the boundary is composed of two or more curved lines, divide each basic curve into one segment and then select the detection points.

[0037] Preferably, the envelope line offset satisfies:

[0038]

[0039] In the formula, n f is the design safety factor, n l is the risk factor after failure, l = 1 to 5, n c is the maintenance cost factor, n g is the confidence level of the experimental data of the reference sample.

[0040] Preferably, the risk factor after failure satisfies:

[0041] n1 = 0.8 to 1;

[0042] n2 = 0.6 to 0.8;

[0043] n3 = 0.4 to 0.6;

[0044] n4 = 0.2 to 0.4;

[0045] n5 = 0.0 to 0.2;

[0046] Among them, n1 is the highest risk level, n2 is the high risk level, n3 is the medium risk level, n4 is the low risk level, and n5 is the risk-free level.

[0047] Preferably, the maintenance cost factor satisfies:

[0048] When ω > 10% z, n c = 1.0;

[0049] When ω ≤ 10% z,

[0050] In the formula, w is the maintenance cost and z is the total price of the equipment.

[0051] The beneficial effects of the present invention:

[0052] (1). An off-line detection device for the health state of a bonding structure of a vehicle, which is designed and developed by the present invention, adopts an off-line monitoring and detection method. Compared with on-line real-time monitoring and detection, the cost is very low. Only a small number of sets of devices can fully cover the monitoring and detection of the same type of bonding structure of the same type of vehicle. The detection device is small, light and easy to carry and transport, and does not cause any damage to the detected structure.

[0053] (2). An off-line detection device for the health state of a bonding structure of a vehicle, which is designed and developed by the present invention. Since there are various installation and arrangement schemes for the sensor and the detected structure, it can be adapted to the health state monitoring and detection of bonding structures made of various different materials.

[0054] (3). An off-line detection method for the health state of a bonding structure of a vehicle, which is designed and developed by the present invention. It can perform off-line monitoring and detection of the health state of the bonding structures of various vehicles, ships, airplanes and other vehicles based on the local dynamic characteristics of the bonding structure. It is simple and easy to implement and does not cause any damage to the bonding structure. Description of the Drawings

[0055] Figure 1 It is a schematic structural diagram of the off-line detection device for the health state of the bonding structure of the vehicle described in the present invention.

[0056] Figure 2 It is a schematic diagram of the position of the detection points in the embodiment described in the present invention. Detailed Embodiments

[0057] The following further detailed description of the present invention is made to enable those skilled in the art to implement it with reference to the text of the specification.

[0058] As Figure 1 shown, an off-line detection device for the health state of a bonding structure of a vehicle provided by the present invention includes:

[0059] An acceleration sensor 110, a force sensor 120, a swept-frequency exciter 130, an acceleration acquisition and conversion module 140, an excitation force acquisition and conversion module 150, an exciter drive module 160, a main controller 170, and a computer analysis system 180. The acceleration sensor 110 is disposed on the bonded structure of the measured vehicle. And the acceleration sensor 110 is connected to the acceleration acquisition and conversion module 140 through a signal line, and is used for signal conversion and arithmetic processing of multiple parameters. One end of the force sensor 120 is fixed to the excitation head 131 of the swept-frequency exciter 130, and the other end can be disposed either on the bonded structure of the measured vehicle or on the acceleration sensor 110. The excitation force acquisition and conversion module 150 is connected to the force sensor 120 through a signal line. The exciter drive module 160 is connected to the swept-frequency exciter 130 through a drive signal line, and is used to provide a swept-frequency drive signal for the swept-frequency exciter 130. The main controller 170 is connected to the acceleration acquisition and conversion module 140, the excitation force acquisition and conversion module 150, and the exciter drive module 160. On the one hand, it provides a swept-frequency control signal for the exciter drive module 160. On the other hand, it collects the output data of the acceleration acquisition and conversion module 140 and the excitation force acquisition and conversion module 150 and transmits the data through a computer interface, and is used for signal transmission and instruction issuance. The computer analysis system 180 is connected to the main controller 170 and is used for data storage and query.

[0060] When detecting the health status, both the force sensor 120 and the acceleration sensor 110 can be disposed at the detection point, that is, the force sensor 120 is disposed above the acceleration sensor 110, or the acceleration sensor 110 can be disposed at the detection point, and the force sensor 120 is disposed on the bonded structure of the measured vehicle close to the detection point.

[0061] Among them, the acceleration sensor 110 can be one or more, and the acceleration sensor 110 is a side-outlet sensor. The bottom surface of the acceleration sensor 110 is mounted on the bonded structure of the measured vehicle by different methods such as a magnetic base, a non-trace adhesive, or a vacuum chuck according to the characteristics of the measured structure material, and a vibration excitation can be applied to the top surface as needed.

[0062] The force sensor 120 is a side-outlet sensor, and a buffer member 190 with appropriate thickness and elasticity is disposed between the force sensor 120 and the bonded structure of the measured vehicle. In this embodiment, the buffer member 190 is a buffer gasket to avoid damaging the surface of the measured structure when applying a vibration load.

[0063] In addition to the functions of amplifying the acceleration signal and A / D conversion, the acceleration acquisition and conversion module 140 can also have functions such as fast arithmetic processing of acceleration amplitude, velocity amplitude, and displacement amplitude, but is not limited to the above functions;

[0064] In this embodiment, the sweep-frequency exciter 130 can adopt a hand-held loading method or a robotic arm loading method according to the excitation load.

[0065] An off-line detection device for the health state of a bonding structure of a vehicle, designed and developed by the present invention, adopts an off-line monitoring and detection method. Compared with on-line real-time monitoring and detection, the cost is very low. Only a small number of sets of devices can fully cover the monitoring and detection of the same type of bonding structures of the same type of vehicles. The detection device is small, light, and easy to carry and transport, and causes no damage to the structure to be detected. At the same time, due to the various installation and arrangement schemes of the sensor and the structure to be measured, it can adapt to the health state monitoring and detection of bonding structures of various different materials.

[0066] The present invention also provides an off-line detection method for the health state of a bonding structure of a vehicle attack. Using the off-line detection device for the health state of a bonding structure of a vehicle, the method includes the following steps:

[0067] Step 1: Select n reference samples, and select the same m detection points on the n reference samples;

[0068] Among them, the selection of the reference samples and the detection points includes:

[0069] Select n newly manufactured bonding structures with qualified quality as reference samples to extract reference benchmark data and establish a health standard for the structure to be detected. Use i to represent the number of the reference sample, i = 1 to n. In theory, the larger the sample size, the higher the effectiveness of the established health diagnosis standard. In the initial stage of the research, n = 5 to 10 can be taken, and more samples can be gradually accumulated and improved during the actual detection process;

[0070] According to the size, shape, material characteristics, and safety requirements of the bonding structure to be detected, select appropriate positions at the bonding boundary of the structure as detection points. The specific selection method is as follows:

[0071] Generally, the boundary of the bonding structure can be divided into straight-line segments and curved-line segments. Select one detection point at the midpoint of each straight-line segment and curved-line segment respectively. However, it should be noted that for a curved boundary composed of two or more curved segments, each basic curved segment should be divided into one segment; in addition, a detection point is set at the centroid position of the bonding structure of the vehicle to be detected.

[0072] Number the selected m detection points, mark the positions of each detection point, and save and record the positioning information. Use j to represent the detection point number, j = 1 to m;

[0073] Step 2: Apply excitations with different frequencies to the selected detection points one by one, respectively collect and measure the variation laws of the excitation load and the acceleration, velocity, and displacement responses of the detection points with frequency, and import the measured data into the computer analysis system by the main controller, and store them in the corresponding database according to the structure number i of the measured reference sample and the detection point number j;

[0074] Within the entire frequency sweep range, that is, in the interval (f a , f b ), calculate and extract the variation laws of the displacement amplitudes and excitation load amplitudes of a total of n reference samples at m measurement points with the frequency sweep frequency f, namely U ij (f) and F ij (f). For each detection point j, a total of n groups of data (curves) can be either directly represented by numerical values or fitted into a variation law function;

[0075] Calculate the amplitude-frequency characteristic data of all detection points on n reference samples respectively:

[0076] δ ij (f) = U ij (f) / F ij (f);

[0077] In the formula, δ ij (f) is the amplitude-frequency characteristic data of the jth detection point on the ith reference sample, U ij (f) is the variation law of the displacement amplitude of the jth detection point on the ith reference sample with the frequency sweep frequency, and F ij (f) is the variation law of the excitation load amplitude of the jth detection point on the ith reference sample with the frequency sweep frequency;

[0078] Step 3: Divide the amplitude-frequency characteristic data into m groups according to the detection point numbers. Each group contains the amplitude-frequency characteristic data of n reference samples. Establish m frequency sweep frequency coordinate systems, depict the n amplitude-frequency characteristic data (curves) corresponding to n reference samples of the same detection point j in the same coordinate system, and extract the upper envelope C j (f) and the lower envelope D j (f) of the n amplitude-frequency characteristic data corresponding to the jth detection point, and [D j (f) - Δ j , C j ()f + Δ] j is the amplitude-frequency characteristic health interval of the jth detection point;

[0079] Among them, Δ j is the envelope offset. The frequency sweep frequency coordinate system is a two-dimensional rectangular coordinate system, with the abscissa being the frequency sweep frequency and the ordinate being the amplitude-frequency characteristic data;

[0080] The envelope offset is usually determined comprehensively according to various factors such as the safety factor of the bonding structure design, the degree of harm (risk factor) after the failure of the bonding structure, the maintenance cost (cost factor), and the confidence level of the experimental data of the reference sample, specifically satisfying:

[0081]

[0082] In the formula, n f is the design safety factor, n l is the risk factor after failure, l = 1 - 5, n c is the maintenance cost factor, n g is the confidence level of the experimental data of the reference sample;

[0083] The risk factor after failure satisfies:

[0084] n1 = 0.8 - 1;

[0085] n2 = 0.6 - 0.8;

[0086] n3 = 0.4 - 0.6;

[0087] n4 = 0.2 - 0.4;

[0088] n5 = 0.0 - 0.2;

[0089] Among them, n1 is the highest risk level, indicating that once it fails, it will cause fatal injuries to the vehicle or surrounding personnel; n2 is the high risk level, indicating that once it fails, it will cause certain injuries to the vehicle or surrounding personnel but not be fatal, and at the same time will be accompanied by major economic or property losses; n3 is the medium risk level, indicating that once it fails, it will only cause minor injuries to the vehicle or surrounding personnel and be accompanied by a certain degree of economic or property losses; n4 is the low risk level, indicating that once it fails, it will not cause injuries to the vehicle or surrounding personnel and will be accompanied by minor economic or property losses; n5 is the risk-free level, indicating that once it fails, it will only affect the appearance, without any personal injuries or additional losses.

[0090] The maintenance cost factor satisfies:

[0091] When ω > 10%z, n c = 1.0;

[0092] When ω ≤ 10%z,

[0093] In the formula, w is the maintenance cost and z is the total price of the equipment.

[0094] Step 4: Select the same detection points as those on the reference sample for the bonding structure of the vehicle in actual application, and obtain the real-time amplitude-frequency characteristic data of all detection points:

[0095] If the real-time amplitude-frequency characteristic data of the detection points are all within the amplitude-frequency characteristic healthy range, the bonded structure of the vehicle is in a healthy state;

[0096] In most cases, if 0 < x t <10%x s and Δr k <10%Δf, there is a potential safety hazard in the bonded structure of the vehicle, but it will not cause failure. Only the detection period needs to be shortened to half of the initial detection period and the detection continues;

[0097] where x t is the number of detection points exceeding the amplitude-frequency characteristic healthy range, x s is the total number of detection points, Δr k is the exceeding amplitude of the k-th detection point exceeding the amplitude-frequency characteristic healthy range, and Δf is the difference between the upper envelope line and the lower envelope line of the corresponding sweep frequency:

[0098] Δf = D j (f) - C j (f);

[0099] That is, the number of detection points exceeding the amplitude-frequency characteristic healthy range is less than 10% of the total number of detection points, and the exceeding amplitude of all detection points exceeding the healthy range is less than 10% of the difference between the upper and lower envelope lines of the corresponding frequency f, indicating a potential safety hazard but not causing failure. Only the detection period needs to be shortened to half of the initial detection period and the detection continues;

[0100] If x t ≥10%x s or Δr k ≥10%Δf, the bonded structure of the vehicle is in a failure risk situation, indicating a relatively high failure risk. It is recommended to remove and re-bond. If you want to continue using, more detailed and accurate evaluation is required by means of finite element analysis or local model equivalent tests, etc.

[0101] In actual implementation, the extraction of the envelope line can be directly extracted in numerical form.

[0102] In the fourth step, it can be collected (detected) by moving a single acceleration sensor point by point, or an acceleration sensor can be arranged at each detection point and the method of simply moving the sweep frequency exciter can be used. Using multiple acceleration sensors can obtain more data and can be effectively evaluated, but the cost of the detection equipment will increase, and the data storage volume and calculation workload for health evaluation will also increase accordingly. It can be selected according to specific requirements in actual implementation.

[0103] In another embodiment, first, 10 healthy window structures are selected, including: a vehicle body structure 200, a window glass 210, and an adhesive interface (area) 220 between the window glass and the vehicle body structure. By analyzing the characteristics of the structural boundary, it is not difficult to find that the local structural boundary consists of 4 straight boundaries and 4 curved boundaries. The centroid of the local structure, the midpoints of the 4 straight boundaries, and the midpoints of the 4 curved boundaries can be used as detection points, a total of 9 detection points. Mark the measurement point numbers and positions: the position of the central detection point, the position of the midpoint of the upper straight edge detection point, the position of the midpoint of the right straight edge detection point, the position of the midpoint of the lower straight edge detection point, the position of the midpoint of the left straight edge detection point, the position of the midpoint of the upper left curved edge detection point, the position of the midpoint of the upper right curved edge detection point, the position of the midpoint of the lower right curved edge detection point, and the position of the midpoint of the lower left curved edge detection point, and record the positioning information. According to the steps in the method, establish a health diagnosis standard as the basis for actual detection;

[0104] During actual detection, according to the shortest failure time X hours of the detected adhesive structure under actual service conditions, an initial detection period can be determined, usually taking hours;

[0105] Then, according to the detection points marked and recorded by the method of the present invention, data collection is carried out for each detection point, and the amplitude-frequency characteristic data of each measurement point is extracted and compared with the health standard to diagnose and evaluate the current health state of the adhesive structure;

[0106] Although the number of samples initially used to establish the health standard may be small, it can be continuously supplemented and improved during actual detection, that is, the data that meet the initial health standard during actual detection can be supplemented as reference samples. As the number of supplemented reference samples gradually increases, the effectiveness of the detection will also increase accordingly.

[0107] An off-line detection method for the health state of a vehicle adhesive structure designed and developed by the present invention can establish a health evaluation standard through statistical analysis based on the local dynamic characteristics of the health state of the adhesive structure. During actual detection, the local dynamic characteristics of the detected structure are compared with the health evaluation standard, and then the health state of the adhesive structures of various vehicles, ships, aircraft, and other vehicles can be monitored and detected off-line without causing any damage to the adhesive structure.

[0108] Although the embodiments of the present invention have been disclosed as above, it is not limited to only the applications listed in the specification and embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the field, additional modifications can be easily made. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to specific details and the embodiments shown and described here.

Claims

1. An off-line detection method for the health state of a vehicle bonding structure, using an off-line detection device for the health state of a vehicle bonding structure, characterized in that, It includes the following steps: Step 1: Select n reference samples and select the same m detection points on the n reference samples; Step 2: Apply excitations with different frequencies to the detection points separately in sequence, and calculate the amplitude-frequency characteristic data of all detection points on the n reference samples respectively: δ ij f() = U ij f() / F ij f(); where δ ij (f) is the amplitude-frequency characteristic data of the j-th detection point on the i-th reference sample, U ij (f) is the variation law of the displacement amplitude of the j-th detection point on the i-th reference sample with the swept frequency f, F ij (f) is the variation law of the excitation load amplitude of the j-th detection point on the i-th reference sample with the swept frequency f, i = 1 to n, j = 1 to m; Step 3: Divide the amplitude-frequency characteristic data into m groups according to the detection points. Each group contains the amplitude-frequency characteristic data of n reference samples, establish m sweep frequency coordinate systems, and extract the upper envelope C j (f) and the lower envelope D j (f), and [D j (f) - Δ j , C j (f) + Δ j is the amplitude-frequency characteristic health interval of the j-th detection point; where Δ j is the envelope offset, and the swept frequency coordinate system is a two-dimensional rectangular coordinate system, with the abscissa being the swept frequency and the ordinate being the amplitude-frequency characteristic data; Step 4: Select the same detection points as those on the reference samples for the adhesive structure of the vehicle in actual application, and obtain the real-time amplitude-frequency characteristic data of all detection points: If the real-time amplitude-frequency characteristic data of all detection points are within the amplitude-frequency characteristic healthy range, the adhesive structure of the vehicle is in a healthy state; If 0 < x t < 10% x s and Δr k < 10% Δf, then there is a safety hazard in the bonded structure of the vehicle, shorten the inspection period to half of the initial inspection period, and continue the inspection; Among them, x t is the number of detection points outside the healthy range of the amplitude-frequency characteristic, x s is the total number of detection points, Δr k is the exceeding amplitude of the k-th detection point outside the healthy range of the amplitude-frequency characteristic, and Δf is the difference between the upper envelope line and the lower envelope line of the corresponding swept frequency: Δf = D j (f) - C j (f); If x t ≥ 10% x s or Δr k ≥ 10% Δf, then the bonded structure of the vehicle is in a failure risk situation; Among them, the off-line detection device for the health state of the adhesive structure of the vehicle includes: At least one acceleration sensor, which is arranged on the adhesive structure of the measured vehicle; An acceleration acquisition and conversion module, which is connected to the at least one acceleration sensor and is used for signal conversion and operation processing of multiple parameters; A sweep-frequency exciter; A force sensor, one end of which is fixed to the excitation head of the sweep-frequency exciter, and the other end is optionally arranged on the adhesive structure of the measured vehicle or at least one acceleration sensor; An excitation force acquisition and conversion module, which is connected to the force sensor; An exciter drive module, which is connected to the sweep-frequency exciter and is used to provide a sweep-frequency drive signal for the sweep-frequency exciter; A main controller, which is connected to the acceleration acquisition and conversion module, the excitation force acquisition and conversion module and the exciter drive module and is used for signal transmission and instruction issuance; A computer analysis system, which is connected to the main controller and is used for data storage and query; Among them, the at least one acceleration sensor is arranged on the adhesive structure of the measured vehicle through a magnetic buckle, a non-trace adhesive or a vacuum chuck.

2. The off-line detection method for the health state of the vehicle bonding structure according to claim 1, characterized in that, The at least one acceleration sensor and the force sensor are both side-outlet sensors.

3. The off-line detection method for the health state of the vehicle bonding structure according to claim 2, characterized in that, It also includes: A buffer, which is arranged between the force sensor and the adhesive structure of the measured vehicle.

4. The off-line detection method for the health state of the vehicle bonding structure according to claim 3, characterized in that, The loading method of the sweep-frequency exciter is hand-held loading or robotic arm loading.

5. The off-line detection method for the health state of the bonding structure of a vehicle as claimed in claim 1, characterized in that, The selection of the detection points specifically includes: Divide the boundary of the adhesive structure of the measured vehicle into straight line segments and curve segments, select the centroid of the adhesive structure, the midpoint of each straight line segment and the midpoint of each curve segment as the detection points, and when the boundary is composed of two or more curve segments, divide each basic curve into one segment and then select the detection points.

6. The off-line detection method for the health state of the vehicle bonding structure according to claim 5, characterized in that The envelope offset satisfies: Where n f is the design safety factor, n l is the risk factor after failure, l = 1 to 5, n c is the maintenance cost factor, n g is the confidence level of the reference sample experimental data.

7. The off-line detection method for the health state of a vehicle bonding structure according to claim 6, wherein, The risk coefficient after failure satisfies: n1＝0.8～1； n2＝0.6～0.8； n3＝0.4～0.6； n4＝0.2～0.4； n5＝0.0～0.2； Among them, n1 is the highest risk level, n2 is the high risk level, n3 is the medium risk level, n4 is the low risk level, and n5 is the risk-free level.

8. The off-line detection method for the health state of the vehicle bonding structure according to claim 7, characterized in that, The maintenance cost coefficient satisfies: When ω > 10%z, n c = 1.0; When ω ≤ 10%z, In the formula, w is the maintenance cost and z is the total price of the equipment.

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