Method, device and equipment for determining ice thickness of plate structure

Abstract

The application provides a method, device and equipment for determining the ice thickness of a plate structure, and the method comprises the following steps: acquiring a real-time passive guided wave signal of the plate structure in an icing state; acquiring a sensitivity index of a preset dispersion curve of the plate structure at a preset frequency; obtaining a fitting dispersion curve of the plate structure according to the passive signal; and determining the ice thickness on the plate structure according to the fitting dispersion curve, the preset dispersion curve and the sensitivity index. The scheme provided by the application does not require a guided wave excitation device, improves the real-time performance and accuracy of the ice thickness detection on the plate structure, and reduces the detection cost and complexity.

Description

Technical Field

[0001] This invention relates to the field of plate structure health monitoring technology, and in particular to a method, apparatus and equipment for determining the icing thickness of a plate structure. Background Technology

[0002] Currently, to understand the icing situation of an aircraft during flight, pilots can visually estimate the presence and amount of ice. However, pilots typically have poor visibility, so they can only roughly infer the overall icing situation of the aircraft, such as the wings and engines, based on the icing on the windshield and wipers. Meanwhile, various icing detectors installed on aircraft have been developed extensively.

[0003] For example, a vibrating rod extended into the airflow is used to detect changes in the rod's resonant frequency caused by ice buildup. This detector obtains the corresponding resonant frequency by driving the vibrating rod's magnetostriction with alternating current and a magnetic field. This is currently the most widely used ice detection technology on aircraft. Other invasive sensors can detect icing by sensing changes in stiffness, dielectric constant, or impedance. The measurement of these parameters usually requires triggering with alternating current or control electronics. When ice accumulates around the sensor, microwave technology can detect frost and ice by sensing changes in characteristic electromagnetic resonances. However, all of the above detectors require direct contact with the ice, so they must be mounted flat on the outer surface of the fuselage, affecting the aircraft's aerodynamic characteristics, and can only detect a localized area near the detector. In addition, fiber optic sensors can be installed on the wings, but a transparent window is needed to measure light diffusion in the ice to detect the ice thickness and type. However, this method is not sensitive to open ice, and the detection area is limited.

[0004] Active guided wave detection technology has a wide detection range and is also used for icing detection. However, it requires signal generating equipment to produce a controllable excitation source. This equipment is large, heavy, and energy-intensive, which can affect the structural integrity of the aircraft and increase reliability risks. Therefore, current active guided wave methods cannot be truly used for online aircraft monitoring. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method, apparatus and equipment for determining the icing thickness of a plate-shaped structure. It does not require waveguide excitation equipment and can detect the icing thickness of the plate-shaped structure in real time using only environmental noise, thereby improving the real-time performance and accuracy of aircraft icing thickness detection and reducing detection costs and complexity.

[0006] To address the aforementioned technical problems, embodiments of the present invention provide a method for determining the icing thickness of a plate-like structure, comprising:

[0007] Acquire real-time passive guided wave signals of a plate-like structure in an icing state;

[0008] Obtain the sensitivity index of the preset dispersion curve of the plate-like structure at a preset frequency;

[0009] Based on the passive waveguide signal, the fitted dispersion curve of the plate structure is obtained;

[0010] The thickness of the ice layer on the plate-like structure is determined based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index.

[0011] Optionally, acquiring the real-time passive guided wave signal of the plate-like structure in an icing state includes:

[0012] Using a first signal receiver, the first passive guided wave signal generated by the plate structure based on environmental noise is acquired in real time.

[0013] The second signal receiver is used to acquire the second passive guided wave signal generated by the plate structure based on the ambient noise in real time. The first signal receiver and the second signal receiver are integrated in the plate structure.

[0014] Optionally, based on the passive waveguide signal, the fitted dispersion curve of the plate-like structure is obtained, including:

[0015] Based on the first passive waveguide signal and the second passive waveguide signal, a cross-correlation signal is obtained;

[0016] Based on the cross-correlation signal, the fitted dispersion curve of the plate-like structure is obtained.

[0017] Optionally, based on the cross-correlation signal, the fitted dispersion curve of the plate-like structure is obtained, including:

[0018] The cross-correlation signal is preprocessed to obtain a preprocessed cross-correlation signal;

[0019] Determine the set of group velocities of the preprocessed cross-correlation signals at the preset frequency;

[0020] The fitted dispersion curve is obtained based on the group velocity set.

[0021] Optionally, determining the set of group velocities of the preprocessed cross-correlation signal at the preset frequency includes:

[0022] When the preprocessed cross-correlation signal is at its peak value at the preset frequency, the propagation time of the passive guided wave signal between the first signal receiver and the second signal receiver is determined.

[0023] Based on the distance between the first signal receiver and the second signal receiver, and the propagation time of the passive guided wave signal, the set of group velocities of the preprocessed cross-correlation signal at the preset frequency is determined.

[0024] Optionally, obtaining the sensitivity index of the preset dispersion curve of the plate-like structure at a preset frequency includes:

[0025] Obtain the first sensitivity index of the preset dispersion curve at the preset frequency;

[0026] Based on the first sensitivity index, determine the second sensitivity index corresponding to the preset dispersion curve at the preset frequency.

[0027] Optionally, the thickness of the ice layer on the plate-like structure is determined based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index, including:

[0028] Obtain the distance between the fitted dispersion curve and the preset dispersion curve at the preset frequency;

[0029] The thickness of the ice layer is determined based on the distance and the sensitivity index.

[0030] Embodiments of the present invention also provide a device for determining the thickness of ice covering a plate-like structure, comprising:

[0031] The first acquisition module is used to acquire the real-time passive waveguide signal of the plate structure in the icing state;

[0032] The second acquisition module is used to acquire the sensitivity index corresponding to the preset dispersion curve of the plate structure at a preset frequency.

[0033] The processing module is used to obtain the fitted dispersion curve of the plate structure based on the passive guided wave signal; and to determine the thickness of the ice layer on the plate structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index.

[0034] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described in any of the preceding embodiments.

[0035] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described in any of the preceding descriptions.

[0036] The above-described solution of the present invention has at least the following beneficial effects:

[0037] The above-described solution of the present invention obtains the real-time passive guided wave signal of the plate-like structure in an icy state; obtains the sensitivity index corresponding to the preset dispersion curve of the plate-like structure at a preset frequency; obtains the fitted dispersion curve of the plate-like structure based on the passive guided wave signal; and determines the thickness of the ice layer on the plate-like structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index, so as to detect the ice thickness on the plate-like structure in real time and accurately, thereby reducing detection costs and complexity. Attached Figure Description

[0038] Figure 1 This is a schematic flowchart of the method for determining the ice thickness of a plate-shaped structure provided in an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the module block of the device for determining the ice thickness of a plate-shaped structure provided in an embodiment of the present invention. Detailed Implementation

[0040] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0041] like Figure 1 The present invention provides a method for determining the icing thickness of a plate-like structure, comprising:

[0042] Step 11: Obtain the real-time passive guided wave signal of the plate structure in the icing state;

[0043] Step 12: Obtain the sensitivity index corresponding to the preset dispersion curve of the plate structure at a preset frequency;

[0044] Step 13: Obtain the fitted dispersion curve of the plate structure based on the passive waveguide signal;

[0045] Step 14: Determine the thickness of the ice layer on the plate structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index.

[0046] In this embodiment, under surface icing conditions, the plate-like structure and the ice layer condensed on its surface form a multi-layered integrated structure. The plate-like structure is widely used in the airframe structure of aircraft (such as the outer shell skin). During the flight of the aircraft, the plate-like structure and the ice layer accumulated on the surface are regarded as a multi-layered integrated structure. Therefore, the sensor does not need to be in direct contact with the accumulated ice layer, avoiding the need to install the icing detector on the surface of the aircraft and ensuring that the aerodynamic characteristics of the aircraft are not affected.

[0047] The passive guided wave signal is generated by the propagation of environmental noise (such as flow-induced random vibration) naturally excited during the flight of an aircraft in the structure. It carries a large amount of structural state information and can propagate in various components of the aircraft. In this application, the passive guided wave signal has the advantages of long detection distance and high sensitivity, making it an effective tool for structural health monitoring and non-destructive testing. At the same time, using the passive guided wave signal excited by environmental noise to detect the icing status of plate structures in real time can avoid the trouble of active guided wave transmission equipment, requires no energy supply, and can minimize the power consumption and cost of monitoring, while avoiding the failure risk caused by complex power supply systems.

[0048] Here, the preset dispersion curve of the plate-like structure is a theoretical dispersion curve obtained based on the physical model; here, the preset frequency is a frequency set according to actual needs, and each preset frequency can be assigned a sensitivity index; the sensitivity index represents the sensitivity of the guided wave group velocity to changes in ice thickness at different preset frequencies;

[0049] Furthermore, based on the real-time acquired passive guided wave signal, the fitting dispersion curve corresponding to the plate-like structure in the icing state can be determined; in practical applications, the passive guided wave signal is the guided wave signal received by the aircraft during flight within a preset signal acquisition time; it should be understood that the fitting dispersion curve is the dispersion curve corresponding to the overall structure of a multi-layer medium consisting of the plate-like structure in the icing state and the ice layer condensed on its surface.

[0050] Furthermore, based on the distance relationship between the preset dispersion curve and the fitted dispersion curve at a preset frequency, and the sensitivity index at the corresponding preset frequency, the thickness of the ice layer on the current plate structure can be obtained.

[0051] Based on the preset dispersion curve obtained from the physical model and the fitted dispersion curve under actual conditions, real-time detection of ice thickness on plate-like structures can be achieved. Simultaneously, based on the passive guided wave signal generated by environmental noise, high-power devices such as guided wave active transmitters can be discarded, improving the practicality and convenience of guided wave icing detection for aircraft and reducing the cost of ice thickness detection. Through the above method, real-time online monitoring of ice thickness on plate-like structures of aircraft can be achieved. Here, aircraft include, but are not limited to, airplanes; the method of this invention can also be used to detect the icing thickness of other aircraft during flight.

[0052] In an optional embodiment of the present invention, step 11 above may include:

[0053] Step 111: Using a first signal receiver, acquire in real time the first passive guided wave signal generated by the plate structure based on environmental noise;

[0054] Step 112: Using a second signal receiver, acquire in real time the second passive guided wave signal generated by the plate structure based on environmental noise. The first signal receiver and the second signal receiver are integrated into the plate structure.

[0055] In this embodiment, the first signal receiver and the second signal receiver are used to receive passive guided wave signals generated by environmental noise excitation on the plate structure. The first signal receiver and the second signal receiver can be small in size, lightweight, and require little or no energy supply; for example, piezoelectric sensors and fiber Bragg gratings (FBGs). The first signal receiver and the second signal receiver can be integrated into the fuselage structure of the aircraft in a very low-invasive manner, which can ensure the maximum integrity of the aircraft fuselage structure and greatly reduce energy loss in the ice thickness detection process. Here, the first signal receiver and the second signal receiver can be integrated into the structure at a preset distance, which can be set according to actual needs. Here, "first" and "second" only define the names of the signal receivers and do not define the order in which they perform their functions. When receiving the passive guided wave signals generated by environmental noise excitation on the plate structure, the first signal receiver and the second signal receiver receive the signals synchronously and in real time.

[0056] It should be understood that environmental noise (such as flow-induced random vibration) excites one side of the aircraft fuselage structure, and the passive guided wave signal in the structure mainly propagates in the A0 antisymmetric mode at lower frequencies. Since the guided wave has dispersion characteristics in the plate structure, that is, the group velocity of the guided wave propagation is different at different frequencies, and the passive guided wave signal excited by environmental noise is a broadband signal, in order to estimate the group velocity of the guided wave at different frequencies, it is necessary to perform bandpass filtering on the original cross-correlation signal to obtain the filtered cross-correlation signal.

[0057] In an optional embodiment of the present invention, step 12 above may include:

[0058] Step 121: Obtain the first sensitivity index of the preset dispersion curve at the preset frequency;

[0059] Step 122: Determine the second sensitivity index corresponding to the preset dispersion curve at the preset frequency based on the first sensitivity index.

[0060] In this embodiment, the first sensitivity index is the local sensitivity of the waveguide group velocity of the preset dispersion curve to changes in ice thickness at different preset frequencies, and the second sensitivity index is the global sensitivity of the waveguide group velocity of the preset dispersion curve to changes in ice thickness at different preset frequencies.

[0061] Since the sensitivity of the waveguide group velocity to ice accumulation varies at different preset frequencies in the A0 antisymmetric mode in the low-frequency range, the first sensitivity index can be obtained by the following formula when the preset thickness of the ice layer is x:

[0062]

[0063] Here, S1 represents the first sensitivity index, C g (f cn ;x) represents the preset frequency curve, f cn This represents the nth preset frequency, where n = 1, ..., N are positive integers, and ε is a set small positive value; the preset frequency f cn Multiple different values ​​can be set according to actual needs, and each preset frequency and preset ice thickness can be assigned a first sensitivity index.

[0064] In practical applications, the thickness of the ice layer on the fuselage can range from several centimeters to a very wide range. Therefore, the global sensitivity of the waveguide group velocity to ice accumulation over a large ice thickness range must be considered. Since the ice thickness is non-negative in reality, if we further assume that the average ice thickness in the ice detection scenario is β, according to the maximum entropy principle, the optimal distribution of the ice thickness is an exponential distribution. Preferably, the exponential distribution of the ice thickness can be expressed as:

[0065]

[0066] Furthermore, by simulating the exponential distribution of the ice thickness using a preset simulation algorithm, different ice thickness samples x can be obtained. n Where n = 1, ..., N are positive integers; here, the preset simulation algorithm can be a Monte Carlo simulation algorithm;

[0067] Furthermore, the second sensitivity index can be expressed as:

[0068]

[0069] By extracting sensitivity indices at different theoretically preset frequencies, the accuracy of ice layer thickness detection can be improved.

[0070] In an optional embodiment of the present invention, the preset dispersion curve can be obtained through the following steps:

[0071] Step 21: Set the thickness, density, Lamé constant, and shear modulus of the ice layer as h2, ρ2, λ2, and μ2, respectively.

[0072] Step 22: Set the thickness, density, Lamé constant, and shear modulus of the plate layer as h1, ρ1, λ1, and μ1, respectively.

[0073] Step 23, the four partial waves of the Rayleigh-Lamb type in the ice layer (Z+shear, Z-shear, Z+longitudinal, Z-longitudinal, where Z is the direction perpendicular to the plate) are represented as follows:

[0074]

[0075]

[0076]

[0077]

[0078] Among them, C P =ω / k, C P The phase velocity of the guided wave is denoted by ω, the preset angular frequency of the guided wave is denoted by k, and the preset wave number of the guided wave is denoted by k. The group velocity is the propagation speed of a point with certain characteristics (such as maximum amplitude) on the envelope of the guided wave signal. It is the energy propagation speed of the wave group. Generally speaking, the group velocity is the propagation speed of a family of waves with similar frequencies. The phase velocity is the propagation speed of a point on the wave with a fixed phase in the direction of propagation.

[0079] Step 24, the four Rayleigh-Lamb type partial waves in the plate layer (Z+shear, Z-shear, Z+longitudinal, Z-longitudinal, where Z is the direction perpendicular to the plate) are represented as follows:

[0080]

[0081]

[0082]

[0083]

[0084] Step 25: Given a preset angular frequency, search according to the preset condition f(k)=|Y|=0 to determine the preset wavenumber k that satisfies the condition. Then, the theoretical preset dispersion curve C under the ice-plate structure can be obtained. g (f cn ;x), where the specific expression for Y is as follows: i is the imaginary unit, and the square of i is -1;

[0085]

[0086] In an optional embodiment of the present invention, step 13 above may include:

[0087] Step 131: Obtain the cross-correlation signal based on the first passive waveguide signal and the second passive waveguide signal;

[0088] Step 132: Obtain the fitted dispersion curve of the plate-like structure based on the cross-correlation signal.

[0089] In this embodiment, the first passive waveguide signal can be represented as a discrete-time signal a1(n·ΔT) through continuous signal sampling, and the second passive waveguide signal can be represented as a discrete-time signal a2(n·ΔT); where ΔT represents the sampling time interval, and n = 1, ..., N are positive integers; since the first signal receiver and the second signal receiver are arranged at a preset distance, the passive waveguide signal is collected and received by the first signal receiver and then continues to propagate to the second signal receiver for collection and reception. Therefore, the first passive waveguide signal and the second passive waveguide signal are correlated and there is a lag time, i.e., the waveguide propagation time. The first passive waveguide signal and the second passive waveguide signal are cross-correlated to obtain the peak value with the strongest correlation in the cross-correlation signal. The time corresponding to this peak value is the waveguide propagation time between the two signal receivers. Subsequently, based on the cross-correlation signal, the fitting dispersion curve of the plate structure in the icy state is determined, thereby accurately estimating the thickness of the ice layer on the plate structure;

[0090] In one feasible example of the present invention, the first passive waveguide signal and the second passive waveguide signal are cross-correlated to obtain the cross-correlation signal, which can be obtained by the following formula:

[0091]

[0092] Among them, C 12 (t) represents the cross-correlation signal, where t represents a preset time interval. The cross-correlation signal is obtained by gradually shifting a discrete-time signal and repeatedly calculating the correlation between the two signals. It should be noted that, under ideal conditions, the cross-correlation signal converges to the impulse response (Green's function) between the two signal receivers.

[0093] In an optional embodiment of the present invention, step 132 above may include:

[0094] Step 1321: Preprocess the cross-correlation signal to obtain the preprocessed cross-correlation signal;

[0095] Step 1322: Obtain the set of group velocities of the preprocessed cross-correlation signals at the preset frequency;

[0096] Step 1323: Obtain the fitted dispersion curve based on the group velocity set.

[0097] In this embodiment, since the passive waveguide signal has dispersion characteristics when propagating in the plate structure, in order to estimate the propagation speed of the guided wave in the plate structure at different preset frequencies, it is necessary to perform cross-correlation processing on the first passive waveguide signal and the second passive waveguide signal, and to preprocess the obtained cross-correlation signal.

[0098] Here, the preprocessing can be bandpass filtering. By setting different preset frequencies (the center frequency of the bandpass filter), frequency components of the signal within the preset frequency range are retained, while frequency components outside the preset frequency are attenuated to extremely low levels, thereby obtaining a filtered (preprocessed) cross-correlation signal to ensure the accuracy of subsequent group velocity extraction based on the preprocessed cross-correlation signal. Each time a preset frequency (the center frequency of the bandpass filter) is set and the cross-correlation signal is preprocessed with bandpass filtering, a preprocessed cross-correlation signal is obtained. The preprocessed cross-correlation signal can be expressed as: C 12 (t;f cn ), where f cn This represents the nth preset frequency, where n = 1, ..., N are positive integers;

[0099] Furthermore, step 1322 above may include:

[0100] Step 13221: Determine the propagation time of the passive guided wave signal between the first signal receiver and the second signal receiver when the preprocessed cross-correlation signal is at its peak value at the preset frequency;

[0101] Step 13222: Based on the distance between the first signal receiver and the second signal receiver, and the propagation time of the passive guided wave signal, obtain the group velocity set corresponding to the preprocessed cross-correlation signal at the preset frequency.

[0102] In this embodiment, since the first signal receiver and the second signal receiver are set at a preset distance, and the propagation speed of the guided wave is different at different preset frequencies when the cross-correlation signal is filtered according to different preset frequencies, the propagation time of the guided wave between the two signal receivers is also different at different preset frequencies. The propagation time of the guided wave between the two signal receivers can be determined by extracting the time corresponding to the signal peak value of the preprocessed cross-correlation signal at the corresponding preset frequency.

[0103] Furthermore, based on the corresponding propagation time at the corresponding preset frequency and the preset distance between the first signal receiver and the second signal receiver, the group velocity of the passive waveguide signal at the corresponding preset frequency can be determined. One preset frequency corresponds to one group velocity. By setting different preset frequencies, the set of group velocities at different preset frequencies can be obtained.

[0104] Preferably, the group velocity can be calculated using the following formula:

[0105] C g (f cn )=||r1-r2|| / t(f cn );

[0106] Among them, C g (f cn ) represents the group velocity at the corresponding preset frequency, t(f cn ) represents the propagation time of the passive guided wave signal between the two signal receivers, i.e., the flight time of the guided wave, and ||r1-r2|| represents the preset distance between the first signal receiver and the second signal receiver.

[0107] In one implementable example of the present invention, step 1323 above may include:

[0108] Step 13231, construct the fitting curve C g (f cn )′=P1 ln(f cn )+P2; where P1 and P2 are both preset fitting coefficients;

[0109] Step 13232: Based on the group velocity at the corresponding preset frequency, the mean square error of the fitted curve can be obtained using the following formula.

[0110]

[0111] Step 13233: Based on the principle of minimum value, the fitting coefficients P1 and P2 in the mean square error of the above formula can be determined by the following formula;

[0112]

[0113] Step 13234: Substitute the calculated fitting coefficients into the above fitting curve to obtain the fitting dispersion curve;

[0114]

[0115] In an optional embodiment of the present invention, step 14 above may include:

[0116] Step 141: Obtain the distance between the fitted dispersion curve and the preset dispersion curve at the preset frequency;

[0117] Step 142: Determine the thickness of the ice layer based on the distance and the sensitivity index.

[0118] In this embodiment, the sensitivity index is a second sensitivity index; the thickness of the ice layer on the plate structure is determined by minimizing the distance between the fitted dispersion curve obtained by passive measurement of flow-induced random vibration and the preset dispersion curve of the theoretical free parameter x of ice thickness, and by using the second sensitivity index to assign weight coefficients to the distance at different preset frequencies.

[0119] Preferably, the thickness of the ice layer on the plate-like structure can be calculated using the following formula:

[0120]

[0121] in, The distance between the fitted dispersion curve and the preset dispersion curve with ice thickness x at the corresponding preset frequency is represented by argmin. argmin represents the parameter with the minimum value, i.e., the parameter x corresponding to the minimum value of the right-hand side of the above formula is the thickness of the ice layer on the plate structure.

[0122] The above-described solution of the present invention acquires real-time passive guided wave signals of a plate-like structure in an icing state using two passive signal receivers; acquires the sensitivity index corresponding to a preset dispersion curve of the plate-like structure at a preset frequency; obtains a fitted dispersion curve of the plate-like structure based on the passive guided wave signals; and determines the thickness of the ice layer on the plate-like structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index, thereby achieving real-time online monitoring of the ice layer thickness.

[0123] The plate-like structure in this solution can be applied to the fuselage of aircraft. During flight, ice forms on the fuselage. The environmental noise generated during flight is used to excite random passive guided wave signals, such as aerodynamic turbulence, within the plate-like structure, replacing a manually controllable excitation source. This avoids the inconvenience of active guided wave transmission equipment, minimizes power consumption, avoids the failure risk of complex power supply systems, and reduces monitoring costs. Furthermore, the first and second signal receivers are small and lightweight, and do not need to be installed on the icing surface of the aircraft in direct contact with the ice. The first and second signal receivers can be integrated into the plate-like fuselage structure of the aircraft in a very low-invasive manner, ensuring maximum structural integrity and not affecting the aerodynamic characteristics of the aircraft during flight, while significantly reducing energy loss during the detection process.

[0124] like Figure 2 As shown, embodiments of the present invention also provide a device 20 for determining the thickness of ice covering a plate-like structure, comprising:

[0125] The first acquisition module 21 is used to acquire the real-time passive waveguide signal of the plate structure in the icing state;

[0126] The second acquisition module 22 is used to acquire the sensitivity index of the preset dispersion curve of the plate structure at a preset frequency.

[0127] Processing module 23 is used to obtain the fitted dispersion curve of the plate structure based on the passive guided wave signal; and to determine the thickness of the ice layer on the plate structure based on the fitted dispersion curve, the preset dispersion curve and the sensitivity index.

[0128] Optionally, the first acquisition module 21 is used to acquire the real-time passive guided wave signal of the plate-like structure in an icing state, including:

[0129] Using a first signal receiver, the first passive guided wave signal generated by the plate structure based on environmental noise is acquired in real time.

[0130] The second signal receiver is used to acquire the second passive guided wave signal generated by the plate structure based on the ambient noise in real time. The first signal receiver and the second signal receiver are integrated in the plate structure.

[0131] Optionally, the processing module 23 is used to obtain the fitted dispersion curve of the plate-like structure based on the passive waveguide signal, including:

[0132] Based on the first passive waveguide signal and the second passive waveguide signal, a cross-correlation signal is obtained;

[0133] Based on the cross-correlation signal, the fitted dispersion curve of the plate-like structure is obtained.

[0134] Optionally, the processing module 23 is configured to obtain the fitted dispersion curve of the plate-like structure based on the cross-correlation signal, including:

[0135] The cross-correlation signal is preprocessed to obtain a preprocessed cross-correlation signal;

[0136] Determine the set of group velocities of the preprocessed cross-correlation signals at the preset frequency;

[0137] The fitted dispersion curve is obtained based on the group velocity set.

[0138] Optionally, the processing module 23 is used to determine the set of group velocities of the preprocessed cross-correlation signal at the preset frequency, including:

[0139] The propagation time of the passive guided wave signal between the first signal receiver and the second signal receiver is determined when the preprocessed cross-correlation signal is at its peak value at the preset frequency.

[0140] Based on the distance between the first signal receiver and the second signal receiver, and the propagation time of the passive guided wave signal, the set of group velocities of the preprocessed cross-correlation signal at the preset frequency is determined.

[0141] Optionally, the second acquisition module 22 is used to acquire the sensitivity index of the preset dispersion curve of the plate-like structure at a preset frequency, including:

[0142] Obtain the first sensitivity index of the preset dispersion curve at the preset frequency;

[0143] Based on the first sensitivity index, determine the second sensitivity index corresponding to the preset dispersion curve at the preset frequency.

[0144] Optionally, the processing module 23 is used to determine the thickness of the ice layer on the plate-like structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index, including:

[0145] Obtain the distance between the fitted dispersion curve and the preset dispersion curve at the preset frequency;

[0146] The thickness of the ice layer is determined based on the distance and the sensitivity index.

[0147] It should be noted that this device corresponds to the method for determining the ice thickness of the plate-shaped structure described above. All implementation methods in the above method embodiments are applicable to the embodiments of this device and can achieve the same technical effect.

[0148] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0149] Embodiments of the present invention also provide a computer-readable storage medium, comprising: stored instructions, which, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0150] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0151] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0152] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0153] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0154] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0155] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0156] Furthermore, it should be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above-described series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0157] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0158] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining the thickness of ice covering a plate-like structure, characterized in that, include: Acquire real-time passive guided wave signals of a plate-like structure in an icing state; Obtain the sensitivity index of the preset dispersion curve of the plate-like structure at a preset frequency; Based on the passive waveguide signal, the fitted dispersion curve of the plate structure is obtained; The thickness of the ice layer on the plate structure is determined based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index. The acquisition of real-time passive guided wave signals of the plate-like structure in an icing state includes: Using a first signal receiver, the first passive guided wave signal generated by the plate structure based on environmental noise is acquired in real time. Using a second signal receiver, a second passive guided wave signal generated by environmental noise on the plate-like structure is acquired in real time. The first and second signal receivers are integrated into the plate-like structure. The acquisition of the sensitivity index of the preset dispersion curve of the plate-like structure at a preset frequency includes: Obtaining the first sensitivity index of the preset dispersion curve at the preset frequency includes: when the preset thickness of the ice layer is x, the first sensitivity index is obtained by the following formula: ； in, Indicates the first sensitivity index, This represents the preset frequency curve. This represents the nth preset frequency, where n=1, ..., N are positive integers. For a set small positive value; Based on the first sensitivity index, a second sensitivity index corresponding to the preset dispersion curve at the preset frequency is determined, including samples with different ice layer thicknesses. The second sensitivity index is expressed as: ； The process of obtaining the fitted dispersion curve of the plate-like structure based on the passive guided wave signal includes: Based on the first passive waveguide signal and the second passive waveguide signal, a cross-correlation signal is obtained. The first passive waveguide signal is represented as a discrete-time signal a1(n·ΔT), and the second passive waveguide signal is represented as a discrete-time signal a2(n·ΔT). The cross-correlation signal is processed using the following formula: ;in, This represents the cross-correlation signal. Indicates a preset time interval; Based on the cross-correlation signal, the fitted dispersion curve of the plate-like structure is obtained; The determination of the thickness of the ice layer on the plate-like structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index includes: Obtain the distance between the fitted dispersion curve and the preset dispersion curve at the preset frequency; The thickness of the ice layer is determined based on the distance and the sensitivity index.

2. The method for determining the ice thickness of the plate-like structure according to claim 1, characterized in that, Based on the cross-correlation signal, the fitted dispersion curve of the plate-like structure is obtained, including: The cross-correlation signal is preprocessed to obtain a preprocessed cross-correlation signal; Determine the set of group velocities of the preprocessed cross-correlation signals at the preset frequency; The fitted dispersion curve is obtained based on the group velocity set.

3. The method for determining the ice thickness of the plate-like structure according to claim 2, characterized in that, Determining the set of group velocities of the preprocessed cross-correlation signal at the preset frequency includes: When the preprocessed cross-correlation signal is at its peak value at the preset frequency, the propagation time of the passive guided wave signal between the first signal receiver and the second signal receiver is determined. Based on the distance between the first signal receiver and the second signal receiver, and the propagation time of the passive guided wave signal, the set of group velocities of the preprocessed cross-correlation signal at the preset frequency is determined.

4. A device for determining the thickness of ice covering a plate-like structure, characterized in that, include: The first acquisition module is used to acquire the real-time passive waveguide signal of the plate structure in the icing state; The second acquisition module is used to acquire the sensitivity index corresponding to the preset dispersion curve of the plate structure at a preset frequency. The processing module is used to obtain the fitted dispersion curve of the plate structure based on the passive guided wave signal; and to determine the thickness of the ice layer on the plate structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index. The acquisition of real-time passive guided wave signals of the plate-like structure in an icing state includes: Using a first signal receiver, the first passive guided wave signal generated by the plate structure based on environmental noise is acquired in real time. Using a second signal receiver, a second passive guided wave signal generated by environmental noise on the plate-like structure is acquired in real time. The first and second signal receivers are integrated into the plate-like structure. The acquisition of the sensitivity index of the preset dispersion curve of the plate-like structure at a preset frequency includes: Obtaining the first sensitivity index of the preset dispersion curve at the preset frequency includes: when the preset thickness of the ice layer is x, the first sensitivity index is obtained by the following formula: ； in, Indicates the first sensitivity index, This represents the preset frequency curve. This represents the nth preset frequency, where n=1, ..., N are positive integers. For a set small positive value; Based on the first sensitivity index, a second sensitivity index corresponding to the preset dispersion curve at the preset frequency is determined, including samples with different ice layer thicknesses. The second sensitivity index is expressed as: ; The process of obtaining the fitted dispersion curve of the plate-like structure based on the passive guided wave signal includes: Based on the first passive waveguide signal and the second passive waveguide signal, a cross-correlation signal is obtained. The first passive waveguide signal is represented as a discrete-time signal a1(n·ΔT), and the second passive waveguide signal is represented as a discrete-time signal a2(n·ΔT). The cross-correlation signal is processed using the following formula: ;in, This represents the cross-correlation signal. Indicates a preset time interval; Based on the cross-correlation signal, the fitted dispersion curve of the plate-like structure is obtained; The determination of the thickness of the ice layer on the plate-like structure based on the fitted dispersion curve, the preset dispersion curve, and the sensitivity index includes: Obtain the distance between the fitted dispersion curve and the preset dispersion curve at the preset frequency; The thickness of the ice layer is determined based on the distance and the sensitivity index.

5. A computing device, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The system stores instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 3.

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