Embedded film resistor measuring method and system for internal failure of composite material connection structure

Abstract

The invention discloses an embedded thin-film resistor measurement method and system for internal failure of a composite material connection structure, and belongs to the field of composite material structure test measurement. Comprising a typical bolt-glue joint combined structure formed by connecting a composite material upper skin, a middle foam core layer, a composite material lower skin, a composite material upper connecting plate and a composite material lower connecting plate through fastening bolts. A one-way film resistance sensor, a three-way film resistance sensor, a four-way film resistance sensor and a porous medium resistance sensor are embedded in key failure areas such as the periphery of a hole, an interlayer interface and a core-skin interface in advance; and the sensor and the structure are integrated through a vacuum forming process. The integrated test piece is placed on the end support, the loading action cylinder and the pressing strip are used for applying load, all the sensors output resistance change signals in real time, the resistance change signals are transmitted to an external acquisition system through the electric signal wire, and conversion from mechanical signals to electric signals is achieved.

Description

Technical Field

[0001] This invention belongs to the field of composite material structure testing and measurement, and particularly relates to an embedded thin film resistance measurement method and system for internal failure of composite material connection structure. Background Technology

[0002] Composite material connection areas typically employ a combination of adhesive and bolted connections. These areas exhibit complex stress compositions and multiple failure modes, including interlaminar shear failure, peri-aperture compression failure, and combined bending and shear failure. They are often weak points in structural design, threatening the safety of composite material structural engineering applications. Composite material connection structures (such as bolted connections and adhesive joints) are prone to internal damage under load, and traditional visual or ultrasonic testing cannot achieve real-time online monitoring, leading to the risk of sudden failure.

[0003] Due to the limited space at the joints of composite materials, traditional sensors can only be placed on the surface, making them insensitive to interfacial shear failures and difficult to observe, measure, and assess the occurrence and development of cracks hidden inside the structure. Different failure modes (such as impact damage and fatigue cracks) may produce similar detection signals, and existing physical monitoring methods such as acoustic and optical sensors are affected by multimodal failures, which can easily lead to missed or false detections of internal structural damage. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an embedded thin-film resistance measurement method for internal failures in composite material connection structures, comprising:

[0005] Embed thin-film resistance sensors in critical failure regions of composite material bonding structures;

[0006] The connection interface between the thin-film resistance sensor and the composite material connection structure is integrally formed;

[0007] A load is applied to the composite material connection structure, causing the thin-film resistance sensor to generate a resistance change signal;

[0008] The resistance change signal is acquired and converted into a digital signal;

[0009] Based on the digital signal, the internal damage of the structure is located and the damage result is obtained;

[0010] Based on the damage results, output structural health status information.

[0011] Optionally, a critical failure region identification step is performed before embedding the thin-film resistive sensor:

[0012] Mechanical simulation or experimental loading of composite material connection structures;

[0013] Based on simulation or experimental results, identify stress concentration regions, structural abrupt regions, and / or material transition regions;

[0014] The identified areas are designated as the critical failure areas.

[0015] Optionally, the integral molding step includes:

[0016] Before assembling the composite material connection structure, attach the thin-film resistance sensor to the critical failure area;

[0017] Use a thin film homogeneous with the composite material as the outer layer of the sensor;

[0018] Encapsulation is achieved using adhesive of the same type as the composite material, enabling the sensor and the connection interface to be cured without additional interface.

[0019] Optionally, the embedding step includes:

[0020] Based on the expected failure mode of the connection structure, select one or a combination of the following sensor types:

[0021] A unidirectional thin-film resistance sensor is embedded around the opening;

[0022] Embedding a triaxial thin-film resistance sensor at the interlayer shear interface;

[0023] A four-way thin-film resistive sensor is embedded in a region that simultaneously bears normal and in-plane loads.

[0024] Embedding a button-type thin-film resistive sensor in a space-constrained area.

[0025] Optionally, when a unidirectional thin-film resistive sensor is embedded, the following is performed:

[0026] Vertical and horizontal resistance bars are arranged on the sensor to form a sensor array;

[0027] Collect the resistance change signals of each resistor bar;

[0028] The normal tensile and compressive stress distribution is obtained based on the resistance change signal.

[0029] Optionally, when a triaxial thin-film resistive sensor is embedded, the following is performed:

[0030] Arrange triaxial resistive sensing elements on the sensor at a set interval;

[0031] Collect the resistance change signals of each sensor;

[0032] Based on the resistance change signal, the in-plane longitudinal, transverse, and shear stress distributions are obtained.

[0033] Optionally, when a four-way thin-film resistive sensor is embedded, the following is performed:

[0034] A disc-shaped resistive sensing unit is arranged on the sensor, corresponding to the normal direction and the in-plane direction respectively;

[0035] Collect the resistance change signals of each disc-shaped unit;

[0036] Based on the resistance change signal, the stress state under normal load and in-plane triaxial load is obtained respectively.

[0037] Optionally, when a button-type thin-film resistive sensor is embedded, the following is performed:

[0038] A multi-directional cross-sensitive grid is formed on the sensor by photolithography;

[0039] Acquire the resistance change signal of the sensitive grid;

[0040] Based on the resistance change signal, the structural response caused by multi-directional loads within a spatially confined area is obtained.

[0041] Optionally, the step of outputting the structural health status information includes:

[0042] Based on historical digital signals and location results, a failure prediction model for composite material structures is constructed.

[0043] Embed the forecast model into a neural network algorithm;

[0044] Using neural network algorithms to determine the degree of damage to real-time digital signals;

[0045] Based on the judgment result, a graded early warning information is triggered and output to the monitoring terminal.

[0046] On the other hand, the present invention also provides an embedded thin-film resistance measurement system for internal failure of composite material connection structures, comprising:

[0047] Thin-film resistive sensor arrays are used to embed and integrally mold in critical failure areas of composite material connection structures, converting the mechanical response inside the structure into a resistance change signal.

[0048] An electrical signal acquisition module is electrically connected to the thin-film resistor sensor array and is used to acquire the resistance change signal in real time and convert it into a digital signal.

[0049] The data processing module is communicatively connected to the electrical signal acquisition module and is used to filter, extract features and perform spatial correlation analysis on the digital signal to obtain the location information of internal structural damage.

[0050] The forecasting and early warning module is communicatively connected to the data processing module and is used to output structural health status assessment results and trigger graded early warnings based on the location information and resistance change trend, according to a preset or self-learning failure prediction model.

[0051] The thin-film resistor sensor array, electrical signal acquisition module, data processing module, and forecasting and early warning module together constitute a closed-loop monitoring link.

[0052] On the other hand, the present invention also provides an electronic device including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0053] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0054] Compared with the prior art, the present invention has the following advantages and technical effects:

[0055] This invention addresses practical engineering applications by establishing a thin-film resistance measurement system for measuring internal structural failures. This system comprises a thin-film resistance sensor, test specimen, electrical signal acquisition instrument, recording computer, and monitoring and early warning module. By monitoring resistance changes to reflect stress distribution and damage evolution within the structure, an intelligent prediction algorithm for composite material structural failure based on stress change trends is developed. This algorithm automatically extracts structural failure characteristics such as fiber fracture, matrix cracking, and delamination buckling. Furthermore, a composite material failure prediction program based on neural networks and deep learning is established. The system's functions include: (1) dynamically capturing abnormal resistance signals caused by damage such as cracking and interface debonding; (2) using multi-channel data fusion technology to locate micro-damage positions through a spatial correlation algorithm based on resistance changes; and (3) outputting a structural health status assessment report to provide a basis for early warning of critical failures. Attached Figure Description

[0056] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0057] Figure 1 This is a schematic diagram of the loading of a composite material bolt connection structure containing an embedded thin-film resistor sensor according to an embodiment of the present invention;

[0058] Figure 2 This is a top view of a composite material bolt connection structure containing an embedded thin-film resistive sensor according to an embodiment of the present invention;

[0059] Figure 3 This is a schematic diagram of a unidirectional thin-film resistor sensor according to an embodiment of the present invention;

[0060] Figure 4 This is a schematic diagram of a three-dimensional thin-film resistive sensor according to an embodiment of the present invention;

[0061] Figure 5 This is a schematic diagram of a four-directional thin-film resistive sensor according to an embodiment of the present invention;

[0062] Figure 6 This is a schematic diagram of a button-type thin-film resistive sensor according to an embodiment of the present invention;

[0063] Figure 7 This is a cross-sectional view of the thin-film resistance sensor according to an embodiment of the present invention;

[0064] Figure 8 This is a schematic diagram of a composite material connection structure failure monitoring system based on a thin-film resistance sensor according to an embodiment of the present invention;

[0065] Among them, 1. Composite material lower skin; 2. Intermediate foam core layer; 3. Composite material upper skin; 4. Composite material upper connecting plate; 5. Composite material lower connecting plate; 6. Fastening bolt; 7. Unidirectional thin-film resistance sensor; 8. Tridirectional thin-film resistance sensor; 9. Quadridirectional thin-film resistance sensor; 10. Porous dielectric resistance sensor; 11. Longitudinal sensing resistor; 12. Lateral sensing resistor; 13. Flexible thin-film substrate; 14. Electrical signal wire; 15. Tridirectional sensing resistor; 16. Quadridirectional sensing resistor; 17. Multidirectional cross sensing resistor; 18. Upper thin-film substrate; 19. Lower thin-film substrate; 20. Intermediate sensing resistor; 21. Pressure strip; 22. Loading cylinder; 23. End support; 24. Micro-stiffness flexible thin-film substrate; 25. Multidirectional adjustable weak stiffness flexible substrate; 26. High flexibility low modulus thin-film substrate. Detailed Implementation

[0066] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0067] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0068] Example 1

[0069] like Figure 8 As shown, this embodiment provides an embedded thin-film resistance measurement method for internal failure of a composite material connection structure, including:

[0070] Embed thin-film resistance sensors in critical failure regions of composite material bonding structures;

[0071] The connection interface between the thin-film resistance sensor and the composite material connection structure is integrally formed;

[0072] A load is applied to the composite material connection structure, causing the thin-film resistance sensor to generate a resistance change signal;

[0073] The resistance change signal is acquired and converted into a digital signal;

[0074] Based on the digital signal, the internal damage of the structure is located and the damage result is obtained;

[0075] Based on the damage results, output structural health status information.

[0076] For composite material bolted and bonded combined structures, the load-bearing conditions of the structure in engineering applications are simulated. A normal compressive load is applied to the middle of the connection area by a three-point bending facility with simple support at both ends and loading in the middle. This is used to identify key areas where the structure may fail, such as abrupt changes in structural form, bonding of different materials, and bolted connection areas, and serves as the embedding area for thin-film resistor sensors.

[0077] Based on the failure modes of composite material connection structures, such as extrusion failure around openings, shear failure between composite laminates, and failure due to a combination of bending and shear in the joint transition zone, suitable thin-film resistance sensors are selected to capture the corresponding structural stresses, providing a basis for structural failure judgment.

[0078] Before the composite material connection and assembly, a thin-film resistance sensor is embedded at the critical failure location and bonded to the connection interface to control the influence of the additional interface. Furthermore, to reduce the impact of heterogeneous material bonding, the outermost interface of the thin-film resistor is preferably fabricated from a homogeneous thin-film material with a composite material structure, and the thin-film resistor is encapsulated using a homogeneous adhesive made of composite material.

[0079] For bolted connections in composite materials, to address the stress problem along the thickness direction in areas where conventional methods cannot create holes, a thin-film resistance sensor is attached to the interface around the bolt hole. A thin-film resistance sensor with the same diameter as the bolt hole is preferred to be designed to directly measure the compressive load in the narrow gap between the bolt and the bolt hole.

[0080] To address structural failure under tensile and compressive loads, a unidirectional thin-film resistance sensor is constructed. The main method involves arranging longitudinal and transverse resistance strips to form an interwoven sensing array. By analyzing the resistance changes under load, the interfacial stress over time and its spatial distribution can be calculated, thus converting the mechanical signal into a measurable and recordable electrical signal.

[0081] A triaxial thin-film resistive sensor is constructed based on the combined effects of in-plane longitudinal load, transverse load, and shear load. The main method involves arranging triaxial resistive induction elements at regular intervals on the thin film, controlling the in-plane stiffness of the film, and introducing a triaxial stiffness correction coefficient to improve the effectiveness of resistance measurement at each measuring point. This establishes a measurement and characterization technique for the combined biaxial and shear stresses.

[0082] To address complex operating conditions where loads are simultaneously applied by normal and in-plane loads, a four-dimensional thin-film resistive sensor was developed. The main method involves arranging thin, disc-shaped resistive sensors to allow for independent measurement of normal and in-plane resistance changes. This enables the separate measurement of normal loads, in-plane tensile / compressive loads, and shear loads. Furthermore, by arranging the disc-shaped resistive sensors at equal intervals, large-area load measurements can be achieved.

[0083] To address the measurement needs in confined spaces, a button-type thin-film resistive sensor was developed. The main method involves controlling the width and spacing of the resistive strips, fabricating the sensitive grid using photolithography, and arranging them longitudinally, laterally, and diagonally. This sensor possesses the ability to measure structural changes caused by multi-directional loads, converting mechanical signals into electrical signals, and is suitable for flexible deployment in minute measurement spaces.

[0084] To modulate the thickness and stiffness of the thin-film resistor, flexible thin films such as nano-carbon or polyimide are embedded into the resistor array after being insulated and encapsulated, forming a three-layer sandwich structure of upper surface thin film - middle resistor - lower surface thin film, controlling the overall thickness of the thin-film resistor to not exceed 0.5mm.

[0085] This embodiment proposes a forward-looking alarm strategy based on internal stress levels. It integrates information such as stress peak value, stress alternation amplitude, peak value change trend, and extreme stress in long-term cumulative data to develop a machine learning model for composite material damage prediction. It embeds long short-term neural networks, embedded physical information neural networks, convolutional neural networks, etc., and combines the technical advantages of different network architectures to build a new deep learning algorithm that is fast, robust, and effective, thus solving the problems of instability and poor sensitivity of traditional alarms.

[0086] On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0087] On the other hand, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0088] Example 1

[0089] This embodiment provides an embedded thin-film resistance measurement method for internal failure of composite material connection structures, including:

[0090] Thin-film resistive sensor arrays are used to embed and integrally mold in critical failure areas of composite material connection structures, converting the mechanical response inside the structure into a resistance change signal.

[0091] An electrical signal acquisition module is electrically connected to the thin-film resistor sensor array and is used to acquire the resistance change signal in real time and convert it into a digital signal.

[0092] The data processing module is communicatively connected to the electrical signal acquisition module and is used to filter, extract features and perform spatial correlation analysis on the digital signal to obtain the location information of internal structural damage.

[0093] The forecasting and early warning module is communicatively connected to the data processing module and is used to output structural health status assessment results and trigger graded early warnings based on the location information and resistance change trend, according to a preset or self-learning failure prediction model.

[0094] The thin-film resistor sensor array, electrical signal acquisition module, data processing module, and forecasting and early warning module together constitute a closed-loop monitoring link.

[0095] like Figure 1 and Figure 2 The diagram illustrates the loading of a composite bolted connection structure with embedded thin-film resistance sensors. It includes a lower composite skin 1, an intermediate foam core layer 2, an upper composite skin 3, an upper composite connecting plate 4, a lower composite connecting plate 5, fastening bolts 6, a unidirectional thin-film resistance sensor 7, a tridirectional thin-film resistance sensor 8, a four-directional thin-film resistance sensor 9, a porous dielectric resistance sensor 10, a pressure strip 20 with an intermediate sensing resistor 21, a loading cylinder 22, and end supports 23. Its main purpose is to demonstrate the stress and failure development process of the structure through mechanical loading, verifying the rationality of the thin-film resistance sensor arrangement and its ability to measure structural failure. In critical areas where the composite connection structure may fail, suitable thin-film resistance sensors are selected and pre-embedded in specific positions. The thin-film resistance sensors are integrated with the composite connection structure through processes such as glue pre-impregnation and vacuum forming. The composite connection structure is placed on the supports at both ends. A load is applied to the middle of the model through the loading cylinder and the intermediate sensing resistor 21 of the pressure strip 20. Under tensile, compressive, and shear loads, the thin-film resistance sensor will change its resistance, converting the mechanical signal into a measurable electrical signal.

[0096] like Figure 3The unidirectional thin-film resistance sensor 7 shown includes a longitudinal sensing resistor 11, a transverse sensing resistor 12, and a flexible thin-film substrate 13. Its main purpose is to measure the normal tensile and compressive stress by causing the resistance change through the normal load, and to provide a detailed characterization of the bolt's extrusion load on the composite material opening, the intermediate sensing resistor 20 of the pressure strip 21, and the compressive load between the composite material and the pressure strip 21. It establishes a digital description of the amplitude and distribution of the normal load and solves the problem that traditional sensors cannot be placed in narrow gaps.

[0097] like Figure 4 The triaxial thin-film resistance sensor 8 shown includes a micro-stiffness flexible thin-film substrate 24, an electrical signal wire 14, and a triaxial sensing resistor 15. Its main function is to sense changes in in-plane loads, including but not limited to longitudinal tension / compression, transverse tension / compression, and in-plane shear. It can be applied to scenarios such as the interface between two composite materials and the internal interface of composite laminates. Furthermore, by adjusting the length of the induced charge, it can also measure the mechanical information of porous media materials. This triaxial thin-film resistance sensor 8 can solve the measurement problems of interlaminar slippage, cracking, and interface damage in composite materials.

[0098] like Figure 5 The four-directional thin-film resistance sensor 9 shown includes a multi-directional adjustable weak stiffness flexible substrate 25, an electrical signal wire 14, and a four-directional sensing resistor 16. Its main function is to sense changes in in-plane load and normal load. It has the combined functions of a unidirectional thin-film resistance sensor 7 and a tridirectional thin-film resistance sensor 8, and can be applied to the measurement of complex stress regions such as tension, compression, bending, and shear inside composite materials, solving the problem of judging the mutual interference of multiple failure modes inside composite material structures.

[0099] like Figure 6 The button-type thin-film resistive sensor shown includes a highly flexible, low-modulus thin-film substrate 26, electrical signal wires 14, and a multi-directional cross-resistor 17. Its main function is to provide stress measurement for spatially confined structures, detecting minute physical quantities through resistance changes, thus overcoming the bottlenecks of traditional sensors in terms of size and environmental adaptability.

[0100] like Figure 7 The cross-section of the thin-film resistor sensor shown includes an upper thin-film substrate 18, a lower thin-film substrate 19, and an intermediate sensing resistor. It adopts a stack of multiple heterogeneous materials, optimizes the stress matching and electrical coupling between layers through interface engineering, and realizes the resistor pattern through photolithography. The resistor sensing unit and other functional components are integrated in the same cross-section to achieve self-calibration and temperature compensation.

[0101] like Figure 8The schematic diagram of a composite material connection structure failure monitoring system based on thin-film resistance sensors illustrates the following: key area screening of the composite material connection structure, prediction of internal failure modes, selection of thin-film resistance sensors, composite material specimens, electrical signal acquisition, acquisition computer, and monitoring and early warning modules. Key area screening identifies areas in the connection structure prone to stress concentration, delamination / debonding / cracks through simulation calculations or preliminary experimental results. Internal failure mode prediction, based on composite material failure theory and connection structure characteristics, predicts possible failure modes (fiber fracture, matrix cracking, interface debonding, etc.) to guide sensor placement strategies. According to monitoring requirements, appropriate thin-film resistance sensor types are selected and embedded into the interlayer of the composite material connection structure to ensure mechanical compatibility. The electrical signal acquisition module collects real-time changes in sensor resistance (reflecting strain / damage), converts them into digital signals, and stores and performs real-time analysis (such as noise analysis) using computer monitoring software. (Acoustic filtering, feature extraction); damage level is judged based on threshold or machine learning model, triggering graded early warning (such as minor damage warning, critical failure alarm); unlike traditional alarm methods, this invention proposes a prospective alarm strategy based on internal stress level, which integrates information such as stress peak value, stress alternation amplitude, peak value change trend, and extreme stress of long-term cumulative data to develop a machine learning model for composite material damage prediction. It embeds long short-term neural networks, embedded physical information neural networks, convolutional neural networks, etc., and integrates the technical advantages of different network architectures to build a new deep learning algorithm with speed, robustness and stamina, which solves the problems of instability and poor sensitivity of traditional alarms.

[0102] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for measuring the resistance of an embedded thin-film composite material connection structure in the event of internal failure, characterized in that, include: Embed thin-film resistance sensors in critical failure regions of composite material bonding structures; The connection interface between the thin-film resistance sensor and the composite material connection structure is integrally formed; A load is applied to the composite material connection structure, causing the thin-film resistance sensor to generate a resistance change signal; The resistance change signal is acquired and converted into a digital signal; Based on the digital signal, the internal damage of the structure is located and the damage result is obtained; Based on the damage results, output structural health status information.

2. The method according to claim 1, characterized in that, Before embedding the thin-film resistive sensor, perform the critical failure region identification step: Mechanical simulation or experimental loading of composite material connection structures; Based on simulation or experimental results, identify stress concentration regions, structural abrupt regions, and / or material transition regions; The identified areas are designated as the critical failure areas.

3. The method according to claim 1, characterized in that, The integrated molding step includes: Before assembling the composite material connection structure, attach the thin-film resistance sensor to the critical failure area; Use a thin film homogeneous with the composite material as the outer layer of the sensor; Encapsulation is achieved using adhesive of the same type as the composite material, enabling the sensor and the connection interface to be cured without additional interface.

4. The method according to claim 1, characterized in that, The embedding step includes: Based on the expected failure mode of the connection structure, select one or a combination of the following sensor types: A unidirectional thin-film resistance sensor is embedded around the opening; Embedding a triaxial thin-film resistance sensor at the interlayer shear interface; A four-way thin-film resistive sensor is embedded in a region that simultaneously bears normal and in-plane loads. Embedding a button-type thin-film resistive sensor in a space-constrained area.

5. The method according to claim 4, characterized in that, When a unidirectional thin-film resistive sensor is embedded, the following is performed: Vertical and horizontal resistance bars are arranged on the sensor to form a sensor array; Collect the resistance change signals of each resistor bar; The normal tensile and compressive stress distribution is obtained based on the resistance change signal.

6. The method according to claim 4, characterized in that, When a triaxial thin-film resistive sensor is embedded, the following is performed: Arrange triaxial resistive sensing elements on the sensor at a set interval; Collect the resistance change signals of each sensor; Based on the resistance change signal, the in-plane longitudinal, transverse, and shear stress distributions are obtained.

7. The method according to claim 4, characterized in that, When a four-way thin-film resistive sensor is embedded, the following is performed: A disc-shaped resistive sensing unit is arranged on the sensor, corresponding to the normal direction and the in-plane direction respectively; Collect the resistance change signals of each disc-shaped unit; Based on the resistance change signal, the stress state under normal load and in-plane triaxial load is obtained respectively.

8. The method according to claim 4, characterized in that, When an embedded button-type thin-film resistive sensor is used, the following is performed: A multi-directional cross-sensitive grid is formed on the sensor by photolithography; Acquire the resistance change signal of the sensitive grid; Based on the resistance change signal, the structural response caused by multi-directional loads within a spatially confined area is obtained.

9. The method according to claim 1, characterized in that, The steps for outputting the health status information of the structure include: Based on historical digital signals and location results, a failure prediction model for composite material structures is constructed. Embed the forecast model into a neural network algorithm; Using neural network algorithms to determine the degree of damage to real-time digital signals; Based on the judgment result, a graded early warning information is triggered and output to the monitoring terminal.

10. An embedded thin-film resistance measurement system for internal failure of a composite material connection structure, characterized in that, include: Thin-film resistive sensor arrays are used to embed and integrally mold in critical failure areas of composite material connection structures, converting the mechanical response inside the structure into a resistance change signal. An electrical signal acquisition module is electrically connected to the thin-film resistor sensor array and is used to acquire the resistance change signal in real time and convert it into a digital signal. The data processing module is communicatively connected to the electrical signal acquisition module and is used to filter, extract features and perform spatial correlation analysis on the digital signal to obtain the location information of internal structural damage. The forecasting and early warning module is communicatively connected to the data processing module and is used to output structural health status assessment results and trigger graded early warnings based on the location information and resistance change trend, according to a preset or self-learning failure prediction model. The thin-film resistor sensor array, electrical signal acquisition module, data processing module, and forecasting and early warning module together constitute a closed-loop monitoring link.

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