Aircraft tool force position state detection system, method and device

Abstract

The invention discloses an aircraft tool force position state detection system, method and device. The system comprises an optical fiber strain sensor, a tool positioner, a demodulator, a computer and an aircraft tool, the optical fiber strain sensor is used for acquiring wavelength signals in response to the operation of a user, and transmitting the acquired wavelength signals to the demodulator; the demodulator is used for demodulating the received wavelength signals to obtain strain measurement data matched with the wavelength signals and sending the strain measurement data to the computer; and the computer is used for processing the received strain measurement data by adopting a pre-trained strain prediction model to obtain strain prediction results matched with the strain measurement data and verifying whether the force position state of the aircraft tool is correct or not according to the strain prediction results. By means of the system, the force position state of the aircraft tool can be detected, the detection precision of the force position state of the aircraft tool is improved, and then the assembly precision of the aircraft tool is improved.

Description

Technical Field

[0001] The present invention relates to the field of tooling installation and detection, and particularly to an aircraft tooling force and position state detection system, method and device. Background Art

[0002] Aircraft tooling is one of the essential equipment in the aircraft manufacturing process, mainly used for operations such as positioning, clamping and assembling the aircraft. The force and position state of the aircraft tooling refers to the state of the force and position received by the tooling during operation, which directly affects the assembly accuracy and quality of the aircraft. Therefore, it is very important to detect and control the force and position state of the aircraft tooling in real time.

[0003] Currently, the commonly used methods for detecting the force and position state of aircraft tooling are mainly: establishing an effective aircraft tooling force and position state detection system, analyzing the strain field distribution state of the positioners assembled on the aircraft tooling, and then monitoring the abnormal stress state of the positioners in real time to guide the repair and adjustment of the tooling and the implementation of the aircraft assembly work.

[0004] However, due to the complex structure and large number of aircraft tooling components, the measurement space at the assembly site is narrow and nearly enclosed, making it difficult to set strain measurement points at all strain-sensitive areas on the aircraft tooling during the assembly process. And due to the severe limitation of the measurement space at the assembly site, the number of strain measurement points set is limited, resulting in the inability to detect the force and position state of the strain-sensitive areas without assembled positioners. In summary, the existing aircraft tooling force and position state detection system has a low detection accuracy for the force and position state of the aircraft tooling, which in turn leads to a low assembly accuracy of the aircraft tooling. Summary of the Invention

[0005] The present invention provides an aircraft tooling force and position state detection system, method and device, which can solve the problem that the existing aircraft tooling force and position state detection system has a low detection accuracy for the force and position state of the aircraft tooling, which in turn leads to a low assembly accuracy of the aircraft tooling.

[0006] In a first aspect, an embodiment of the present invention provides an aircraft tooling force and position state detection system, which includes:

[0007] An optical fiber strain sensor, at least one tooling positioner, a demodulator, a computer and an aircraft tooling; the optical fiber strain sensor is arranged on the tooling positioner and is in contact connection with the tooling positioner. The optical fiber strain sensor and the computer are respectively connected to the demodulator through wires, and the tooling positioner is installed at a preset installation position of the aircraft tooling;

[0008] The optical fiber strain sensor is configured to collect wavelength signals in response to a user's operation and transmit the collected wavelength signals to the demodulator;

[0009] The demodulator is used to demodulate the received wavelength signals, obtain strain measurement data matching the wavelength signals, and send the strain measurement data to a computer;

[0010] The computer is used to process the received strain measurement data by using a pre-trained strain prediction model, obtain a strain prediction result matching the strain measurement data, and verify whether the force position state of the aircraft tooling is correct according to the strain prediction result.

[0011] In a second aspect, an embodiment of the present invention provides a method for detecting the force position state of aircraft tooling, and the method includes:

[0012] Receiving the strain measurement data demodulated by the demodulator from the wavelength signals collected by the fiber optic strain sensor;

[0013] Processing the received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching the strain measurement data;

[0014] Verifying whether the force position state of the aircraft tooling is correct according to the strain prediction result.

[0015] In a third aspect, an embodiment of the present invention provides a device for detecting the force position state of aircraft tooling, and the device includes:

[0016] A demodulation data receiving module, configured to receive the strain measurement data demodulated by the demodulator from the wavelength signals collected by the fiber optic strain sensor;

[0017] A strain prediction result obtaining module, configured to process the received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching the strain measurement data;

[0018] A force position state verification module, configured to verify whether the force position state of the aircraft tooling is correct according to the strain prediction result.

[0019] In the technical solution of the embodiment of the present invention, through an optical fiber strain sensor, in response to the operation of the user, wavelength signals are collected, and the collected wavelength signals are transmitted to a demodulator; through the demodulator, the received wavelength signals are demodulated to obtain strain measurement data matching the wavelength signals, and the strain measurement data are sent to a computer; through the computer, a pre-trained strain prediction model is used to process the received strain measurement data to obtain a strain prediction result matching the strain measurement data, and the force position state of the aircraft tooling is verified according to the strain prediction result, which solves the problem that the detection accuracy of the force position state of the aircraft tooling in the prior art is relatively low, and further leads to a relatively low assembly accuracy of the aircraft tooling. It can detect the force position state of the aircraft tooling, improve the detection accuracy of the force position state of the aircraft tooling, and further improve the assembly accuracy of the aircraft tooling.

[0020] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0022] Figure 1 is a schematic structural diagram of a force position state detection system for aircraft tooling according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flowchart of a method for detecting the force position state of aircraft tooling according to Embodiment 2 of the present invention;

[0024] Figure 3 is a schematic structural diagram of a force position state detection device for aircraft tooling according to Embodiment 3 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention shall fall within the protection scope of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such data used can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 It is a schematic structural diagram of an aircraft tooling force and position state detection system provided for Embodiment 1 of the present invention.

[0029] As Figure 1 shown, the system includes: an optical fiber strain sensor 110, a tooling locator 120, a demodulator 130, a computer 140, and an aircraft tooling 150; the optical fiber strain sensor 110 is disposed on the tooling locator 120 and is in contact connection with the tooling locator 120. The optical fiber strain sensor 110 and the computer 140 are respectively connected to the demodulator 130 through wires. The tooling locator 120 is installed at a preset installation position of the aircraft tooling. It should be noted that since the role of the aircraft tooling in the system described in this embodiment is to carry the tooling locator 120 and complete the tooling installation work, and does not involve the detection of the force and position state of the aircraft tooling, so Figure 1 the structural schematic of the aircraft tooling 150 is not included.

[0030] Specifically, in this embodiment, the optical fiber strain sensor 110 is installed on the tooling locator 120 to make it in close contact with the tooling locator 120. Then, the optical fiber strain sensor 110 is connected to the demodulator 130 through a wire to convert the strain signal detected by the sensor into an electrical signal. Finally, the demodulator 130 is connected to the computer 140 through a wire to transmit the electrical signal to the computer 140 for processing and analysis. When installing the tooling locator 120, it needs to be installed at the preset installation position of the aircraft tooling to ensure that the tooling locator 120 can accurately detect the strain condition of the aircraft tooling.

[0031] The optical fiber strain sensor 110 is used to collect wavelength signals in response to the operation of the user and transmit the collected wavelength signals to the demodulator 130;

[0032] Among them, the optical fiber strain sensor 110 can be a fiber grating strain sensor; further, the fiber grating strain sensor belongs to a kind of optical fiber sensor. The sensing process based on the fiber grating obtains sensing information through the modulation of the fiber Bragg wavelength by external physical parameters, and it is a wavelength modulation type optical fiber sensor.

[0033] In this embodiment, the operation of the user can be a signal acquisition command generated by the user through a touch operation; further, the wavelength signal is the strain signal generated by each optical fiber strain sensor 110 after the aircraft tooling installed with multiple optical fiber strain sensors 110 is installed. Those skilled in the art should know that the strain signal generated by the optical fiber sensor in this embodiment is actually a signal in the form of a wavelength; further, the optical fiber sensor can be selected as different types of optical fiber sensors according to different working needs in actual work. This embodiment does not limit the specific type and quantity of the optical fiber sensors.

[0034] The demodulator 130 is used to demodulate the received wavelength signals, obtain strain measurement data matching the wavelength signals, and send the strain measurement data to the computer 140;

[0035] It should be noted that since there are usually multiple optical fiber strain sensors 110 installed on the same aircraft tooling in actual applications, the demodulator 130 will also receive multiple different wavelength signals correspondingly when receiving the wavelength signals. In actual applications, after demodulating the wavelength signals, the demodulator 130 can also bind the information of the optical fiber sensor corresponding to the wavelength signal to the demodulation result of the wavelength signal, obtain the strain measurement data and send it to the computer 140, so as to facilitate relevant personnel to locate the specific position of the optical fiber sensor matching the wavelength signal according to the demodulation result of the wavelength signal; Those skilled in the art should know that the operation of using the demodulator 130 to demodulate the wavelength signal to obtain the strain measurement data and send each strain measurement data to the computer 140 is a mature existing technology, and this embodiment will not elaborate on this.

[0036] The computer 140 is used to process the received strain measurement data by using a pre-trained strain prediction model, obtain a strain prediction result matching the strain measurement data, and verify whether the force position state of the aircraft tooling is correct according to the strain prediction result.

[0037] Among them, the strain prediction model is used to obtain a strain prediction result matching the strain measurement according to the received strain measurement; in this embodiment, since there are points on the aircraft tooling where tooling locators 120 cannot be set, but force and position state detection is required, at this time, the pre-trained strain prediction model can be used to predict the force and position state of the points where measurement is not possible based on the collectable strain measurement data, thereby solving the problem in the prior art that due to severe limitations in the measurement space at the assembly site and the inability to install tooling locators 120, the detection accuracy of the aircraft tooling force and position state detection system for the aircraft tooling force and position state is relatively low.

[0038] In this embodiment, the predicted ideal value corresponding to each tooling locator 120 can be set according to actual needs; when the strain prediction result obtained by processing the strain measurement data corresponding to the tooling locator 120 through the strain prediction model is consistent with the predicted ideal value, it indicates that the force and position state of the aircraft tooling at the position of the tooling locator 120 is correct, otherwise it is incorrect, and the aircraft tooling needs to be reinstalled; further, the predicted ideal value can be set and adjusted by relevant staff according to actual work needs, the type of aircraft tooling, and the specific position of the tooling locator 120, and this embodiment will not elaborate on this.

[0039] In a specific implementation manner of this embodiment, the construction steps of a specific strain prediction model are as follows:

[0040] 1) Based on the strain big data set constructed by pre-simulation, using the simulated strain value of the nodes at the strain measurement points as the input, and the strain values of all other nodes, that is, the strain values at the points where measurement is not possible, as the output to construct the big data set of the locator strain state:

[0041] Ε={(ε ai ,ε bi )|i=1,2,…,k}

[0042] Among them, k is the total number of simulation groups, ε ai is the vector of the strain simulation results of the selected measurement points in the i-th group of simulations, and ε bi is the vector of the strain simulation results of the non-measurable sensitive points in the i-th group of simulations.

[0043] 2) To solve the non-linear mapping relationship between ε ai and ε bi , the following optimization problem is introduced, that is, a support vector machine model is established:

[0044]

[0045]

[0046] Among them, ω is the slope of the optimal hyperplane, b is the intercept of the optimal hyperplane, C is the penalty coefficient, and ξi is the slack variable.

[0047] 3) To better fit the non-linear mapping relationship between the measured points and the strains at the unmeasurable points, the following RBF kernel function is introduced:

[0048] K(ε ai ,ε aj ) = exp(-γg||ε ai -ε aj || 2 )

[0049] γ is the gamma parameter in the kernel function. At the same time, the original optimization problem is transformed into the following dual problem:

[0050]

[0051]

[0052] Furthermore, the optimal solutions ω * and b* of the original problem can be solved as follows:

[0053]

[0054]

[0055] where α * is the optimal solution of α in the dual problem. Grid search is used to optimize the hyperparameters C and γ to ensure the training effect of the model. Finally, the strain prediction model for the sensitive points of the locator aircraft tooling is constructed as:

[0056]

[0057] Among them, is the strain prediction result of the unmeasurable sensitive points.

[0058] It should be noted that the method of constructing a strain prediction model based on a large strain dataset constructed by pre-simulation is a mature existing technology. In this embodiment, only a way of constructing a strain prediction model is provided on the above basis, and the method of constructing a strain prediction model for the large strain dataset constructed by pre-simulation in practical applications is not specifically limited.

[0059] In the technical solution of the embodiment of the present invention, through the fiber optic strain sensor, in response to the operation of the user, the wavelength signal is collected, and each collected wavelength signal is transmitted to the demodulator; through the demodulator, each received wavelength signal is demodulated to obtain strain measurement data matching each wavelength signal, and each strain measurement data is sent to the computer; through the computer, it is used to process each received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching each strain measurement data, and verify whether the force position state of the aircraft tooling is correct according to the strain prediction result, which solves the problem that the detection accuracy of the force position state of the aircraft tooling in the prior art is relatively low, and further leads to the relatively low assembly accuracy of the aircraft tooling. It can detect the force position state of the aircraft tooling, improve the detection accuracy of the force position state of the aircraft tooling, and further improve the assembly accuracy of the aircraft tooling.

[0060] Embodiment 2

[0061] Figure 2 FIG. is a flowchart of a method for detecting the force position state of an aircraft tooling provided by Embodiment 2 of the present invention. This embodiment is applicable to the situation of detecting the force position state of an aircraft tooling. This method can be executed by the computer in the aircraft tooling force position state detection system described in Embodiment 1 of the present invention. The computer in the aircraft tooling force position state detection system can be configured in a terminal or a server with the function of detecting the force position state of the aircraft tooling.

[0062] As Figure 2 shown, the method includes:

[0063] S210. Receive the strain measurement data obtained by demodulating the wavelength signal collected by the fiber optic strain sensor by the demodulator.

[0064] Specifically, when the fiber optic strain sensor collects the wavelength signal, these signals will be transmitted to the receiving demodulator. After receiving these signals, the receiving demodulator will perform demodulation processing on them to obtain the strain measurement data. These strain measurement data can include information such as the magnitude, direction, and change rate of the strain. These data can be used to analyze the force position state of the aircraft tooling to ensure the assembly accuracy and quality of the aircraft.

[0065] S220. Process each received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching each strain measurement data.

[0066] Specifically, a pre-trained strain prediction model is used to process the received strain measurement data to obtain strain prediction results matching the strain measurement data, including: obtaining the historical locator data of the target aircraft tooling, and processing the historical locator data through finite element simulation analysis to obtain a large strain dataset; the large strain dataset includes: measurable nodes, measurable strain values matching the measurable nodes, unmeasurable nodes, and simulated strain values matching the unmeasurable nodes; training a preset algorithm based on the large strain dataset to obtain a strain prediction model matching the target aircraft tooling; and processing the strain measurement data through the strain prediction model to obtain strain prediction results matching the strain measurement data.

[0067] Exemplarily, first, obtain the historical locator data of the target aircraft tooling; wherein, the historical locator data may include information such as the attitude and force conditions of the aircraft tooling at a specific position; then, process the historical locator data through finite element simulation analysis to obtain a large strain dataset; further, in this process, the structural model of the tooling can be divided into a finite number of elements, and the strain value of each element can be calculated; then, construct a strain prediction model according to the large strain dataset. The strain prediction model can be a model based on machine learning algorithms, such as neural networks, support vector machines, etc.; further, when training the strain prediction model, the measurable strain values in the large strain dataset can be used as inputs, and the unmeasurable strain values can be used as outputs, and the model can be trained through a preset algorithm to obtain a strain prediction model matching the target aircraft tooling. Finally, process the strain measurement data through the strain prediction model to obtain strain prediction results matching the strain measurement data.

[0068] Further, the finite element simulation analysis is a numerical method for solving partial differential equations. It discretizes the continuous physical problem into a finite number of elements, solves the partial differential equations on each element, and then combines the solutions of all elements to obtain the solution of the entire physical problem; correspondingly, in this embodiment, the finite element analysis method can be used to obtain a large strain dataset based on the historical locator data; the large strain dataset obtained by the method of this embodiment is richer in data types, larger in data quantity, and more comprehensive than the large strain dataset formed only based on measurable variable values in the prior art.

[0069] On the basis of the above steps, further, a strain prediction model matching the target aircraft tooling is obtained by training a preset algorithm based on a strain big data set, including: constructing various non-linear mapping relationships between measurable nodes and unmeasurable nodes in the strain big data set based on a support vector machine model; processing each non-linear mapping relationship through a particle swarm algorithm to obtain a measurement point combination meeting preset conditions; training the preset algorithm based on grid search and the measurement point combination to obtain a strain prediction model matching the target aircraft tooling.

[0070] S230. Verify whether the force position state of the aircraft tooling is correct according to the strain prediction result.

[0071] Among them, verifying whether the force position state of the aircraft tooling is correct according to the strain prediction result includes: sequentially determining whether each strain prediction result is equal to the strain threshold of the preset installation position of the tooling locator matching the strain prediction result; if there is at least one strain prediction result that is not equal to the strain threshold of the preset installation position of the tooling locator matching the strain prediction result, it is determined that the force position state of the aircraft tooling is incorrect, and a warning prompt is generated and transmitted to a display device for display.

[0072] Further, sequentially determining whether each strain prediction result is less than the strain threshold of the preset installation position of the tooling locator matching the strain prediction result further includes: if there is no at least one strain prediction result that is not equal to the strain threshold of the preset installation position of the tooling locator matching the strain prediction result, it is determined that the force position state of the aircraft tooling is correct, and an installation success prompt is generated and transmitted to a display device for display.

[0073] Further, the warning prompt includes: a warning message, a strain prediction result matching the warning message, and a preset installation position of the tooling locator matching the strain prediction result.

[0074] In this embodiment, since the strain big data set obtained through the above steps is more abundant in data types, larger in data quantity, and more comprehensive than the strain big data set formed only based on measurable variable values in the prior art, when using the strain big data set described in this embodiment to train a preset algorithm, due to the richness of training samples, the strain prediction result obtained by the strain prediction model during prediction is more accurate than that in the prior art, solving the problem of low detection accuracy in the force position detection of aircraft tooling in the prior art.

[0075] Optionally, in this embodiment, the aircraft tooling force position state detection method further includes: randomly generating at least one strain measurement point that meets preset constraint conditions as the preset installation position of each tooling locator.

[0076] Among them, the preset constraint conditions include: the preset installation position is within a preset installation area, the distance between each tooling locator is greater than a preset threshold, and the distance from the preset installation position of each tooling locator to the edge of the aircraft tooling is greater than a preset distance.

[0077] In a specific implementation manner of this embodiment, after setting the above constraint conditions, within the range allowed by the constraint conditions, a random number generation algorithm can be used, such as a uniform distribution random number generator or a normal distribution random number generator, to generate multiple random numbers that meet the conditions as the preset installation positions of each tooling locator.

[0078] The technical solution of the embodiment of the present invention first receives the strain measurement data demodulated by the demodulator from the wavelength signals collected by the fiber optic strain sensors, then uses a pre-trained strain prediction model to process each received strain measurement data to obtain a strain prediction result that matches each strain measurement data, and finally verifies whether the force and position state of the aircraft tooling is correct according to the strain prediction result, realizing the detection of the force and position state of the aircraft tooling, improving the detection accuracy of the force and position state of the aircraft tooling, and further improving the assembly accuracy of the aircraft tooling.

[0079] Embodiment III

[0080] Figure 3 It is a schematic structural diagram of a device for detecting the force and position state of an aircraft tooling provided in Embodiment III of the present invention.

[0081] As Figure 3 shown, the device includes:

[0082] A demodulated data receiving module 310, configured to receive the strain measurement data demodulated by the demodulator from the wavelength signals collected by the fiber optic strain sensors;

[0083] A strain prediction result obtaining module 320, configured to use a pre-trained strain prediction model to process each received strain measurement data to obtain a strain prediction result that matches each strain measurement data;

[0084] A force and position state verification module 330, configured to verify whether the force and position state of the aircraft tooling is correct according to the strain prediction result.

[0085] The technical solution of the embodiment of the present invention first receives the strain measurement data demodulated by the demodulator from the wavelength signals collected by the fiber optic strain sensors, then uses a pre-trained strain prediction model to process each received strain measurement data to obtain a strain prediction result that matches each strain measurement data, and finally verifies whether the force and position state of the aircraft tooling is correct according to the strain prediction result, realizing the detection of the force and position state of the aircraft tooling, improving the detection accuracy of the force and position state of the aircraft tooling, and further improving the assembly accuracy of the aircraft tooling.

[0086] Based on the above embodiments, the strain prediction result acquisition module 320 includes:

[0087] A strain big data set acquisition unit, configured to acquire historical locator data of a target aircraft tooling, and process the historical locator data through finite element simulation analysis to obtain a strain big data set; the strain big data set includes: measurable nodes, measurable strain values matched with the measurable nodes, unmeasurable nodes, and simulated strain values matched with the unmeasurable nodes;

[0088] A strain prediction model training unit, configured to train a preset algorithm based on the strain big data set to obtain a strain prediction model matched with the target aircraft tooling;

[0089] A strain measurement data processing unit, configured to process each strain measurement data through the strain prediction model to obtain a strain prediction result matched with each strain measurement data.

[0090] Based on the above embodiments, the strain prediction model training unit further includes:

[0091] A mapping relationship determination unit, configured to construct non-linear mapping relationships between each measurable node and each unmeasurable node in the strain big data set based on a support vector machine model;

[0092] A particle swarm algorithm unit, configured to process each non-linear mapping relationship through a particle swarm algorithm to obtain a measuring point combination meeting preset conditions;

[0093] An algorithm training unit, configured to train a preset algorithm based on grid search and the measuring point combination to obtain a strain prediction model matched with the target aircraft tooling.

[0094] Based on the above embodiments, the force and position state verification module 330 includes:

[0095] A strain threshold judgment unit, configured to sequentially judge whether each strain prediction result is less than the strain threshold of the preset installation position of the tooling locator matched with the strain prediction result;

[0096] A warning prompt generation unit, configured to, if there is at least one strain prediction result that is not equal to the strain threshold matched with the strain prediction result, judge that the force and position state of the aircraft tooling is incorrect, generate a warning prompt and transmit it to a display device for display.

[0097] Based on the above embodiments, the strain threshold judgment unit is further configured to: if there is no at least one strain prediction result that is not equal to the strain threshold matched with the strain prediction result, judge that the force and position state of the aircraft tooling is correct, generate an installation success prompt and transmit it to a display device for display.

[0098] Based on the above embodiments, the aircraft tooling force and position state detection device further includes: an installation position determination module, configured to randomly generate at least one strain measurement point that satisfies a preset constraint condition as the preset installation position of each tooling locator.

[0099] The aircraft tooling force and position state detection device provided by an embodiment of the present invention can execute the aircraft tooling force and position state detection method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0100] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

Claims

1. An aircraft tooling force and position state detection system, characterized in that, Comprising: An optical fiber strain sensor, at least one tooling locator, a demodulator, a computer, and an aircraft tooling; The optical fiber strain sensor is arranged on the tooling locator and is in contact connection with the tooling locator. The optical fiber strain sensor and the computer are respectively connected to the demodulator through wires, and the tooling locator is installed at a preset installation position of the aircraft tooling; The optical fiber strain sensor is configured to collect wavelength signals in response to a user's operation and transmit the collected wavelength signals to the demodulator; The demodulator is configured to demodulate the received wavelength signals to obtain strain measurement data matching the wavelength signals and send the strain measurement data to the computer; The computer is configured to process the received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching the strain measurement data and verify whether the force-position state of the aircraft tooling is correct according to the strain prediction result.

2. A method for detecting the force and position state of an aircraft tooling, which is executed by a computer in the aircraft tooling force and position state detection system as described in claim 1, characterized in that, Comprising: Receiving the strain measurement data demodulated by the demodulator from the wavelength signals collected by the optical fiber strain sensor; Processing the received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching the strain measurement data; Verifying whether the force-position state of the aircraft tooling is correct according to the strain prediction result.

3. The method according to claim 2, wherein Processing the received strain measurement data by using a pre-trained strain prediction model to obtain a strain prediction result matching the strain measurement data, including: Obtaining each historical locator data of the target aircraft tooling and processing each historical locator data through finite element simulation analysis to obtain a strain big data set; the strain big data set includes: measurable nodes, measurable strain values matching the measurable nodes, unmeasurable nodes, and simulation strain values matching the unmeasurable nodes; Training a preset algorithm based on the strain big data set to obtain a strain prediction model matching the target aircraft tooling; Processing each strain measurement data through the strain prediction model to obtain a strain prediction result matching the strain measurement data.

4. The method according to claim 3, wherein Training a preset algorithm based on the strain big data set to obtain a strain prediction model matching the target aircraft tooling, including: Constructing each non-linear mapping relationship between the measurable nodes and the unmeasurable nodes in the strain big data set based on a support vector machine model; Processing each non-linear mapping relationship through a particle swarm algorithm to obtain a measurement point combination meeting preset conditions; Training a preset algorithm based on grid search and the measurement point combination to obtain a strain prediction model matching the target aircraft tooling.

5. The method according to claim 2, wherein Verifying whether the force-position state of the aircraft tooling is correct according to the strain prediction result, including: Sequentially determining whether each strain prediction result is equal to the strain threshold value of the preset installation position of the tooling locator matching the strain prediction result; If there is at least one strain prediction result that is not equal to the strain threshold value of the strain prediction result matching it, it is determined that the force-position state of the aircraft tooling is incorrect, a warning prompt is generated and transmitted to a display device for display.

6. The method according to claim 5, wherein Sequentially determining whether each strain prediction result is less than the strain threshold value of the preset installation position of the tooling locator matching the strain prediction result, further including: If there is no strain threshold where at least one strain prediction result matches the strain prediction result and they are not equal, it is determined that the force position state of the aircraft tooling is correct, and a successful installation prompt is generated and transmitted to the display device for display.

7. The method according to claim 5, characterized in that The warning prompt includes: a warning message, a strain prediction result that matches the warning message, and a preset installation position of the tooling locator that matches the strain prediction result.

8. The method according to claim 2, characterized in that The aircraft tooling force position state detection method further includes: Randomly generating at least one strain measurement point that satisfies the preset constraint conditions as the preset installation position of each tooling locator.

9. The method according to claim 8, characterized in that The preset constraint conditions include: The preset installation position is within the preset installation area, the distance between each tooling locator is greater than the preset threshold, and the distance from the preset installation position of each tooling locator to the edge of the aircraft tooling is greater than the preset distance.

10. An aircraft tooling force and position state detection device is executed by a computer in the aircraft tooling force and position state detection system as described in claim 1, characterized in that, It includes: A demodulation data receiving module for receiving the strain measurement data obtained by demodulating the wavelength signal collected by the fiber optic strain sensor by the demodulator; A strain prediction result acquisition module for processing the received strain measurement data using a pre-trained strain prediction model to obtain a strain prediction result that matches each strain measurement data; A force position state verification module for verifying whether the force position state of the aircraft tooling is correct according to the strain prediction result.

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