Internal combustion engine vibration reduction method, system and equipment with built-in bent acoustic black hole and medium

Abstract

The invention discloses an internal combustion engine vibration reduction method, system, equipment and medium with built-in bent acoustic black holes, and belongs to the field of vibration reduction and noise reduction of typical excitation sources of internal combustion engines. The bending wave band gap characteristic of the periodic vibration reduction structure is calculated through a first algorithm; based on the frequency spectrum position relation between the bending wave band gap and the target vibration reduction frequency range, generating an adjustment decision for geometric parameters of the parameterized model; the geometric parameters are subjected to collaborative iteration adjustment until the requirement of the target vibration reduction frequency range is met; and outputting a final structure parameter. Through layered bending design, a plurality of acoustic black holes act at the same time, a more complex wave mode conversion effect is excited, and broadband efficient vibration reduction is achieved. In the buoyant raft system, the frequency collaborative design of acoustic black hole local energy absorption area and periodic band gap vibration reduction is achieved, a double vibration reduction barrier is formed through an energy coupling and band gap overlapping mechanism, and the low-frequency attenuation capacity of the structure is enhanced.

Description

Technical Field

[0001] This invention relates to the field of vibration reduction and noise reduction technology for typical excitation sources of internal combustion engines, specifically to a vibration reduction method, system, device and medium for internal combustion engines with a built-in bending acoustic black hole. Background Technology

[0002] As a key piece of equipment in modern transportation and national defense, the vibration and noise levels of internal combustion engines directly affect the operational reliability of equipment, the fatigue life of structures, passenger comfort, and especially the acoustic stealth performance of military ships. The wide-frequency, high-energy vibrations generated by internal combustion engines during operation are transmitted to the hull through paths such as the base, ultimately radiating strong structural noise into the surrounding waters.

[0003] To suppress this vibration transmission path, floating raft systems have become one of the most effective technical means in the field of ship vibration reduction and noise reduction. Traditional floating raft systems typically consist of an upper raft frame, a lower raft frame, intermediate isolators, and equipment bases. By integrating multiple vibration devices onto a common elastic raft frame, they utilize the mass effect and the impedance mismatch principle of the isolators to block the transmission of vibration energy. However, with the increasingly stringent requirements for quietness in modern ships, traditional floating raft systems have also revealed some inherent limitations: First, their vibration reduction performance, especially in the low-frequency range, is limited by the stiffness of the isolators and the mass of the raft frame, making it difficult to cope with even lower frequency excitations; second, to obtain sufficient stiffness and mass, the raft frame is often designed to be quite bulky, occupying valuable cabin space and contradicting the concept of lightweight ship design; third, as an elastic structure, the raft frame itself generates bending waves when excited. These waves propagate, reflect, and even converge within the raft frame, potentially forming "hot spots," causing vibration energy to concentrate in certain local locations, which not only reduces the overall vibration reduction effect but may also induce structural fatigue.

[0004] The acoustic black hole effect is a cutting-edge concept in structural vibration control in recent years. Its basic principle is to gradually reduce the wave velocity of bending waves by changing the geometry of the structure (e.g., gradually decreasing the thickness of components according to a power law). Theoretically, the wave velocity can be reduced to zero under ideal conditions, thus achieving efficient concentration of vibration energy without reflection. Subsequently, adding a small amount of damping material to the tip region of the black hole can efficiently dissipate the concentrated energy. This concept provides a completely new approach to lightweight and efficient vibration control. However, traditional acoustic black hole designs are mostly applied directly to simple structures such as flat plates and beams. How to innovatively integrate this advanced wave regulation mechanism into complex floating raft systems to solve the problems of localized vibration energy concentration, insufficient low-frequency control, and the contradiction between weight and performance remains a challenge, and mature and effective solutions are still lacking.

[0005] Therefore, there is an urgent need in this field for an innovative floating raft structure and design method that can overcome the above-mentioned defects of traditional floating rafts, and achieve efficient suppression and dissipation of broadband vibration, especially low-frequency vibration energy, while ensuring a compact and lightweight structure. Summary of the Invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by this invention is: how to overcome the shortcomings of traditional floating raft systems, such as insufficient low-frequency vibration reduction performance, bulky structure, and easy formation of vibration hotspots, and to solve the technical problem of the difficulty in effectively integrating acoustic black holes into complex floating raft structures, thereby providing an internal combustion engine vibration reduction scheme that can achieve a compact and lightweight structure and has efficient suppression and dissipation capabilities for broadband, especially low-frequency vibrations.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole, comprising, Obtain the target vibration reduction frequency range for the internal combustion engine; Construct a parameterized model of a periodic vibration reduction structure containing a bending acoustic black hole; Based on the theory of elastic wave dynamics, the bending wave bandgap characteristics of a periodic vibration reduction structure are calculated using the first algorithm. Based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range, adjustment decisions are generated for the geometric parameters of the parameterized model. Based on the adjustment decision, the geometric parameters are adjusted iteratively until the bending wave bandgap meets the requirements of the target vibration reduction frequency range; Output the final structural parameters that meet the target vibration reduction requirements; The curved acoustic black hole is embedded as an energy-consuming unit within a single cell of a periodic structure.

[0009] As a preferred embodiment of the internal combustion engine vibration reduction method with a built-in bending acoustic black hole described in this invention, wherein: the target vibration reduction frequency range of the internal combustion engine includes... Sensors are placed at all engine mounts of the internal combustion engine to measure vibration signals; The measured vibration signals are preprocessed to obtain vibration characteristics, and all signals are averaged to form a reference for vibration characteristics. Based on the actual working conditions of the internal combustion engine and the reference data on vibration characteristics, the frequency range with the maximum vibration energy is identified and determined as the target vibration reduction frequency range.

[0010] As a preferred embodiment of the internal combustion engine vibration reduction method with a built-in curved acoustic black hole described in this invention, the parameterized model for constructing the periodic vibration reduction structure containing the curved acoustic black hole includes, Determine the geometric parameters of the parametric model and define the constraints of the parameters based on the installation environment and performance requirements of the periodic vibration reduction structure; Under constraints, initial values ​​are assigned to the geometric parameters, and the remaining derived dimensions of the parametric model are calculated based on predetermined structural relationships. Based on the initial values ​​of the geometric parameters and the derived dimensions, the initial geometric configuration of the curved acoustic black hole within a periodic structural unit cell is established.

[0011] As a preferred embodiment of the internal combustion engine vibration reduction method with a built-in bending acoustic black hole as described in this invention, the step of calculating the bending wave bandgap characteristics of the periodic vibration reduction structure using a first algorithm includes: Establish the elastic wave control equations for the periodically damped structure in the plane; Based on the elastic wave control equation and the periodic boundary conditions of the structure, an eigenvalue problem is constructed and solved to obtain the characteristic frequency spectrum of the elastic wave. Based on the structural vibration modes corresponding to different frequency points in the characteristic frequency spectrum, the characteristic frequency range corresponding to the dominant bending wave mode is filtered out and used as the bending wave bandgap.

[0012] As a preferred embodiment of the internal combustion engine vibration reduction method with a built-in curved acoustic black hole as described in this invention, the step of generating adjustment decisions for the geometric parameters of the parameterized model based on the spectral position relationship between the curved wave bandgap and the target vibration reduction frequency range includes: Calculate the deviation between the mid-frequency of the flexural wave bandgap and the mid-frequency of the target vibration reduction frequency range; If the deviation exceeds the first preset threshold, a first adjustment command is generated to adjust the height of the unit cell of the periodic vibration damping structure. If the deviation does not exceed the first preset threshold but does not achieve a perfect match, a second adjustment command is generated to adjust the power-law shape parameters of the curved acoustic black hole.

[0013] This invention transforms a complex multi-parameter optimization problem into a well-defined decision-making process with clear physical guidance by introducing a conditional branching decision-making mechanism based on intermediate frequency deviation. First, it identifies whether the current design defect is due to bandgap position shift or poor bandgap morphology, and then intelligently triggers targeted adjustments to the periodic structure scale or the shape of the acoustic black hole, respectively.

[0014] It overcomes the technical difficulties of blind parameter adjustment and difficult coupling relationship handling in traditional design, enabling the design process to converge quickly along the correct physical direction, greatly improving optimization efficiency and success rate, and realizing directional design of vibration reduction performance.

[0015] As a preferred embodiment of the internal combustion engine vibration reduction method with a built-in bending acoustic black hole as described in this invention, the step of performing coordinated iterative adjustment of geometric parameters according to adjustment decisions until the bending wave bandgap meets the requirements of the target vibration reduction frequency range includes: Based on the direction of the adjustment decision, the corresponding geometric parameters are updated according to the preset adjustment strategy; Using the updated geometric parameters, the parametric model is reconstructed and the flexural wave bandgap is calculated; it is then determined whether the recalculated flexural wave bandgap meets the requirements of the target vibration reduction frequency range. If the requirements are not met, the process returns to the step of generating adjustment decisions, using the latest flexural bandgap for comparison and decision-making again, until the requirements are met.

[0016] This invention seamlessly integrates parameter adjustment, model updating, performance verification, and target determination, forming an optimization loop. This ensures that the design process can continuously and automatically approach the optimal solution until the preset vibration reduction target is strictly met, completely eliminating reliance on human experience and repeated trial and error.

[0017] As a preferred embodiment of the internal combustion engine vibration reduction method with a built-in bending acoustic black hole described in this invention, the final structural parameters that satisfy the target vibration reduction requirements include: When the flexural wave bandgap meets the target vibration reduction frequency range requirements, the values ​​of all geometric parameters corresponding to the parametric model are used as the final design result output.

[0018] This invention provides a vibration reduction system for an internal combustion engine with a built-in bending acoustic black hole.

[0019] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an internal combustion engine vibration reduction system with built-in bending acoustic black hole, comprising: a data collection module, a model building module, a calculation module, a decision-making module, an adjustment module, and an output module; The data collection module is used to obtain the target vibration reduction frequency range of the internal combustion engine. The model building module is a parameterized model for building a periodic vibration reduction structure containing a curved acoustic black hole; The calculation module calculates the flexural wave bandgap characteristics of the periodic damping structure using a first algorithm. The decision module generates adjustment decisions for the geometric parameters of the parameterized model based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range. The adjustment module performs coordinated iterative adjustments to the geometric parameters based on the adjustment decision until the bending wave bandgap meets the requirements of the target vibration reduction frequency range. The output module outputs the final structural parameters that meet the target vibration reduction requirements.

[0020] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the described method for vibration reduction of an internal combustion engine with a built-in bending acoustic black hole.

[0021] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the described method for vibration reduction of an internal combustion engine with a built-in bending acoustic black hole.

[0022] The beneficial effects of this invention are as follows: ① Through a layered bending design, this invention enables multiple acoustic black holes to act simultaneously, potentially stimulating more complex wave mode conversion effects, thereby achieving broadband and efficient vibration reduction. ② In the floating raft system, the frequency synergy design of the "acoustic black hole local energy absorption zone" and "periodic bandgap vibration reduction" is achieved. A dual vibration reduction barrier is formed through energy coupling and bandgap overlap mechanisms, significantly enhancing the structure's low-frequency attenuation capability. ③ Combining the physical characteristics of the structure, parameter changes are made "directional," forming a "structural design process where physical characteristics drive parameter changes," significantly improving design efficiency and engineering portability. ④ By combining geometric and mechanical symmetry, a highly stable periodic unit cell is constructed, effectively improving vibration reduction consistency and design repeatability. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 The above is a general flowchart of an internal combustion engine vibration reduction method with a built-in bending acoustic black hole, provided as an embodiment of the present invention.

[0025] Figure 2 This is a unit cell structure diagram of a vibration reduction raft structure with a built-in flexural acoustic black hole, provided as an embodiment of the present invention for a vibration reduction method of an internal combustion engine with a built-in flexural acoustic black hole.

[0026] Figure 3 This is a schematic diagram of a one-dimensional acoustic black hole beam model, which is provided as an embodiment of the present invention for a vibration reduction method of an internal combustion engine with a built-in bending acoustic black hole.

[0027] Figure 4 This is a schematic diagram of a bending acoustic black hole beam model, which is provided as an embodiment of the present invention for a vibration reduction method of an internal combustion engine with a built-in bending acoustic black hole.

[0028] Figure 5The energy band structure diagram of the unit cell structure of the vibration reduction raft structure with built-in flexural acoustic black hole provided in an embodiment of the present invention is shown.

[0029] Figure 6 The figure shows a simulation model of the transmission loss of a traditional vibration-damping floating raft structure, which is a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole, provided as an embodiment of the present invention.

[0030] Figure 7 The diagram shows a simulation model of the transmission loss of a vibration reduction raft structure with a built-in flexural acoustic black hole, which is provided as an embodiment of the present invention for a vibration reduction method of an internal combustion engine with a built-in flexural acoustic black hole.

[0031] Figure 8 A comparison diagram of transmission loss between a conventional vibration-damping raft structure and a vibration-damping raft structure with a built-in bending acoustic black hole, provided as an embodiment of the present invention. Detailed Implementation

[0032] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0033] Example 1, referring to Figure 1 This is one embodiment of the present invention, which provides a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole, comprising: In traditional internal combustion engine vibration damping raft design, structural selection and parameter trial and error are typically based on engineers' experience, or optimization is performed only on a single type of damping mechanism (such as simple mass isolation or local damping). These methods have significant limitations: First, the design process lacks systematic theoretical guidance and precise fluctuation control, making it difficult to achieve "directional" and "efficient" suppression of specific low-frequency vibration bands, often resulting in substandard vibration damping performance or structural redundancy. Second, traditional methods fail to effectively coordinate the use of two advanced fluctuation control mechanisms: "bandgap attenuation of periodic grids" and "local energy dissipation of acoustic black holes," thus failing to address the propagation and local concentration of vibration energy in the structure under broadband excitation. Furthermore, the design process has low automation, heavily relies on manual iteration, resulting in low efficiency and poor reproducibility of results.

[0034] Therefore, this invention provides a vibration reduction method for internal combustion engines with a built-in bending acoustic black hole.

[0035] S1. Obtain the target vibration reduction frequency range of the internal combustion engine; S2. Construct a parameterized model of a periodic vibration reduction structure containing a flexural acoustic black hole; S3. Calculate the flexural wave bandgap characteristics of the periodic vibration reduction structure using the first algorithm; S4. Based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range, generate adjustment decisions for the geometric parameters of the parameterized model; S5. Based on the adjustment decision, the geometric parameters are adjusted in a coordinated iterative manner until the bending wave bandgap meets the requirements of the target vibration reduction frequency range. S6. Output the final structural parameters that meet the target vibration reduction requirements.

[0036] The curved acoustic black hole is embedded as an energy-consuming unit within a single cell of a periodic structure.

[0037] Example 2, Figures 2-4 As one embodiment of the present invention, based on the previous embodiment, a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole is provided, comprising: This invention belongs to the field of vibration-damping floating raft structure technology, and relates to a design method for an internal combustion engine vibration-damping floating raft structure with a built-in bending acoustic black hole.

[0038] The vibration-damping floating raft structure with a built-in curved acoustic black hole is mainly composed of a thin acoustic black hole plate that is centrally symmetrically installed at the geometric center of the "I" shaped grid structure.

[0039] like Figure 2 As shown, the black hole region of this acoustic black hole thin plate is designed according to a power law, and the power law satisfies... .

[0040] like Figure 3 As shown, it underwent a semi-circular bend of over 160 degrees, thereby effectively extending its actual base length.

[0041] like Figure 4 As shown, the bending only applies to the power-law segment. Four identical acoustic black hole structures are symmetrically arranged outward from the center of the "I" grid, resembling the letters "C" in two directions, and the acoustic black holes on the same side share a portion of the uniform segment.

[0042] The entire structure is made of steel and is a highly symmetrical periodic structure with a uniform cross-section in the Z-axis direction. Its bandgap characteristics can be utilized to achieve efficient vibration reduction. The method is characterized by the following steps: S1. Obtain the target vibration reduction frequency range of the internal combustion engine, including the following steps: S11. Sensors are placed at all engine mounts of the internal combustion engine to measure vibration signals.

[0043] Comprehensive acquisition of vibration data of internal combustion engines under specific operating conditions provides precise input and basis for subsequent vibration reduction design (such as matching the floating raft structure with built-in bending acoustic black hole).

[0044] Accelerometers were placed at all engine mounts of the internal combustion engine to measure the vibration signals of the structure. S12. Preprocess the measured vibration signal to obtain vibration characteristics and average all signals to form a reference for vibration characteristics; S13. Based on the actual working conditions of the internal combustion engine and the reference data of vibration characteristics, identify the frequency range with the maximum vibration energy and determine it as the target vibration reduction frequency range.

[0045] Based on the vibration characteristics under actual working conditions, the maximum frequency range of the internal combustion engine vibration is determined, and this is used as the target frequency [f1, f2] for subsequent vibration reduction.

[0046] The preprocessing in embodiment S12 of this application involves: bandpass filtering the raw acceleration time-domain signal obtained from the measurement to remove high-frequency noise and low-frequency drift interference. The filtered signal is divided into multiple equal-length data segments, and a Hanning window is applied to reduce spectral leakage. A fast Fourier transform is performed on each windowed data segment to convert it into a linear spectrum in the frequency domain. The amplitudes of all linear spectra are averaged (e.g., by calculating the average power spectral density) as a reference for subsequent vibration characteristics.

[0047] In one optional implementation, the preprocessing in S12 is as follows: short-time Fourier transform is used to perform time-frequency analysis on the original acceleration time-domain signal obtained by measurement. The signal segments are truncated by sliding time windows and Fourier transform is performed on each segment to obtain the time spectrum of the signal frequency components as a function of time. Subsequently, the time spectrum is averaged in the frequency dimension within the time interval corresponding to the stable working condition to extract the stable distribution characteristics of the vibration energy in the frequency domain under the working condition, which serves as a reference for subsequent vibration characteristics.

[0048] In another optional implementation, the preprocessing in S12 involves wavelet packet decomposition of the original acceleration time-domain signal, which decomposes the signal into a series of detail components covering different frequency sub-bands. Then, the energy proportion of each detail component is calculated, and key frequency bands with concentrated energy are selected. Finally, by reconstructing the signal components of these key frequency bands and calculating their power spectra, spectral characteristics reflecting the main vibration sources are obtained as a reference for subsequent vibration characteristics.

[0049] This invention systematically deploys sensors at all engine mounts of an internal combustion engine and performs measurements. This step directly obtains firsthand vibration signals from the vibration source, replacing the approximate methods of traditional design that rely on empirical estimation or simplified models. This avoids design deviations caused by inaccurate input data. By preprocessing the measured signals (such as filtering, segmentation, FFT transformation, and averaging), a stable and representative frequency-domain "vibration characteristic reference" is extracted from the complex time-domain signal. Combined with the actual operating conditions of the internal combustion engine, the "target vibration reduction frequency range" where vibration energy is most concentrated is clearly identified.

[0050] S2. Construct a parametric model of the periodic vibration reduction structure containing the curved acoustic black hole, including the following steps: S21. Determine the geometric parameters of the parametric model and define the constraints of the parameters based on the installation environment and performance requirements of the periodic vibration reduction structure.

[0051] Two core geometric parameters were identified as optimization variables: the structural height of the periodic damping unit cell and the power-law exponent of the built-in bending acoustic black hole.

[0052] These two parameters were strictly defined based on practical engineering constraints: the unit cell height is physically limited by the installation space (maximum height). W max And the minimum number of unit cells required to generate an effective periodic bandgap (from which the maximum unit cell length is derived). M max The double constraint is used to determine its effective upper limit, which is expressed as follows: (1) At the same time, it is stipulated that the initial value of the power law exponent must not be less than m_min = 1.2. This sets a clear feasible region for subsequent modeling.

[0053] S22. Under constraints, assign initial values ​​to the geometric parameters and calculate the remaining derived dimensions of the parametric model based on the predetermined structural relationships. S23. Based on the initial values ​​of the geometric parameters and the derived dimensions, establish the initial geometric configuration of the curved acoustic black hole within the periodic structural unit cell.

[0054] Acoustic black hole region length L Uniform segment length L 1. Length of the power-law segment L 2, L = L 1+ L 2, L 1 / L 2 = 1 / 25; cut-off height is H 0, uniform segment height is H1. Power law is satisfied. , .

[0055] Based on the above definition of the overall configuration of the unit cell structure of the vibration-damping floating raft, all dimensions can be determined by only determining the height of the unit cell structure and the power exponent of the acoustic black hole structure.

[0056] Based on the parameters and dimensions determined in the first two steps, the specific three-dimensional geometric model is constructed. The established model has clear structural characteristics: its foundation is an I-shaped grid with a uniform cross-section (e.g., 5mm); at the geometric center of this grid unit cell, four identical acoustic black hole plates are symmetrically embedded, arranged radially outward from the center, resembling a two-way C-shape; the characteristic of each black hole plate is that its thickness follows a power-law function. The cut-off height is H 0, uniform segment height is H 1. Satisfy , m It is a power exponent. It is an exponential parameter. It increases from the truncation point towards the edge, and its power-law segment is bent into a semi-circular arc exceeding 160 degrees to extend the energy propagation path within a finite space; the entire unit cell structure is made of steel and has high symmetry in the direction perpendicular to the plane (Z-axis). This geometric configuration is the physical basis for all subsequent wave characteristic analysis and optimization iterations.

[0057] In embodiment S22 of this application, the remaining derived dimensions of the parameterized model are calculated based on predetermined structural relationships by: setting an initial point for the optimization process and completing the basic dimension chain calculation. The initial value is set as: unit cell height. W = W lim / 2, power-law exponent m=1.2. Based on the predetermined structural relationship of a unit cell aspect ratio of 2 determined in the invention, the length of the unit cell can be directly calculated from the height W. Furthermore, based on the overall size of the unit cell, by introducing a reduction factor α (valued at 0.7~0.75) that considers the bending angle and assembly gap, the centerline length L of the curved acoustic black hole is estimated using the formula: (2) in, It is a reduction factor, taking into account that the bending angle is not 180°, the structure has thickness, and there are gaps between the acoustic black hole thin plate and the "I" grid structure. The value ranges from 0.7 to 0.75. Based on the manufacturing constraints of the unit cell structure of the vibration-damping floating raft structure, the cut-off height is H0 = 0.05 mm. Furthermore, the required cutoff height H0 = 0.05 mm for constructing the acoustic black hole was determined. At this point, all key and derived dimensions of the model have been initially assigned values.

[0058] In an alternative implementation, the calculation of the remaining derived dimensions of the parameterized model in S22 based on predetermined structural relationships involves: prioritizing the lightweighting of the initial model, setting a preset ratio between its overall mass and the mass of a solid structure of the same volume; based on this ratio, the determined unit cell height (W), material density, and the preset rib width of the "I" shaped grid, the planar length of the unit cell is derived through the mass balance equation, thereby determining the aspect ratio; subsequently, the length (L) of the flexural acoustic black hole is set as a fixed proportion of the unit cell length. All dimensions calculated through this alternative scheme, together with the core geometric parameters (W, m), constitute a complete parameterized model of a periodic vibration-damping structure containing a flexural acoustic black hole, which serves as input for the subsequent calculation of the flexural wave bandgap characteristics in step S3.

[0059] In another optional implementation, the remaining derived dimensions of the parameterized model calculated in S22 based on predetermined structural relationships are as follows: With the goal of initial fluctuation matching with the target vibration reduction frequency range, the length of the unit cell is set to half of the wavelength of the bending wave corresponding to the lower frequency limit as a reference; subsequently, the total length (L) of the acoustic black hole is equal to this unit cell length; finally, the specific thickness of the grid ribs is determined based on the stiffness coordination relationship between the "I"-shaped grid and the built-in black hole thin plate. The parameterized model constructed in this way also directly serves as the initial geometric basis for the bandgap calculation in step S3 and the iterative optimization starting in S4.

[0060] Traditional raft design relies on general, empirical descriptions of the overall structure, making precise fluctuation analysis and optimization difficult. This invention integrates a curved acoustic black hole with a periodic grid structure, abstracting it into a parametric model of a finite number of key geometric parameters and their constraints, centered on the unit cell height (W) and the black hole power-law exponent (m). It not only accurately captures the core characteristics of power-law thickness variation and large-angle bending but also ensures periodicity through an "I"-shaped grid.

[0061] This step involves not arbitrarily setting parameters, but strictly defining the constraints of design variables based on the actual installation space and the physical requirements of periodic vibration reduction (such as the minimum number of unit cells), ensuring that the design starting point is within the engineering feasibility range. By assigning reasonable initial values ​​(unit cell height...),... W = W limBy using the formula ( / 2, power law exponent m=1.2) and calculating derived dimensions based on explicit geometric relationships (such as aspect ratio = 2, reduction factor α), an initial design point with clear physical meaning and predictable performance was constructed. This allows the optimization process to start from a promising starting point and explore along physically meaningful directions, avoiding the optimization process from getting trapped in local optima or ineffective regions.

[0062] S3. Calculate the flexural wave bandgap characteristics of the periodic vibration reduction structure using the first algorithm, including the following steps: S31. Establish the elastic wave control equations for the periodic vibration reduction structure in the plane.

[0063] When an elastic wave propagates in the XOY plane, the elastic wave equation is obtained by expanding the displacement wave function in the X and Y directions of the position coordinates, as shown in equation (3) below. (3) in, u It is the position (x, y) and time. t The displacement wave function, where x and y represent the coordinates of the particle. x and u y These represent the displacement components along the x-axis and y-axis, respectively. ρ λ is the density, and λ and μ are Lamé constants for periodic structures.

[0064] S32. Based on the elastic wave control equation and the periodic boundary conditions of the structure, construct and solve the eigenvalue problem to obtain the characteristic frequency spectrum of the elastic wave. Based on the above elastic wave control equations and the periodic boundary conditions satisfied by the periodic structure, an eigenvalue problem is constructed and solved to obtain the characteristic frequency spectrum (i.e., band structure) of the elastic wave.

[0065] This step corresponds to the original scheme, where Bloch's theorem is applied within the finite element framework to discretize the wave control equation into a typical eigenvalue equation (i.e., formula (4) in the document): (4) Where K is the total stiffness matrix and M is the total mass matrix. u It is the displacement wave function, and ω is the angular frequency of the propagating wave.

[0066] Solving this eigenvalue equation yields the characteristic frequencies of the structure under all wave vectors, thus allowing for the plotting of the complete band structure.

[0067] S33. Based on the structural vibration modes corresponding to different frequency points in the characteristic frequency spectrum, filter and select the characteristic frequency range corresponding to the dominant bending wave mode as the bending wave bandgap.

[0068] Based on the structural vibration modes corresponding to different frequency points in the characteristic frequency spectrum, the characteristic frequency range corresponding to the dominant bending wave mode is filtered out, and this range is defined as the bending wave bandgap.

[0069] Because the structure has a uniform cross-section in the z-axis direction, it can be considered a two-dimensional structure when calculating its properties.

[0070] This method studies the flexural wave bandgap, and the characteristic frequencies to be solved need to be further filtered by the judgment equation (5), which is: (5) in, q It is a filter factor. ux It is the displacement in the x-direction. v It represents the displacement in the y-direction, and "*" indicates the conjugate operator, i.e. ux* yes ux conjugate, v* yes v The conjugate of , s is the area of ​​a single cell.

[0071] The band gap obtained by filtering is the flexural band gap, such as... Figure 5 As shown, its definition formula is shown in equation (6).

[0072] Y= φ ∩[ f 1, f 2] (6) Here, Y is the objective function for optimization, also called the effective bandgap, and φ is the set of flexural wave bandgap.

[0073] The first algorithm in embodiment S3 of this application is: a band structure calculation method based on the finite element method and Bloch's theorem.

[0074] The parameterized geometric model established in step S2 is discretized using the finite element method to form the mass matrix and stiffness matrix. Subsequently, periodic boundary conditions (Bloch boundary conditions) are applied to the governing equations describing the propagation of elastic waves in the plane (i.e., equation (3)), transforming it into an eigenvalue problem with wave vector as the parameter (i.e., equation (4)). By scanning the characteristic wave vectors on the boundary of the first Brillouin zone and solving for the corresponding eigenvalues, a structurally complete characteristic frequency spectrum (i.e., a band structure diagram) is obtained; a filtering criterion is then applied. (Where q is the filtering factor, u is the displacement in the x direction, v is the displacement in the y direction, and s is the unit cell area) Perform pattern recognition on the spectrum and extract the continuous bandgap frequency range dominated by the bending wave, which is the required bending wave bandgap.

[0075] In an optional implementation, the first algorithm in S3 is a band structure calculation method based on the plane wave expansion method. This algorithm expands the material parameters (density, elastic constants) and displacement field of the periodic structure in reciprocal lattice space using plane wave basis functions; it transforms the elastic wave equation into wave vector space, thereby constructing an eigenvalue equation with the plane wave expansion coefficients as unknowns; by truncating a finite number of plane waves and solving this eigenvalue equation, the dispersion relation between the structure's characteristic frequencies and the wave vector is obtained; furthermore, by performing mode analysis on the eigenvalue displacement fields corresponding to each characteristic frequency point (such as calculating the energy ratio of its transverse and longitudinal displacements), the frequency range of the bending wave bandgap is screened and determined.

[0076] In another alternative implementation, the first algorithm in S3 is a band structure calculation method based on multiple scattering theory. This algorithm treats the distribution of built-in curved acoustic black holes and "I"-shaped lattices and other scatterers in a homogeneous matrix as a periodic arrangement; by solving the scattering field of a single scatterer and using the structure factor of the periodic lattice to coherently superimpose the scattered waves from all scatterers, a self-consistent equation for the total wave field of the system is established; by solving the nontrivial solution conditions of this equation, the band gap frequency range in which the elastic wave propagates in this periodic system is directly obtained; by analyzing the vibration mode of the wave field at the band gap frequency, it is confirmed that the band gap corresponds to a curved wave mode.

[0077] The "bent wave bandgap" calculated in step S3 of this invention is not a static result, but a dynamic function strongly correlated with the model's geometric parameters (W, m). This characteristic makes it a perfect objective function to drive the optimization algorithm in step S4. The bandgap frequency is sensitive to changes in the unit cell height W, which can be used to precisely "translate" the bandgap position (inner loop); the bandgap width and shape are sensitive to changes in the black hole power exponent m, which can be used to finely "shape" the bandgap performance (outer loop). The output of this step is not only the endpoint of performance evaluation, but also a compass guiding the optimization algorithm to perform a directed and efficient search.

[0078] S4. Based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range, generate adjustment decisions for the geometric parameters of the parameterized model, including the following steps: S41. Calculate the deviation between the mid-frequency of the flexural wave bandgap and the mid-frequency of the target vibration reduction frequency range.

[0079] If we assume that Y has only one bandgap [f3, f4], we first compare the matching relationship between the bending wave bandgap intermediate frequency of the unit cell structure of the vibration-damping raft structure and the target bandgap intermediate frequency to see if it satisfies equation (7). If it does, we directly output the unit cell structure height W and the power exponent m of the acoustic black hole structure, and determine the final optimized structure according to step S4; if it does not satisfy equation (7), we further determine whether it satisfies equation (8), which is expressed as: [f 3, f 4]=[ f 1, f 2] (7) (8) Where [f3, f4] are the effective band gaps, and [f1, f2] are the target band gaps. It should be further noted that the intermediate frequency is... The first threshold is .

[0080] S42. If the deviation exceeds the first preset threshold, a first adjustment command is generated to adjust the height of the unit cell of the periodic vibration damping structure.

[0081] If equation (7) and equation (8) are not satisfied, then the first threshold is not met, and the height of the single-cell structure is not satisfied. W Further adjustments are made to generate a first adjustment command for adjusting the unit cell height of the periodic damping structure, expressed as: (9) in, W It is the height of the single-cell structure, with the subscript " n " indicates an iteration step, W lim This indicates a height limit.

[0082] S43. If the deviation does not exceed the first preset threshold but does not achieve a complete match, a second adjustment command is generated to adjust the power-law shape parameters of the curved acoustic black hole.

[0083] If equation (7) is not satisfied but equation (8) is satisfied (i.e., the deviation does not exceed the first preset threshold but is not a complete match), then the outer loop is entered, and increments are made with a step size of Δm = 0.05. The power-law exponent of the acoustic black hole is further adjusted as the second adjustment instruction.

[0084] S5. Based on the adjustment decision, perform coordinated iterative adjustments to the geometric parameters until the bending wave bandgap meets the requirements of the target vibration reduction frequency range, including the following steps: S51. Based on the direction of the adjustment decision, update the corresponding geometric parameters according to the preset adjustment strategy.

[0085] The corresponding geometric parameters in the parametric model are updated according to the specific adjustment instructions generated by step S4.

[0086] When the instruction requires adjustment of the height of the periodic unit cell, the height parameter W is reassigned according to the preset internal loop strategy (i.e., the adjustment formula given by the inventor). When the instruction requires adjusting the power-law shape of the acoustic black hole, the power exponent m is reassigned according to the preset outer loop strategy (i.e., increasing in fixed steps).

[0087] The current step itself does not involve any analysis or decision-making; it merely serves as a terminal for receiving and implementing upstream instructions.

[0088] S52. Using the updated geometric parameters, reconstruct the parametric model and calculate the flexural wave bandgap; determine whether the recalculated flexural wave bandgap meets the requirements of the target vibration reduction frequency range.

[0089] First, using the new parameter values, the entire process from geometric modeling (S2) to bandgap calculation (S3) is completely repeated to obtain a new flexural wave bandgap that reflects the current design point.

[0090] The newly calculated flexural bandgap is compared with the initially set target vibration reduction frequency range.

[0091] It should be noted that the purpose of the comparison here is completely different from the decision-making comparison in step S4.

[0092] Step S52 is a final goal achievement check, the criterion for which is whether the new flexural bandgap completely covers the target frequency range. This is a yes or no conclusive judgment, assessing whether this iteration has enabled the design to reach the preset final performance endpoint.

[0093] S53. If not satisfied, return to the step of generating adjustment decision, and compare and decide again using the latest flexural bandgap until the requirement is met.

[0094] If the judgment in step S52 is "yes", that is, the current design has met the final requirements, the process ends and the output result is ready.

[0095] If the judgment is "no", that is, the current design still does not meet the standard, then step S53 is responsible for using the latest bending wave bandgap data obtained in this iteration as the input for a new round of analysis, feeding back and re-triggering the upstream step S4.

[0096] Step S4 will restart the analysis of intermediate frequency deviation and generate new decision logic based on this new performance data, thereby driving the next round of parameter updates and performance evaluation.

[0097] Step S53 itself does not perform calculations or decisions; it is merely a process controller that enables the cyclical connection between the execution-evaluation stage and the analysis-decision stage, ensuring that the optimization process can automatically iterate until the final goal is achieved.

[0098] The cooperative iterative adjustment in embodiment S5 of this application is a serial iterative mechanism that strictly follows the inner and outer loop logic. The adjustment begins with the execution of an explicit instruction from S4: if an instruction to adjust the unit cell height is received, the parameter W is updated; if an instruction to adjust the black hole exponent is received, the parameter m is updated with a fixed step size Δm = 0.05.

[0099] After the parameters are updated, geometric modeling and bandgap calculation are re-executed to obtain new performance data. A final target judgment is then performed to verify whether the new bandgap completely covers the target frequency band [f3, f4] = [f1, f2]. If not, the latest performance data is fully fed back to step S4, triggering a new round of decision generation, thus forming a closed loop. In this mechanism, the inner and outer loops (adjusting W and adjusting m) are not performed simultaneously. Instead, step S4 determines which loop to enter in each iteration based on a strict intermediate frequency deviation criterion, thereby achieving step-by-step, orderly collaboration.

[0100] In one alternative implementation, the cooperative iterative adjustment in S5 is an enhanced iterative method that introduces an adaptive step size and a parallel evaluation mechanism.

[0101] When updating parameters, the adjustment step size is no longer fixed, but proportional to the matching error between the current bandgap and the target frequency band. The larger the error, the larger the step size to accelerate convergence. After updating any set of parameters (W or m), not only is the flexural wave bandgap recalculated, but multiple performance indicators such as the width and attenuation intensity of the bandgap are also evaluated simultaneously.

[0102] The termination decision requires not only frequency coverage but also that the bandgap attenuation intensity reaches a preset threshold. If these conditions are not met, the system will send a performance evaluation report containing multiple indicators to step S4, generating a composite instruction that simultaneously fine-tunes multiple parameters.

[0103] In another alternative implementation, the collaborative iterative adjustment in S5 is an iterative optimization process based on weight allocation and parameter synchronization fine-tuning.

[0104] Upon receiving the adjustment instructions generated by S4, instead of adjusting a single parameter, a small adjustment is made simultaneously to the cell height W and the black hole exponent m according to a preset weighting scheme (for example, if the instruction requires a primary adjustment to W, m is also adjusted by a very small margin). After each synchronous fine-tuning, the bandgap is remodeled and recalculated. The termination condition is consistent with the core implementation method. If it is not met, the new performance data is fed back. The core of this scheme is that each iteration acknowledges the coupling effect between the two design parameters, and exploring a better combination of cooperating parameters through accompanying fine-tuning may help escape local optima, but requires more iterations.

[0105] This invention transforms abstract decision-making instructions into precise and repeatable digital adjustments to geometric parameters. Whether adjusting the unit cell height according to a specific formula or adjusting the power law exponent with a fixed step size, the process strictly follows preset rules, completely eliminating errors and inconsistencies that may be introduced by human intervention.

[0106] By remodeling and calculating, the bending wave bandgap under the new parameters can be obtained immediately, and the judgment is strictly based on whether it completely covers the target frequency range. This avoids the ineffective repetitive work caused by the lag in effect evaluation or subjectivity in the traditional trial and error method.

[0107] S6. Output the final structural parameters that meet the target vibration reduction requirements.

[0108] When the flexural wave bandgap meets the target vibration reduction frequency range requirements, the values ​​of all geometric parameters corresponding to the parametric model are used as the final design result output.

[0109] Example 3, referring to Figure 5 and Figure 8 This invention provides a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole, as one embodiment of the present invention. To verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0110] For the unit periodic structure of the vibration-damping floating raft structure, its parameters can be obtained through optimization: the height of the unit cell structure is W=70mm, the power exponent of the acoustic black hole structure is m=1.2, the length of the acoustic black hole region is L=80mm, and the bending angle is 160°.

[0111] Structure as Figure 2 As shown. The raft structure is made of steel with a density of 7850 kg / m³, an elastic modulus of 210000 MPa, and a Poisson's ratio of 0.3.

[0112] After setting the appropriate periodic conditions, the wave vector is scanned with a step size of 0.1, meaning there are 11 scan points within the range of 0 to 1. Each wave vector has its own mass matrix and stiffness matrix, derived from... The frequency under the corresponding wave vector can be obtained from the generalized eigenvalue equation. After bending wave filtering, the bending wave band structure of the structure is calculated as follows: Figure 5 . Figure 5 The frequency range that does not contain any specific frequency points can be considered the bandgap, as shown by the blue shading in the figure. From Figure 5 It can be observed that a band gap [225,477]Hz is formed in the 800Hz range, indicating that the optimized structure is effective and the band gap range covers the target range of vibration reduction requirements.

[0113] To further demonstrate the superiority of the structure, the vibration reduction effect of the vibration-damping raft structure with its built-in bending acoustic black hole was compared with that of a traditional raft structure, and simulation models of their transmission losses were constructed. The models are as follows: Figure 6 and Figure 7 As shown.

[0114] For the transmission loss simulation model, the equivalent base and equivalent hull are modeled as solids. The hypothetical equivalent material coefficients can be used, with a density of 750 kg / m3, an elastic modulus of 210000 MPa, and a Poisson's ratio of 0.3. The structural constraints are at both ends of the equivalent hull. The signals collected at the excitation points are used as the input signal in, and the vibration response at the middle position of the upper surface of the equivalent hull is selected as the output signal out. The transmission loss is calculated by TL = 20 * log(in / out).

[0115] The transmission losses of the vibration-damping floating raft structure with an embedded bending acoustic black hole and the traditional floating raft structure are calculated and compared. The results are as follows: Figure 8 As shown in the figure, the transmission curve of the built-in curved acoustic black hole is located below the traditional floating raft structure in the range of 250Hz to 750Hz, indicating that the vibration reduction floating raft structure with built-in curved acoustic black hole has a better vibration reduction effect in the range of 250Hz to 750Hz, proving that the optimized structure is effective.

[0116] Example 4 is an embodiment of the present invention, which provides an internal combustion engine vibration reduction system with a built-in bending acoustic black hole, including a data collection module, a model building module, a calculation module, a decision-making module, an adjustment module, and an output module; The data collection module is used to obtain the target vibration reduction frequency range of the internal combustion engine. The model building module is a parameterized model for building a periodic vibration reduction structure containing a curved acoustic black hole; The calculation module calculates the flexural wave bandgap characteristics of the periodic damping structure using a first algorithm. The decision module generates adjustment decisions for the geometric parameters of the parameterized model based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range. The adjustment module performs coordinated iterative adjustments to the geometric parameters based on the adjustment decision until the bending wave bandgap meets the requirements of the target vibration reduction frequency range. The output module outputs the final structural parameters that meet the target vibration reduction requirements.

[0117] This embodiment also provides an electronic device applicable to a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as proposed in the above embodiment.

[0118] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as proposed in the above embodiments.

[0119] The storage medium proposed in this embodiment belongs to the same inventive concept as the method for reducing vibration of an internal combustion engine with a built-in curved acoustic black hole proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0120] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0121] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole, characterized in that: include, Obtain the target vibration reduction frequency range for the internal combustion engine; Construct a parameterized model of a periodic vibration reduction structure containing a bending acoustic black hole; The flexural wave bandgap characteristics of the periodic damping structure are calculated using the first algorithm. Based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range, adjustment decisions are generated for the geometric parameters of the parameterized model. Based on the adjustment decision, the geometric parameters are adjusted iteratively until the bending wave bandgap meets the requirements of the target vibration reduction frequency range; Output the final structural parameters that meet the target vibration reduction requirements; The curved acoustic black hole is embedded as an energy-consuming unit within a single cell of a periodic structure.

2. The vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in claim 1, characterized in that: The target vibration reduction frequency range for the internal combustion engine includes... Sensors are placed at all engine mounts of the internal combustion engine to measure vibration signals; The measured vibration signals are preprocessed to obtain vibration characteristics, and all signals are averaged to form a reference for vibration characteristics. Based on the actual working conditions of the internal combustion engine and the reference data on vibration characteristics, the frequency range with the maximum vibration energy is identified and determined as the target vibration reduction frequency range.

3. The vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in claim 2, characterized in that: The parameterized model for constructing a periodic vibration reduction structure incorporating a curved acoustic black hole includes, Determine the geometric parameters of the parametric model and define the constraints of the parameters based on the installation environment and performance requirements of the periodic vibration reduction structure; Under constraints, initial values ​​are assigned to the geometric parameters, and the remaining derived dimensions of the parametric model are calculated based on predetermined structural relationships. Based on the initial values ​​of the geometric parameters and the derived dimensions, the initial geometric configuration of the curved acoustic black hole within a periodic structural unit cell is established.

4. The vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in claim 3, characterized in that: The calculation of the flexural wave bandgap characteristics of the periodic vibration reduction structure using the first algorithm includes, Establish the elastic wave control equations for the periodically damped structure in the plane; Based on the elastic wave control equation and the periodic boundary conditions of the structure, an eigenvalue problem is constructed and solved to obtain the characteristic frequency spectrum of the elastic wave. Based on the structural vibration modes corresponding to different frequency points in the characteristic frequency spectrum, the characteristic frequency range corresponding to the dominant bending wave mode is filtered out and used as the bending wave bandgap.

5. The vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in claim 4, characterized in that: The generation of adjustment decisions for the geometric parameters of the parameterized model based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range includes: Calculate the deviation between the mid-frequency of the flexural wave bandgap and the mid-frequency of the target vibration reduction frequency range; If the deviation exceeds the first preset threshold, a first adjustment command is generated to adjust the height of the unit cell of the periodic vibration damping structure. If the deviation does not exceed the first preset threshold but does not achieve a perfect match, a second adjustment command is generated to adjust the power-law shape parameters of the curved acoustic black hole.

6. The vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in claim 5, characterized in that: The step of performing coordinated iterative adjustments to the geometric parameters based on the adjustment decision until the flexural wave bandgap meets the requirements of the target vibration reduction frequency range includes... Based on the direction of the adjustment decision, the corresponding geometric parameters are updated according to the preset adjustment strategy; Using the updated geometric parameters, the parametric model is reconstructed and the flexural wave bandgap is calculated; Determine whether the recalculated flexural wave bandgap meets the requirements of the target vibration reduction frequency range; If the requirements are not met, the process returns to the step of generating adjustment decisions, using the latest flexural bandgap for comparison and decision-making again, until the requirements are met.

7. The vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in claim 6, characterized in that: The final structural parameters that satisfy the target vibration reduction requirements include: When the flexural wave bandgap meets the target vibration reduction frequency range requirements, the values ​​of all geometric parameters corresponding to the parametric model are used as the final design result output.

8. A vibration reduction system for an internal combustion engine with a built-in bending acoustic black hole, employing the vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in any one of claims 1 to 7, characterized in that, include: The module includes a data collection module, a model building module, a calculation module, a decision-making module, an adjustment module, and an output module. The data collection module is used to obtain the target vibration reduction frequency range of the internal combustion engine. The model building module is a parameterized model for building a periodic vibration reduction structure containing a curved acoustic black hole; The calculation module calculates the flexural wave bandgap characteristics of the periodic damping structure using a first algorithm. The decision module generates adjustment decisions for the geometric parameters of the parameterized model based on the spectral position relationship between the flexural wave bandgap and the target vibration reduction frequency range. The adjustment module performs coordinated iterative adjustments to the geometric parameters based on the adjustment decision until the bending wave bandgap meets the requirements of the target vibration reduction frequency range. The output module outputs the final structural parameters that meet the target vibration reduction requirements.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the vibration reduction method for an internal combustion engine with a built-in bending acoustic black hole as described in any one of claims 1 to 7.

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