A cabin structure dynamic strength detection system

Abstract

This invention discloses a dynamic strength testing system for a cabin structure, comprising a monitoring unit, a data receiving unit, a data preprocessing unit, a data analysis unit, and a data output unit. The monitoring unit receives monitoring signals from various monitoring points on the mounting base of the aircraft's electronic components. These monitoring signals include acceleration, velocity, and strain signals. The data receiving unit receives the monitoring signals and forwards them to the data preprocessing unit, which normalizes the signals before sending them to the data analysis unit. This invention assesses the service status by comprehensively collecting acceleration, velocity, and strain signals, significantly simplifying the testing process and reducing experimental costs.

Description

Technical Field

[0001] This invention relates to the field of aviation, and in particular to a dynamic strength testing system for cabin structures. Background Technology

[0002] With the development of aviation technology, aircraft need to carry various scientific instruments and equipment for different purposes. To adapt to the installation and carrying of various instruments and equipment, this paper studies the fatigue failure criteria of complex cabin structures under random vibration to address the problem of structural dynamics adaptability of aviation equipment.

[0003] The area affected by random vibrations is mainly concentrated in the complex tail section of the cabin, which consists of two main components: the outer shell and the mounting plate. Due to the bolted connections between the sections, the mounting plate is significantly affected by random impact vibrations and transmits vibrational energy to the outer shell. Under mixed high-frequency and low-frequency random vibrations, the cabin is highly susceptible to damage. As the carrier of critical core precision scientific instruments and equipment in aviation equipment, the dynamic strength testing of the aircraft structure is particularly crucial. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a dynamic strength detection system for cabin structures.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A dynamic strength testing system for cabin structures includes a monitoring unit, a data receiving unit, a data preprocessing unit, a data analysis unit, and a data output unit;

[0007] The monitoring unit is used to obtain monitoring signals from each monitoring point on the aircraft electronic component mounting base; the monitoring signals include acceleration signals, velocity signals and strain signals; the data receiving unit is used to receive the monitoring signals and forward them to the data preprocessing unit, the data preprocessing unit normalizes the monitoring signals and then sends them to the data analysis unit.

[0008] The data analysis unit analyzes the received acceleration, velocity, and strain signals to obtain the corresponding displacement and strain modes, and then obtains the damage factor vector based on the displacement and strain modes.

[0009] The data output unit is used to output the damage factor vector to obtain the damage status of the cabin structure.

[0010] Further improvements include a frustum-shaped overall geometry for the stern compartment of the cabin structure; the monitoring unit is mounted on the cabin structure via a mounting base structure; the mounting base structure has a U-shaped plate structure with uniform plate thickness, and the top surface and side feet are square, with three bolt holes evenly distributed on each side foot; the monitoring unit includes a velocity signal monitoring unit, an acceleration signal monitoring unit, and a strain signal monitoring unit; the velocity signal monitoring unit consists of several velocity sensors; the acceleration signal monitoring unit consists of several acceleration sensors; and the strain signal monitoring unit consists of several strain gauges.

[0011] Further improvements include the following steps for the cabin structure dynamic strength testing system to perform cabin structure dynamic strength testing:

[0012] Step 1: The acceleration signal monitoring unit monitors the acceleration of the monitoring point of the mounting base structure and feeds it back to the signal processing module in real time;

[0013] Step 2: The speed monitoring unit is used to monitor the speed of the monitoring point of the mounting base structure and feed it back to the signal processing module in real time;

[0014] Step 3: The strain signal monitoring unit monitors the strain at the monitoring point of the mounting base structure and feeds it back to the signal processing module in real time;

[0015] Step 4: After sampling and collecting acceleration, velocity and strain data, the data is transmitted to the data analysis unit. The data analysis unit analyzes the received acceleration signal, velocity signal and strain signal to obtain the predicted stiffness damage factor.

[0016] Step 5: Compare the predicted stiffness damage factor with the preset threshold. If the predicted stiffness damage factor is greater than the preset threshold, issue an alarm.

[0017] A further improvement is made to the method for obtaining the predicted stiffness damage factor as follows:

[0018] Step 4.1: Perform modal testing on the mounting base. The data analysis unit performs modal analysis on the collected signals to obtain the natural frequencies and mixed mode shapes of the mounting base.

[0019] Step 4.2: The assumed stiffness damage factor vector is used as an input variable and imported into the finite element model of the mounting base. The data analysis unit calculates the natural frequency, displacement mode and strain mode of the cabin structure.

[0020] Step 4.3: Construct the mixed mode shape and calculate the mixed modes of the assumed stiffness-damage factor lower limit element model. The mixed mode shapes are as follows:

[0021] Φ hFor mixed modes, Φ ε For strain modes, S represents the displacement mode; T denotes matrix transpose; S is the transformation matrix between strain and displacement. + S represents the pseudo-inverse of S; I is the identity matrix;

[0022] Using the assumed stiffness damage factor as the data label, displacement modes strain mode Φ ε and mixed mode Φ h The training dataset is constructed using the input data of the BP neural network; the training input neural network is then trained until the loss function converges to obtain the trained neural network.

[0023] Step 4.4 involves real-time acquisition of the displacement modes of the cabin structure. strain mode Φ ε and mixed mode Φ h Input the trained neural network to obtain the predicted stiffness damage factor.

[0024] 5. The cabin structure dynamic strength detection system as described in claim 4, wherein the loss function is as follows:

[0025]

[0026]

[0027]

[0028] In the formula: λ mea，i Let λ be the natural frequency measured by the i-th strain sensor. est，i (Θ) represents the calculated natural frequency at the location of the i-th sensor; the subscripts mea and est represent measurement and calculation, respectively; N m N represents the total modal order; s This represents the sum of the number of all sensors, including velocity sensors, acceleration sensors, and strain gauge sensors; w f，i w φ，i For each weight coefficient, in the weight coefficient value test, the two values ​​in the objective function are on the same order of magnitude; φ mea，ij This represents the mixed mode measured between the i-th and j-th sensors; φ est，ij (Θ) represents the predicted mixed mode between the i-th and j-th sensors; f(Θ) represents the total error between the actual strength value and the predicted strength value of the cabin structure, R f,i (Θ) represents the error between the actual element modal frequency and the predicted element modal frequency. This represents the error between the actual element mode shape and the predicted element mode shape.

[0029] A further improvement is made to the method for constructing the hybrid mode shape as follows:

[0030] Structural displacement frequency response function H x (w) Structural acceleration frequency response function and structural strain frequency response function H ε (w) respectively satisfy the following relations:

[0031]

[0032]

[0033]

[0034] The three formulas above are simplified to:

[0035] H x (w)=Φ T Φ * (w)

[0036]

[0037] H ε (w)=(S + Φ) T Φ * (w)

[0038] Based on the interrelationships between the different mode shapes, the following hybrid mode shapes are constructed:

[0039]

[0040] in, These are the displacement mode shape and the strain mode shape of the k-th mode, respectively; M k For modal mass; w k ξ k Here, represents the k-th modal frequency and damping ratio, respectively; T denotes matrix transpose; Nm is the total modal order of the structure, i is the imaginary unit; S is the transformation matrix between strain and displacement, h, ε, ... These represent mixed modes, strain modes, and displacement modes, respectively.

[0041] The beneficial effects of this invention are as follows:

[0042] In the technical solution of this invention, the service status is judged by comprehensively collecting acceleration signals, velocity signals and strain signals, which can greatly simplify the testing process and reduce repeated experiments to a certain extent, thereby reducing experimental costs. Attached Figure Description

[0043] The invention will be further illustrated with reference to the accompanying drawings, but the contents of the drawings do not constitute any limitation on the invention.

[0044] Figure 1 A simplified diagram of the measured cabin model and experimental setup.

[0045] Figure 2 This is a schematic diagram of the workflow of the present invention. Detailed Implementation

[0046] To make the purpose, technical solution, and advantages of the invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and examples.

[0047] Reference Figure 1 and Figure 2 The present invention provides a dynamic strength testing system for cabin structures, comprising:

[0048] Operating condition monitoring module;

[0049] Includes: acceleration monitoring unit, velocity monitoring unit, strain monitoring unit. The acceleration monitoring unit, velocity monitoring unit, and strain monitoring unit are located on the aircraft electronic component mounting structure. They monitor the acceleration, velocity, and strain signals at each monitoring point on the aircraft electronic component mounting structure, and transmit the data to the signal processing module after sampling and collection.

[0050] Signal processing module;

[0051] It includes: a data receiving unit, a data preprocessing unit, a data analysis unit, and a data output unit. The data analysis unit analyzes the collected acceleration signals, velocity signals, and strain signals.

[0052] In the operating condition monitoring module, the acceleration signal monitoring unit includes an acceleration signal acquisition unit for real-time acquisition of acceleration signals at various monitoring points on the aircraft electronic component mounting base, in order to monitor the acceleration signals at the monitoring points; the velocity monitoring unit includes a velocity sensor unit for real-time acquisition of velocity signals at various monitoring points on the aircraft electronic component mounting base, in order to monitor the velocity signals at the monitoring points; and the strain monitoring unit includes a strain sensor unit for real-time acquisition of strain signals at various monitoring points on the aircraft electronic component mounting base, in order to monitor the strain signals at the monitoring points.

[0053] The measured cabin structure's tail section has an overall geometric shape of a frustum; the mounting base has an overall geometric shape of a Z-shaped plate structure with uniform plate thickness, and the top surface and side feet are square, with three bolt holes evenly distributed on each side foot; the velocity signal monitoring unit is mainly composed of velocity sensors; the acceleration signal monitoring unit is mainly composed of acceleration sensors; and the strain signal monitoring unit is mainly composed of strain gauges.

[0054] Specifically, the dynamic strength testing of the cabin structure includes the following steps:

[0055] Step 1: The acceleration signal monitoring unit monitors the acceleration of the monitoring point of the mounting base structure and feeds it back to the signal processing module in real time;

[0056] Step 2: The speed monitoring unit is used to monitor the speed of the monitoring point of the mounting base structure and feed it back to the signal processing module in real time;

[0057] Step 3: The strain signal monitoring unit monitors the strain at the monitoring point of the mounting base structure and feeds it back to the signal processing module in real time;

[0058] Step 4: After the data is sampled and collected, it is transmitted to the data analysis unit, which analyzes the received acceleration signal, velocity signal and strain signal.

[0059] Step 5: Issue an alarm based on the degree of structural damage analyzed.

[0060] Reference Figure 2 In step 4, the data analysis unit performs modal simulation analysis on the finite element model of the mounting base constructed in the system through the received signal. The mode shape is used as a sensitive identification index for local damage. By analyzing the three modes of acceleration, velocity and dynamic strain, the corresponding displacement mode and strain mode are obtained.

[0061] Specifically, the frequency response functions of the structure's displacement, acceleration, and strain satisfy the following relationships:

[0062]

[0063]

[0064]

[0065] In the formula: These are the displacement mode shape and strain mode shape of the i-th mode, respectively; M i For modal mass; w i ξ i , where i is the i-th modal frequency and damping ratio, respectively; i is the imaginary unit; Nm is the total number of modal orders of the structure.

[0066] Based on the interrelationships between the different mode shapes, the constructed hybrid mode shape satisfies the following relationship:

[0067]

[0068] Where: h, ε, These represent the mixed mode, strain mode, and displacement mode, respectively; I is the identity matrix.

[0069] Since existing modal analysis methods face significant challenges in accurately acquiring higher-order modes, the data analysis unit selects only the first three modes, i.e., N, when analyzing the data. m =3 for analysis. The assumed stiffness-damage factor is used as the data label, and the displacement modes... strain mode Φ ε and mixed mode Φ h The training dataset is constructed using the input data of the BP neural network; the training input neural network is then trained until the loss function converges to obtain the trained neural network.

[0070] Step 4.4 involves real-time acquisition of the displacement modes of the cabin structure. strain mode Φ ε and mixed mode Φ h Input the trained neural network to obtain the predicted stiffness damage factor.

[0071] Specifically, the implementation of step 4 includes the following sub-steps:

[0072] Step 4.1: Perform modal testing on the mounting base. The data analysis unit performs modal analysis on the collected signals to obtain the natural frequencies and mixed mode shapes of the mounting base.

[0073] Step 4.2: Import the stiffness damage factor vector as an input variable into the finite element model of the mounting base, and calculate the structural frequency, displacement mode, and strain mode; Step 4.3: Based on the constructed mixed mode shape, calculate the mixed modes of the model under the assumed damage factor:

[0074]

[0075] Step 4.4

[0076] The modal analysis results of the measured data and the structural natural frequencies and mixed modes calculated by the numerical model are input into the following objective function:

[0077]

[0078]

[0079]

[0080] In the formula: λ represents the corresponding state modal frequency, and the subscripts mea and est indicate measurement and calculation, respectively; N m N represents the total modal order; s This represents the sum of the number of all sensors, including accelerometers and strain gauges; w f,i w φ,i For each weight coefficient, in the weight coefficient value test, the two values ​​in the objective function are on the same order of magnitude;

[0081] Step 4.5: After completing the calculation of the objective function, determine whether the function value meets the convergence condition: if the convergence condition is met, output the value and determine the damage status of the structure based on the output damage factor vector; if the convergence condition is not met, modify the damage factor vector and perform a new round of calculation.

[0082] In the technical solution of this invention, the service status is judged by comprehensively collecting acceleration signals, velocity signals and strain signals, which can greatly simplify the testing process and reduce experimental costs.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A dynamic strength testing system for cabin structures, characterized in that, It includes a monitoring unit, a data receiving unit, a data preprocessing unit, a data analysis unit, and a data output unit; The monitoring unit is used to obtain monitoring signals from monitoring points on the aircraft's electronic component mounting base; the monitoring signals include acceleration signals, velocity signals, and strain signals; the data receiving unit is used to receive the monitoring signals and forward them to the data preprocessing unit, which normalizes the monitoring signals and then sends them to the data analysis unit. The data analysis unit analyzes the received acceleration, velocity, and strain signals to obtain the corresponding displacement and strain modes, and then obtains the damage factor vector based on the displacement and strain modes. The data output unit is used to output damage factor vectors to obtain the damage status of the cabin structure; the overall geometric shape of the tail section of the cabin structure is a frustum; the monitoring unit is installed on the cabin structure via a mounting base structure; the overall geometric shape of the mounting base structure is a Z-shaped plate structure with uniform plate thickness, and the top surface and side feet are square, with three bolt holes evenly distributed on each side foot; the monitoring unit includes a velocity signal monitoring unit, an acceleration signal monitoring unit, and a strain signal monitoring unit; the velocity signal monitoring unit consists of several velocity sensors; the acceleration signal monitoring unit consists of several acceleration sensors; the strain signal monitoring unit consists of several strain gauges. The steps for performing dynamic strength testing of the cabin structure using the cabin structure dynamic strength testing system are as follows: Step 1: The acceleration signal monitoring unit monitors the acceleration of the monitoring point of the mounting base structure and feeds it back to the signal processing module in real time; Step 2: The speed signal monitoring unit is used to monitor the speed of the monitoring point of the mounting structure and feed it back to the signal processing module in real time; Step 3: The strain signal monitoring unit monitors the strain at the monitoring point of the mounting base structure and feeds it back to the signal processing module in real time; Step 4: After sampling and collecting acceleration, velocity and strain data, the data is transmitted to the data analysis unit. The data analysis unit analyzes the received acceleration signal, velocity signal and strain signal to obtain the predicted stiffness damage factor. Step 5: Compare the predicted stiffness damage factor with a preset threshold. If the predicted stiffness damage factor is greater than the preset threshold, issue an alarm. The method for obtaining the predicted stiffness damage factor is as follows: Step 4.1: Perform modal testing on the mounting base. The data analysis unit performs modal analysis on the collected signals to obtain the natural frequencies and mixed mode shapes of the mounting base. Step 4.2: The assumed stiffness damage factor vector is used as an input variable and imported into the finite element model of the mounting base. The data analysis unit calculates the natural frequency, displacement mode and strain mode of the cabin structure. Step 4.3: Based on the constructed mixed mode shapes, calculate the mixed modes of the assumed stiffness-damage factor lower limit element model. The mixed mode shapes are as follows: Φ h For mixed modes, Φ ε For strain modes, S represents the displacement mode; T denotes matrix transpose; S is the transformation matrix between strain and displacement. + Indicates the pseudoinverse of S; I represents the identity matrix, with the assumed stiffness-damage factor used as the data label, and the displacement modes... strain mode Φ ε and mixed mode Φ h The training dataset is constructed using the input data of the BP neural network. The training input is used to train the neural network until the loss function converges, resulting in a well-trained neural network. Step 4.4 involves real-time acquisition of the displacement modes of the cabin structure. strain mode Φ ε and mixed mode Φ h Input the trained neural network to obtain the predicted stiffness damage factor.

2. The cabin structure dynamic strength testing system as described in claim 1, characterized in that, The loss function is as follows: In the formula: λ mea，i Let λ be the natural frequency measured by the i-th strain sensor. est，i (Θ) represents the calculated natural frequency at the location of the i-th sensor; the subscripts mea and est represent measurement and calculation, respectively; N m N represents the total modal order; s This represents the sum of the number of all sensors, including velocity sensors, acceleration sensors, and strain gauge sensors; w f,i w φ,i For each weight coefficient, in the weight coefficient value test, the two values ​​in the objective function are on the same order of magnitude; φ mea，ij This represents the mixed mode measured between the i-th and j-th sensors; φ est，ij (Θ) represents the predicted mixed mode between the i-th and j-th sensors; f(Θ) represents the total error between the actual strength value and the predicted strength value of the cabin structure, R f,i (Θ) represents the error between the actual element modal frequency and the predicted element modal frequency. This represents the error between the actual element mode shape and the predicted element mode shape.

3. The cabin structure dynamic strength testing system as described in claim 1, characterized in that, The method for constructing the hybrid mode shape is as follows: Structural displacement frequency response function H x (w) Structural acceleration frequency response function and structural strain frequency response function H ε (w) respectively satisfy the following relations: The three formulas above are simplified to: H x (w)=Φ T F * (w) H ε (w)=(S + F) T F * (w) Based on the interrelationships between different mode shapes, the following hybrid mode shapes are constructed: in, These are the displacement mode shape and the strain mode shape of the k-th mode, respectively; M k For modal mass; w k ζ k Let h and ε represent the k-th modal frequency and damping ratio, respectively; T denotes matrix transpose; Nm is the total modal order, i is the imaginary unit; S is the transformation matrix between strain and displacement, where h, ε, and ε are the modal frequencies and damping ratios, respectively. These represent mixed modes, strain modes, and displacement modes, respectively.

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