Hatch cover tightness detection method and system based on acoustic wave analysis

Abstract

The invention discloses a hatch cover tightness detection method and system based on acoustic wave analysis, which specifically relates to the technical field of quality detection, and is used to solve the problem that the existing detection accuracy hidden dangers in the detection process cannot be discovered in time; by utilizing Shannon entropy and Lempel-Ziv complexity analysis, potential high-risk areas of hatch covers are identified in the preliminary stage; by comprehensively analyzing the interaction and chaotic behavior of acoustic wave signals, the accuracy of acoustic wave detection is evaluated in real time, and by generating a detailed detection report, the detection data and analysis results are presented in a formalized manner; by evaluating the comprehensive accuracy and the proportion of high-risk areas, a quantitative basis is provided for judging the credibility of the detection report, thereby ensuring the accuracy and timeliness of decision-making, and significantly improving the reliability and accuracy of acoustic wave detection.

Description

Technical Field

[0001] The present invention relates to the technical field of quality inspection, and more specifically, to a hatch cover tightness inspection method and system based on acoustic wave analysis. Background Art

[0002] In modern aerospace, marine engineering and other industrial fields, the structural integrity and sealing of hatch covers are key factors to ensure safety and functionality. The main steps of hatch cover tightness detection based on acoustic wave analysis are to emit sound waves from the acoustic wave transmitter, which pass through the hatch cover and reflect at the interface between the hatch cover and the outside world. The acoustic wave receiver captures the sound waves reflected from the hatch cover. By analyzing these reflected waves, the leakage point or the location of poor sealing can be detected. By comparing the acoustic wave reflection characteristics of different areas, possible leakage or sealing defects can be analyzed.

[0003] In actual hatch cover tightness detection based on acoustic wave analysis, traditional methods may have low recognition accuracy and the risk of misjudgment when processing complex or low-contrast reflection signals; if the detection accuracy risks in the detection process are not discovered in time, it will result in the inability to timely discover and deal with structural defects, which may cause the hatch cover to fail and endanger the safe operation of the entire facility.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a hatch cover tightness detection method and system based on acoustic wave analysis to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The hatch cover tightness detection method based on acoustic wave analysis includes the following steps:

[0008] S1: Perform preliminary acoustic inspection of the hatch cover and identify high-risk areas of the hatch cover by analyzing the acoustic signal using Shannon entropy and Lempel-Ziv complexity;

[0009] S2: After increasing the frequency of the sound wave, the high-risk area of ​​the hatch cover is tested again by the sound wave;

[0010] S3: By analyzing the multi-scale information flow based on information theory during the second acoustic wave inspection, the hidden dangers of acoustic wave signal interaction in the high-risk area of ​​the hatch cover are evaluated; sensitivity analysis of the acoustic wave signal based on chaos theory is performed to evaluate the possibility of chaotic behavior of the acoustic wave signal during the second acoustic wave inspection;

[0011] S4: By comprehensively analyzing the potential risk of acoustic signal interaction in high-risk areas of the hatch cover and the possibility of chaotic behavior of acoustic signals during the re-sonic inspection, the accuracy of the re-sonic inspection process is evaluated in real time;

[0012] S5: After the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test;

[0013] S6: Evaluate the overall accuracy of the second acoustic inspection process and obtain the proportion of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover;

[0014] S7: Based on the comprehensive accuracy of the second ultrasonic inspection process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic inspection of the hatch cover, determine whether to trust the hatch cover tightness inspection report.

[0015] In a preferred embodiment, the high-risk areas of the hatch cover are identified by analyzing the acoustic wave signal using Shannon entropy and Lempel-Ziv complexity, specifically:

[0016] The probability of the signal amplitude occurring is used to calculate the Shannon entropy of the acoustic signal based on the probability of the signal amplitude occurring.

[0017] converting the processed sound wave signal into a binary sequence according to a preset threshold;

[0018] Apply the Lempel-Ziv algorithm to traverse the binary sequence, identify the occurrence of new patterns, count them, and calculate the Lempel-Ziv complexity;

[0019] Comparing the calculated Shannon entropy and Lempel-Ziv complexity of the acoustic signal with preset baseline values;

[0020] The hatch cover areas where the Shannon entropy or Lempel-Ziv complexity of the acoustic wave signal is higher than the baseline value are marked as high-risk areas of the hatch cover.

[0021] In a preferred embodiment, after the frequency of the sound wave is increased, the high-risk area of ​​the hatch cover is subjected to another sound wave inspection, specifically:

[0022] Adjust the frequency of the sonic transmitter higher, re-emit the sonic waves of the adjusted frequency in the high-risk area of ​​the hatch cover, collect the sonic data reflected from the high-risk area of ​​the hatch cover, perform advanced processing on the captured sonic data, and evaluate the actual structural status of the high-risk area of ​​the hatch cover based on the results of the sonic data analysis.

[0023] In a preferred embodiment, by analyzing the multi-scale information flow based on information theory in the second acoustic wave detection, the hidden danger level of the acoustic wave signal interaction in the high-risk area of ​​the hatch cover is evaluated, specifically:

[0024] Apply wavelet transform to the acoustic signal; select appropriate wavelet mother function and decomposition level;

[0025] By measuring the directed information flow between two time series, the high-risk detection transfer entropy is calculated using the following formula: ;

[0026] is the high risk detection transfer entropy, It is a time series In time status, It is a time series In time status, It is a time series In time status, Indicates that in a given and Under the conditions The probability of occurrence, Indicates that in the known and In the case The probability of occurrence, Indicates that in the known In the case Probability of occurrence.

[0027] In a preferred embodiment, a sensitivity analysis based on chaos theory is performed on the acoustic wave signal to evaluate the possibility of chaotic behavior of the acoustic wave signal in the acoustic wave detection again, specifically:

[0028] Select the embedding dimension and time delay, and reconstruct the one-dimensional acoustic signal time series into a high-dimensional phase space through Takens theorem;

[0029] In the reconstructed phase space, an initial point and its nearest neighbor are selected, and the initial distance between the initial point and its nearest neighbor is calculated;

[0030] Calculate the distance between neighboring points after each time step;

[0031] For different initial points and their nearest neighbor points, calculate the Lyapunov exponent.

[0032] In a preferred embodiment, the accuracy of the second acoustic wave detection process is evaluated in real time by comprehensively analyzing the hidden dangers of acoustic wave signal interaction in the high-risk area of ​​the hatch cover and the possibility of chaotic behavior of the acoustic wave signal in the second acoustic wave detection, specifically:

[0033] The high-risk detection transfer entropy and Lyapunov exponent are normalized, and the normalized high-risk detection transfer entropy and Lyapunov exponent are respectively assigned preset proportional coefficients to calculate the acoustic wave detection accuracy evaluation coefficient. The accuracy of the second acoustic wave detection process is evaluated in real time through the acoustic wave detection accuracy evaluation coefficient.

[0034] In a preferred embodiment, the comprehensive accuracy of the second acoustic wave inspection process is evaluated, and the proportion of high-risk areas of the hatch cover during the initial acoustic wave inspection of the hatch cover is obtained, specifically:

[0035] In the two-dimensional coordinate system, let time be the horizontal axis and the accuracy evaluation coefficient of acoustic wave detection be the vertical axis;

[0036] Draw a curve of the acoustic wave detection accuracy evaluation coefficient changing with time;

[0037] Set a threshold value of the acoustic wave detection accuracy evaluation coefficient; mark the area between the portion of the curve where the acoustic wave detection accuracy evaluation coefficient exceeds the threshold value and the time axis as the excess area;

[0038] Divide the excess area by the total time interval length of the second acoustic wave detection process to obtain the second acoustic wave detection accuracy index;

[0039] The proportion of the high-risk area of ​​the hatch cover when the preliminary acoustic wave inspection is carried out on the hatch cover is the ratio of the area of ​​the high-risk area of ​​the hatch cover when the preliminary acoustic wave inspection is carried out on the hatch cover to the total area of ​​the hatch cover on which the preliminary acoustic wave inspection is carried out;

[0040] The proportion of high-risk areas of the hatch covers during the preliminary acoustic inspection of the hatch covers is marked as the risk area proportion.

[0041] In a preferred embodiment, based on the comprehensive accuracy of the second acoustic wave detection process and the proportion of high-risk areas of the hatch cover during the initial acoustic wave detection of the hatch cover, it is determined whether to trust the hatch cover tightness detection report, specifically:

[0042] When the second acoustic wave detection accuracy index is less than or equal to the second acoustic wave detection accuracy threshold, and the risk area ratio is less than or equal to the risk area ratio threshold, the hatch cover tightness detection report is determined to be trusted; otherwise, the hatch cover tightness detection report is determined to be distrusted.

[0043] On the other hand, the present invention provides a hatch cover tightness detection system based on acoustic wave analysis, including a hatch cover risk identification module, a second acoustic wave detection module, an action hidden danger assessment module, a signal chaos assessment module, a detection accuracy assessment module, a detection report generation module, a report generation analysis module and a report generation judgment module;

[0044] Hatch cover risk identification module: Performs preliminary acoustic wave inspection on hatch covers and identifies high-risk areas of hatch covers by analyzing acoustic wave signals using Shannon entropy and Lempel-Ziv complexity;

[0045] Secondary acoustic wave detection module: After increasing the frequency of the acoustic wave, the high-risk area of ​​the hatch cover is re-detected by acoustic wave;

[0046] Hazard assessment module: By analyzing the multi-scale information flow based on information theory in the second acoustic wave detection, the degree of hidden danger of acoustic wave signal interaction in the high-risk area of ​​the hatch cover is assessed;

[0047] Signal chaos evaluation module: Performs sensitivity analysis on the acoustic signal based on chaos theory to evaluate the possibility of chaotic behavior of the acoustic signal in the second acoustic detection;

[0048] Detection accuracy assessment module: Through comprehensive analysis of the hidden dangers of acoustic signal interaction in the high-risk area of ​​the hatch cover and the possibility of chaotic behavior of acoustic signals in the second acoustic wave detection, the accuracy of the second acoustic wave detection process is evaluated in real time;

[0049] Test report generation module: after the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test;

[0050] Report generation and analysis module: evaluates the overall accuracy of the second acoustic inspection process and obtains the proportion of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover;

[0051] Report generation judgment module: Based on the comprehensive accuracy of the second ultrasonic inspection process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic inspection of the hatch cover, it is judged whether to trust the hatch cover tightness inspection report.

[0052] The technical effects and advantages of the hatch cover tightness detection method and system based on acoustic wave analysis of the present invention are as follows:

[0053] 1. The beneficial effects provided by the present invention on hatch cover tightness detection are remarkable, especially in improving detection accuracy and reducing the risk of misjudgment. First, by utilizing Shannon entropy and Lempel-Ziv complexity analysis, potential high-risk areas of the hatch cover can be identified at the preliminary stage. The application of this technology significantly improves the ability to analyze complex or low-contrast acoustic signals during the detection process, so that the structural integrity and sealing of the hatch cover can be accurately evaluated even when the signal quality is not ideal. In addition, Shannon entropy and Lempel-Ziv complexity, as statistical tools for measuring the amount of information and structural complexity, greatly reduce the risk of misjudgment caused by errors in signal interpretation.

[0054] 2. By comprehensively analyzing the interaction and chaotic behavior of acoustic wave signals, this process can evaluate the accuracy of acoustic wave detection in real time and ensure the reliability of the test results. By generating a detailed test report, the test data and analysis results can be presented in a formalized manner, which is convenient for understanding and subsequent operations. By evaluating the comprehensive accuracy and the proportion of high-risk areas, a quantitative basis is provided for judging the credibility of the test report, ensuring the accuracy and timeliness of decision-making. Overall, the transparency and scientific nature of the acoustic wave detection process are improved, which helps to timely discover and deal with potential structural defects, thereby ensuring the functionality and safety of the hatch cover. It not only significantly improves the reliability and accuracy of acoustic wave detection, but also greatly enhances the monitoring capability of the hatch cover structural integrity by providing a more comprehensive and in-depth analysis, thereby ensuring the safe operation of key structures in aerospace, marine engineering and other key industrial fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of a hatch cover tightness detection method based on acoustic wave analysis of the present invention;

[0056] Figure 2 It is a structural schematic diagram of the hatch cover tightness detection system based on acoustic wave analysis of the present invention. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Example 1

[0059] Figure 1 The present invention provides a hatch cover tightness detection method based on acoustic wave analysis, which comprises the following steps:

[0060] S1: Perform a preliminary acoustic inspection of the hatch cover and identify high-risk areas of the hatch cover by analyzing the acoustic signal using Shannon entropy and Lempel-Ziv complexity.

[0061] S2: After increasing the frequency of the sound wave, the high-risk area of ​​the hatch cover is tested again by sonic wave.

[0062] S3: By analyzing the multi-scale information flow based on information theory during the second acoustic wave inspection, the hidden dangers of acoustic wave signal interaction in the high-risk area of ​​the hatch cover are evaluated; sensitivity analysis of the acoustic wave signal based on chaos theory is performed to evaluate the possibility of chaotic behavior of the acoustic wave signal during the second acoustic wave inspection.

[0063] S4: The accuracy of the second acoustic wave inspection process is evaluated in real time by comprehensively analyzing the potential risks of acoustic wave signal interaction in high-risk areas of the hatch cover and the possibility of chaotic behavior of acoustic wave signals during the second acoustic wave inspection.

[0064] S5: After the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test.

[0065] S6: Evaluate the overall accuracy of the second acoustic inspection process and obtain the percentage of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover.

[0066] S7: Based on the comprehensive accuracy of the second ultrasonic inspection process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic inspection of the hatch cover, determine whether to trust the hatch cover tightness inspection report.

[0067] The hatch covers were initially inspected by acoustic wave and the acoustic wave signals were analyzed using Shannon entropy and Lempel-Ziv complexity to identify high risk areas of the hatch covers, specifically:

[0068] The purpose of the preliminary acoustic inspection of the hatch cover is to conduct a preliminary assessment of the overall structural integrity and sealing of the hatch cover through acoustic testing. The equipment used includes a sonic transmitter (which can emit sound waves in a specific frequency range), multiple sonic receivers (distributed in key areas of the hatch cover to capture reflected waves), and a data acquisition system.

[0069] The acoustic wave transmitter emits sound waves of a predetermined frequency on one side of the hatch cover. These sound waves penetrate the hatch cover and are reflected at its internal structure and the interface on the other side, and these reflected waves are captured by the receiver arranged on the opposite side of the hatch cover.

[0070] The received sound wave signal is converted into an electrical signal and recorded by a data acquisition system. The recorded data includes the intensity, time delay and frequency change of the sound wave.

[0071] Shannon entropy is used to evaluate the uncertainty and information content in acoustic signals and is suitable for revealing changes in acoustic signals when they encounter discontinuities or anomalies in the hatch cover structure.

[0072] Calculate the Shannon entropy of the sound wave signal. The Shannon entropy of the sound wave signal is used to quantify the information complexity of the signal. Its expression is: ;in, is the Shannon entropy of the sound wave signal, is the signal amplitude The probability of occurrence, is the total number of different amplitude levels in the sound wave signal (the amplitude level is determined based on the quantization processing of the signal), It is the number of amplitude levels in the sound wave signal.

[0073] in, It is obtained by analyzing the intensity distribution of the received sound wave signal, specifically:

[0074] The received continuous amplitude sound wave signal is first quantized, usually into 256 different levels (or depending on the resolution of the signal processing hardware).

[0075] For each quantized amplitude level, count the number of times it appears in the entire sound wave signal, and then divide it by the total number of samples to calculate the probability .

[0076] The high Shannon entropy of the acoustic signal indicates the presence of diverse reflection patterns in the acoustic signal, which may be related to the complex or variable internal structural characteristics of the hatch cover, indicating potential structural problems or material inhomogeneity.

[0077] Lempel-Ziv complexity is a method to measure the complexity of a data sequence. Based on the concept of sequence compression, it calculates the complexity by analyzing the frequency of occurrence of new patterns in a data sequence. Specifically, the Lempel-Ziv algorithm scans the sequence step by step and encodes each newly discovered non-repeating pattern to build a compressed dictionary. The number of unique new patterns in the sequence is used as a measure of its complexity. This indicator can effectively reflect the information content and structural randomness of the sequence.

[0078] Use the sonic detection equipment to emit sonic waves at a predetermined frequency and record the sonic wave signals reflected from the hatch cover.

[0079] The collected sound wave signals are digitally processed, including filtering, denoising and normalization.

[0080] The processed sound wave signal is converted into a binary sequence according to a preset threshold value, and the preset threshold value is usually the average value or median value of the sound wave signal.

[0081] The Lempel-Ziv algorithm is applied to traverse the binary sequence, identify the occurrence of new patterns, and count them to calculate the Lempel-Ziv complexity.

[0082] Specifically, converting the sound wave signal into a binary sequence involves thresholding the amplitude level of the sound wave signal, that is, marking the part with an amplitude higher than a certain set threshold as 1, and marking the part lower than the set threshold as 0. The set threshold is usually determined based on the average amplitude or other statistical characteristics of the signal.

[0083] The calculated Shannon entropy and Lempel-Ziv complexity of the acoustic signal are compared with preset baseline values, which are statistical averages obtained from standard data of healthy hatches.

[0084] The hatch cover areas where the Shannon entropy or Lempel-Ziv complexity of the acoustic signal is higher than the baseline value are marked as high-risk areas of the hatch cover. The high-risk areas of the hatch cover may have structural defects, material degradation or poor sealing.

[0085] Among them, the instability of the acoustic signal during the detection process may indeed cause the Shannon entropy and Lempel-Ziv complexity of the acoustic signal to be higher than the baseline value, thereby affecting the accuracy of the detection. Shannon entropy is an indicator for measuring signal uncertainty and information content, which reflects the randomness and complexity of the signal. If the sound wave is disturbed during propagation, such as due to environmental noise, equipment performance fluctuations or operating errors, the randomness of the signal may increase, resulting in an increase in the Shannon entropy value. Similarly, Lempel-Ziv complexity is a method to measure the structural complexity of a data sequence. If the signal is subject to external interference or internal structural changes, the frequency of new or atypical patterns will increase, resulting in an increase in Lempel-Ziv complexity. In the case of instability in the acoustic signal during the detection process, it is also necessary to increase the frequency of the acoustic wave to conduct another acoustic wave inspection of the high-risk area of ​​the hatch cover.

[0086] After increasing the frequency of the sound wave, the high-risk area of ​​the hatch cover is tested again by sound wave, specifically:

[0087] Increase the frequency of the sonicator. Increasing the frequency provides greater resolution, allowing the sound waves to more accurately detect small defects such as micro-cracks or subtle delaminations.

[0088] Make sure all acoustic receivers are calibrated to receive signals at higher frequencies. Adjust the receiver's sensitivity and gain to ensure that subtle changes in reflected waves are captured accurately.

[0089] In the identified high-risk areas of the hatch cover, the sound waves are re-emitted at a modified frequency. Since the sound waves have a shorter wavelength, they can interact with the microstructure inside the hatch cover in more detail, providing more information about the defects.

[0090] Collect data on sound waves reflected from these areas, paying special attention to capturing subtle reflections that may be amplified due to the increased frequency.

[0091] Advanced processing of captured acoustic wave data, including filtering, signal enhancement, and noise removal, is performed to optimize the signal for analyzability.

[0092] Based on the results of the acoustic wave data analysis, the actual structural status of each hatch cover's high-risk area is evaluated. Analyze whether there are changes in defect size or new defects. Prepare a detailed inspection report for each inspection area, including acoustic wave data charts, complexity and entropy calculation results, and analysis of changes compared to the initial inspection. Based on the inspection results, specific repair suggestions or further inspection suggestions are made. For areas with obvious defects, it is recommended to make immediate repairs or strengthen monitoring.

[0093] By analyzing the multi-scale information flow based on information theory in the second acoustic wave detection, the hidden dangers of acoustic wave signal interaction in the high-risk area of ​​the hatch cover are evaluated, specifically:

[0094] High-frequency sound waves are used to re-test the high-risk areas of the hatch covers that have been identified through preliminary inspections. Specific sound wave transmitting and receiving equipment is used to ensure that sufficient data can be captured for subsequent analysis.

[0095] Amplitude, frequency, and phase information of the sound waves were recorded using a data acquisition system.

[0096] The collected sound wave signals are filtered and denoised as necessary. Accurate data analysis requires minimizing background noise and interference from irrelevant frequencies. The sound wave signals are standardized to ensure consistency of analysis.

[0097] Applying wavelet transform to the processed acoustic signal can provide frequency and position information of the signal at multiple time scales.

[0098] Select the appropriate wavelet mother function and decomposition level and adjust them according to the characteristics of the signal.

[0099] Transfer Entropy is a method to measure the directed (asymmetric) information flow between two time series. The transfer entropy of high-risk detection is calculated as follows: .

[0100] is the high risk detection transfer entropy, which represents the value of the high risk detection transfer entropy for the time series For time series The transfer entropy of .

[0101] It is a time series In time status, It is a time series In time status, It is a time series In time status.

[0102] is the joint probability of the three variables, indicating that and Under the conditions Probability of occurrence; represents the conditional probability, given that and In the case of Probability of occurrence; Represents conditional probability, indicating that In the case of Probability of occurrence.

[0103] Time Series :This can be the acoustic wave signal data continuously recorded by an acoustic wave sensor at a specific point on the hatch cover (such as detection point A). This sequence records the changes in the acoustic wave signal at that point over a period of time, such as amplitude or energy.

[0104] Time Series : With time series Similar, but from another location on the hatch cover (e.g., detection point B). This location may be some distance from point A, allowing the signals captured by both sequences to reveal interactions within the structure or the effects of sound wave propagation.

[0105] By calculating the high-risk detection transfer entropy, the degree of hidden dangers in the accuracy of the re-sonic inspection process of the high-risk area of ​​the hatch cover can be revealed. This is mainly because the high-risk detection transfer entropy reflects the information flow and interaction between the acoustic signals in a specific area of ​​the hatch cover, indicating that the mutual dependence of the acoustic signals is enhanced, which may indicate the instability or inconsistency of the inspection area, which are all signs that the accuracy of the inspection may be threatened. A large high-risk detection transfer entropy may indicate hidden dangers in the inspection process. These hidden dangers may be caused by improper inspection settings, equipment calibration errors, or limitations of the inspection method itself; for example, if the acoustic transmitter or receiver is not accurately aligned or the response frequency is improperly adjusted, errors may occur in the interpretation of the data, resulting in an abnormal increase in the high-risk detection transfer entropy.

[0106] That is, the greater the high-risk detection transfer entropy, the greater the hidden danger of acoustic signal interaction in the high-risk area of ​​the hatch cover.

[0107] The sensitivity analysis of the acoustic wave signal based on chaos theory is carried out to evaluate the possibility of chaotic behavior of the acoustic wave signal in the second acoustic wave detection, specifically:

[0108] In order to analyze the chaotic characteristics in the acoustic signal time series, it is necessary to reconstruct the one-dimensional acoustic signal time series into a high-dimensional phase space. This is achieved through the Takens theorem, which requires the selection of appropriate embedding dimensions and time delays.

[0109] The time delay is usually determined by the autocorrelation function or the average mutual information method, and the goal is to find the first point where the autocorrelation is zero or the mutual information is minimal. The embedding dimension is determined by the false nearest neighbors (FNN) method, increasing the embedding dimension until the proportion of false nearest neighbors drops to zero.

[0110] In the reconstructed phase space, select an initial point and its nearest neighbor , and calculate the initial point and its nearest neighbor The initial distance between .

[0111] Let the system change over time Evolution, calculate the distance between adjacent points after each time step ,in is the time step.

[0112] Repeat the above process, for different initial points and their nearest neighbor points, take the average value as the Lyapunov index, which is expressed as: ;in, and are the initial distance and the elapsed time respectively The distance after is the Lyapunov exponent.

[0113] If the calculated Lyapunov exponent is > 0, it indicates that the system is very sensitive to the initial conditions and may have chaotic behavior. This means that the acoustic signal may exhibit complex nonlinear dynamics during high-frequency detection, which may affect the accuracy of detection.

[0114] If the Lyapunov exponent ≈ 0, the dynamic behavior of the system may be close to periodicity or quasi-periodicity, indicating that the detection process is relatively stable and the possibility of chaotic behavior is low.

[0115] If the Lyapunov exponent is < 0, the system tends to be stable and the signal may not be affected by the initial conditions.

[0116] Therefore, the larger the Lyapunov index, the greater the possibility that the acoustic signal will exhibit chaotic behavior during the acoustic detection. The Lyapunov index is an indicator of the system's sensitivity to initial conditions. A positive Lyapunov index indicates that the system has chaotic characteristics, which means that small changes in the system will be amplified, leading to unpredictable and instability in the results. Therefore, the larger the Lyapunov index, the more likely the system is to exhibit chaotic behavior, and the higher the uncertainty and error risk in the detection process.

[0117] By calculating the Lyapunov exponent, the nonlinear behavior of the acoustic signal can be quantified, which is very useful for identifying complex dynamic effects during the detection process. By evaluating the chaotic characteristics of the acoustic signal, hidden dangers that may affect the accuracy of the detection can be identified and eliminated, thereby improving the reliability of the detection results; in the second acoustic detection, the chaos of the signal is evaluated by accurately measuring the Lyapunov exponent. This method can reveal how small changes in the acoustic signal affect the dynamics of the entire system, providing a powerful tool for quantifying nonlinear behavior in acoustic signals, allowing inspectors to more accurately identify and evaluate complex dynamic changes that may exist in high-risk areas. Secondly, this method enhances the reliability of the detection process because by identifying chaotic behavior, the detection strategy can be adjusted in time, thereby reducing errors and improving the accuracy of detection. Finally, by predicting and managing the chaotic characteristics of the acoustic signal, the potential risks and costs caused by inaccurate detection can be effectively avoided.

[0118] The accuracy of the second acoustic wave detection process is evaluated in real time by comprehensively analyzing the potential risks of acoustic wave signal interaction in the high-risk area of ​​the hatch cover and the possibility of chaotic behavior of acoustic wave signals during the second acoustic wave detection. Specifically:

[0119] The high-risk detection transfer entropy and Lyapunov exponent are normalized, and the normalized high-risk detection transfer entropy and Lyapunov exponent are respectively assigned preset proportional coefficients to calculate the acoustic wave detection accuracy evaluation coefficient. The accuracy of the second acoustic wave detection process is evaluated in real time through the acoustic wave detection accuracy evaluation coefficient.

[0120] The specific implementation method of calculating the acoustic wave detection accuracy evaluation coefficient is not specifically limited here. Any method that can calculate the acoustic wave detection accuracy evaluation coefficient by assigning the normalized high-risk detection transfer entropy and Lyapunov exponent to preset proportional coefficients is acceptable. In order to implement the technical solution of the present invention, the present invention provides a specific method for calculating the acoustic wave detection accuracy evaluation coefficient, and its expression is: ;in, To accurately evaluate the coefficients for acoustic wave detection, are the preset proportional coefficients of high risk detection transfer entropy and Lyapunov exponent, respectively, and Both are greater than 0.

[0121] The greater the transfer entropy of high-risk detection, the greater the hidden danger of acoustic signal interaction in the high-risk area of ​​the hatch cover; the larger the Lyapunov exponent, the greater the possibility of chaotic behavior of acoustic signals in the second acoustic wave detection; therefore, according to the expression of the acoustic wave detection accuracy evaluation coefficient, the greater the acoustic wave detection accuracy evaluation coefficient, the worse the accuracy of the second acoustic wave detection process.

[0122] When both the transfer entropy and Lyapunov index of high-risk detection are high, it indicates that the information flow between signals is large and the system is sensitive to initial state changes. These two situations are usually related to structural problems, detection noise or other interference, which can increase the instability and prediction difficulty of the system. Therefore, when the accuracy evaluation coefficient of acoustic wave detection is large, it means that there may be more problems with the detection system and its detection accuracy is poor. This evaluation method provides an intuitive means to judge the reliability of re-detection through quantitative analysis, helping operators or system monitoring personnel to identify potential risks and problems, so as to take appropriate measures to adjust or optimize and improve the overall effect of detection.

[0123] Among them, the setting of the preset proportional coefficient is usually based on experimental data, historical test results or expert experience, aiming to balance the influence of each parameter in the overall evaluation. The high-risk detection transfer entropy and Lyapunov exponent each measure different risk factors: the former focuses on the information flow between signals, and the latter evaluates the sensitivity of the system to initial conditions. The setting of the preset proportional coefficient needs to be verified by a large amount of experimental data to determine the actual impact of each indicator on the detection accuracy. Usually, the preset proportional coefficient is adjusted in a simulation environment through an optimization algorithm (such as genetic algorithm, gradient descent method) until the weight ratio that most accurately reflects the detection accuracy is found. In addition, the adjustment of the preset proportional coefficient must also take into account changes in the operating environment to ensure the adaptability and stability of the system under different conditions.

[0124] After the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test, specifically:

[0125] The existing technology for generating hatch cover tightness test reports based on preliminary and secondary acoustic wave tests is relatively mature. For a better understanding, the following are the specific steps:

[0126] Collect all relevant data from the initial and re-sonication, including the amplitude, frequency, phase information of the sound waves, and any calculated derived parameters such as transfer entropy, Lyapunov exponent, etc.

[0127] Ensure that all data is up to date and has been properly processed and corrected to ensure the accuracy of the analysis.

[0128] Necessary statistical analysis was performed on the collected data, including data cleaning, outlier processing, and normalization to standardize the data format and range.

[0129] Compare the results of the initial test and the retest and analyze the differences and similarities between the two. Pay special attention to any significant changes, such as increases or decreases in amplitude, changes in frequency, and differences in decay characteristics.

[0130] Based on data analysis, key findings are refined, such as identified high-risk areas, potential structural issues, or any changes that require special attention.

[0131] Provide detailed descriptions and explanations of any problems found during the inspection, including possible causes and recommended solutions.

[0132] Write a structured report that includes an introduction, methodology, analysis of results, conclusions, and recommendations.

[0133] Include charts, graphs, and other visual aids in your report to visually present the results of your data analysis and key findings.

[0134] Provides specific recommendations based on the analysis results, such as repair suggestions, follow-up inspection plans, or any preventive measures that need to be taken.

[0135] Based on the inspection results, the current condition of the hatch cover and future maintenance needs are evaluated.

[0136] Evaluate the overall accuracy of the second acoustic inspection process and obtain the percentage of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover, specifically:

[0137] In the two-dimensional coordinate system, let time be the horizontal axis and the acoustic wave detection accuracy evaluation coefficient be the vertical axis.

[0138] Based on the data collected during the second ultrasonic testing process, a curve showing the change of the ultrasonic testing accuracy assessment coefficient over time is drawn.

[0139] Set the threshold of the acoustic wave detection accuracy assessment coefficient, which is used to distinguish between higher and lower accuracy areas.

[0140] The area between the portion of the curve where the acoustic wave detection accuracy evaluation coefficient exceeds the threshold and the time axis is marked as the excess area.

[0141] The excess area is divided by the total time interval length of the re-sonic wave detection process to obtain the re-sonic wave detection accuracy index.

[0142] The greater the re-sonic wave detection accuracy index is, the worse the overall accuracy of the re-sonic wave detection process is.

[0143] Among them, the proportion of the high-risk area of ​​the hatch cover when the preliminary acoustic wave inspection is carried out on the hatch cover is the ratio of the area of ​​the high-risk area of ​​the hatch cover when the preliminary acoustic wave inspection is carried out on the hatch cover to the total area of ​​the hatch cover on which the preliminary acoustic wave inspection is carried out.

[0144] The greater the proportion of high-risk areas in the hatch cover during the preliminary acoustic inspection of the hatch cover, the greater the potential risk to the accuracy of the preliminary acoustic inspection. This means that the accuracy of the preliminary acoustic inspection may be at risk. This is because a large proportion of high-risk areas usually indicates that the hatch cover may have more structural problems or defects, such as cracks, corrosion or other structural damage, which will affect the propagation characteristics of the sound waves. In these areas, the sound waves may encounter different degrees of scattering, absorption or reflection, which will affect the clarity of the signal and the accuracy of the interpretation. If the results of the preliminary inspection show a large area of ​​high-risk areas, this may indicate that the acoustic inspection has been subject to more interference or insufficient signal capture, thereby increasing the possibility of misjudgment of the inspection results.

[0145] The proportion of high-risk areas of the hatch covers during the preliminary acoustic inspection of the hatch covers is marked as the risk area proportion.

[0146] Based on the comprehensive accuracy of the second ultrasonic test process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic test of the hatch cover, it is judged whether to trust the hatch cover tightness test report, specifically:

[0147] When the second acoustic wave detection accuracy index is less than or equal to the second acoustic wave detection accuracy threshold, and the risk area ratio is less than or equal to the risk area ratio threshold, the hatch cover tightness detection report is determined to be trusted; otherwise, the hatch cover tightness detection report is determined to be distrusted.

[0148] The re-sonic detection accuracy index below the re-sonic detection accuracy threshold indicates that the acoustic detection system has maintained a high performance in operation, has not been disturbed too much, and has provided reliable data. At the same time, a lower risk area ratio means that the overall structural integrity of the hatch cover is good and there are fewer problem areas. When these two conditions are met at the same time, it means that the test results are both stable and reflect the true state of the hatch cover, so the hatch cover tightness test report can be trusted. If any of the conditions is not met, there may be a risk of not being accurately identified, so the test report cannot be fully trusted.

[0149] Among them, the accuracy threshold of the second acoustic wave detection should be set based on the technical specifications of the acoustic wave detection equipment, previous detection data and expected performance standards. Through historical data analysis, the typical accuracy index range of the acoustic wave detection system under normal operating conditions can be determined. Setting the upper limit of this range as the threshold means that the detection results exceeding this value may be affected by abnormal factors and the accuracy is reduced.

[0150] The setting of the risk area ratio threshold should take into account the use environment, material properties and structural design of the hatch cover. With reference to historical inspection data and industry standards for structural health monitoring, the maximum reasonable ratio of high-risk areas within the normal and acceptable safety range is evaluated. This threshold reflects the expected maximum risk area ratio in the absence of significant structural risk. Exceeding this value may indicate increased structural damage or aging.

[0151] Example 2

[0152] The difference between Example 2 of the present invention and Example 1 is that this example introduces a hatch cover tightness detection system based on acoustic wave analysis.

[0153] Figure 2 A structural schematic diagram of a hatch cover tightness detection system based on acoustic wave analysis of the present invention is given. The hatch cover tightness detection system based on acoustic wave analysis includes a hatch cover risk identification module, a secondary acoustic wave detection module, an action hidden danger assessment module, a signal chaos assessment module, a detection accuracy assessment module, a detection report generation module, a report generation analysis module and a report generation judgment module.

[0154] Hatch cover risk identification module: Performs preliminary acoustic inspection of hatch covers and identifies high-risk areas of hatch covers by analyzing acoustic signals using Shannon entropy and Lempel-Ziv complexity.

[0155] Secondary ultrasonic inspection module: After increasing the frequency of the ultrasonic wave, the high-risk area of ​​the hatch cover is inspected again by ultrasonic wave.

[0156] Hazard assessment module: By analyzing the multi-scale information flow based on information theory in the second acoustic wave detection, the degree of hazard of acoustic wave signal interaction in the high-risk area of ​​the hatch cover is evaluated.

[0157] Signal chaos evaluation module: Performs sensitivity analysis on the acoustic signal based on chaos theory to evaluate the possibility of chaotic behavior of the acoustic signal during the acoustic detection.

[0158] Detection accuracy assessment module: Through comprehensive analysis of the potential risks of acoustic signal interactions in high-risk areas of the hatch cover and the possibility of chaotic behavior of acoustic signals during the second acoustic wave detection, the accuracy of the second acoustic wave detection process is evaluated in real time.

[0159] Test report generation module: After the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test.

[0160] Report generation and analysis module: Evaluate the overall accuracy of the second acoustic inspection process and obtain the proportion of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover.

[0161] Report generation judgment module: Based on the comprehensive accuracy of the second ultrasonic inspection process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic inspection of the hatch cover, it is judged whether to trust the hatch cover tightness inspection report.

[0162] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0163] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0164] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0165] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0166] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0167] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0169] If the functions are implemented in the form of software function modules 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 the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0170] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0171] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A hatch cover tightness detection method based on acoustic wave analysis, characterized in that: The steps include: S1: Perform preliminary acoustic inspection of the hatch cover and identify high-risk areas of the hatch cover by analyzing the acoustic signal using Shannon entropy and Lempel-Ziv complexity; S2: After increasing the frequency of the sound wave, the high-risk area of ​​the hatch cover is tested again by the sound wave; S3: By analyzing the multi-scale information flow based on information theory during the second acoustic wave inspection, the hidden dangers of acoustic wave signal interaction in the high-risk area of ​​the hatch cover are evaluated; Conduct sensitivity analysis on the acoustic signal based on chaos theory to evaluate the possibility of chaotic behavior of the acoustic signal during the second acoustic detection; S4: By comprehensively analyzing the potential risk of acoustic signal interaction in high-risk areas of the hatch cover and the possibility of chaotic behavior of acoustic signals during the re-sonic inspection, the accuracy of the re-sonic inspection process is evaluated in real time; S5: After the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test; S6: Evaluate the overall accuracy of the second acoustic inspection process and obtain the proportion of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover; S7: Based on the comprehensive accuracy of the second acoustic wave inspection process and the proportion of high-risk areas of the hatch cover during the initial acoustic wave inspection of the hatch cover, determine whether to trust the hatch cover tightness inspection report; Evaluate the overall accuracy of the second acoustic inspection process and obtain the percentage of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover, specifically: In the two-dimensional coordinate system, let time be the horizontal axis and the accuracy evaluation coefficient of acoustic wave detection be the vertical axis; Draw a curve of the change of the accuracy evaluation coefficient of acoustic wave detection over time; Set a threshold value of the acoustic wave detection accuracy evaluation coefficient; mark the area between the portion of the curve where the acoustic wave detection accuracy evaluation coefficient exceeds the threshold value and the time axis as the excess area; Divide the excess area by the total time interval length of the second acoustic wave detection process to obtain the second acoustic wave detection accuracy index; The proportion of the high-risk area of ​​the hatch cover when the preliminary acoustic wave inspection is carried out on the hatch cover is the ratio of the area of ​​the high-risk area of ​​the hatch cover when the preliminary acoustic wave inspection is carried out on the hatch cover to the total area of ​​the hatch cover on which the preliminary acoustic wave inspection is carried out; The proportion of high-risk areas of the hatch covers during the preliminary acoustic inspection of the hatch covers is marked as the risk area proportion.

2. The hatch cover tightness detection method based on acoustic wave analysis according to claim 1 is characterized in that: By analyzing the acoustic signal using Shannon entropy and Lempel-Ziv complexity, high-risk areas of the hatch cover are identified, specifically: The probability of the signal amplitude occurring is used to calculate the Shannon entropy of the acoustic signal based on the probability of the signal amplitude occurring. converting the processed sound wave signal into a binary sequence according to a preset threshold; Apply the Lempel-Ziv algorithm to traverse the binary sequence, identify the occurrence of new patterns, count them, and calculate the Lempel-Ziv complexity; Comparing the calculated Shannon entropy and Lempel-Ziv complexity of the acoustic signal with preset baseline values; The hatch cover areas where the Shannon entropy or Lempel-Ziv complexity of the acoustic wave signal is higher than the baseline value are marked as high-risk areas of the hatch cover.

3. The hatch cover tightness detection method based on acoustic wave analysis according to claim 2 is characterized in that: After increasing the frequency of the sound wave, the high-risk area of ​​the hatch cover is tested again by sound wave, specifically: Adjust the frequency of the sonic transmitter higher, re-emit the sonic waves of the adjusted frequency in the high-risk area of ​​the hatch cover, collect the sonic data reflected from the high-risk area of ​​the hatch cover, perform advanced processing on the captured sonic data, and evaluate the actual structural status of the high-risk area of ​​the hatch cover based on the results of the sonic data analysis.

4. The hatch cover tightness detection method based on acoustic wave analysis according to claim 3 is characterized in that: By analyzing the multi-scale information flow based on information theory in the second acoustic wave detection, the hidden dangers of acoustic wave signal interaction in the high-risk area of ​​the hatch cover are evaluated, specifically: Apply wavelet transform to the acoustic signal; select appropriate wavelet mother function and decomposition level; By measuring the directed information flow between two time series, the high-risk detection transfer entropy is calculated using the following formula: ; is the high risk detection transfer entropy, It is a time series In time status, It is a time series In time status, It is a time series In time status, Indicates that in a given and Under the conditions The probability of occurrence, Indicates that in the known and In the case The probability of occurrence, Indicates that in the known In the case Probability of occurrence.

5. The hatch cover tightness detection method based on acoustic wave analysis according to claim 4 is characterized in that: The sensitivity analysis of the acoustic wave signal based on chaos theory is carried out to evaluate the possibility of chaotic behavior of the acoustic wave signal in the second acoustic wave detection, specifically: Select the embedding dimension and time delay, and reconstruct the one-dimensional acoustic signal time series into a high-dimensional phase space through Takens theorem; In the reconstructed phase space, an initial point and its nearest neighbor are selected, and the initial distance between the initial point and its nearest neighbor is calculated; Calculate the distance between neighboring points after each time step; For different initial points and their nearest neighbor points, calculate the Lyapunov exponent.

6. The hatch cover tightness detection method based on acoustic wave analysis according to claim 5 is characterized in that: The accuracy of the second acoustic wave detection process is evaluated in real time by comprehensively analyzing the potential risks of acoustic wave signal interaction in the high-risk area of ​​the hatch cover and the possibility of chaotic behavior of acoustic wave signals during the second acoustic wave detection. Specifically: The high-risk detection transfer entropy and Lyapunov exponent are normalized, and the normalized high-risk detection transfer entropy and Lyapunov exponent are respectively assigned preset proportional coefficients to calculate the acoustic wave detection accuracy evaluation coefficient. The accuracy of the second acoustic wave detection process is evaluated in real time through the acoustic wave detection accuracy evaluation coefficient.

7. The method for detecting hatch cover tightness based on acoustic wave analysis according to claim 6, characterized in that: Based on the comprehensive accuracy of the second ultrasonic test process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic test of the hatch cover, it is judged whether to trust the hatch cover tightness test report, specifically: When the accuracy index of the second acoustic wave detection is less than or equal to the accuracy threshold of the second acoustic wave detection, and the risk area ratio is less than or equal to the risk area ratio threshold, the hatch cover tightness detection report is determined to be trustworthy; Otherwise, it is determined that the hatch cover tightness test report is not trusted.

8. A hatch cover tightness detection system based on acoustic wave analysis, used to implement the hatch cover tightness detection method based on acoustic wave analysis according to any one of claims 1 to 7, characterized in that: It includes a hatch cover risk identification module, a second acoustic wave detection module, an action hidden danger assessment module, a signal chaos assessment module, a detection accuracy assessment module, a detection report generation module, a report generation analysis module and a report generation judgment module; Hatch cover risk identification module: Performs preliminary acoustic wave inspection on hatch covers and identifies high-risk areas of hatch covers by analyzing acoustic wave signals using Shannon entropy and Lempel-Ziv complexity; Secondary acoustic wave detection module: After increasing the frequency of the acoustic wave, the high-risk area of ​​the hatch cover is re-detected by acoustic wave; Hazard assessment module: By analyzing the multi-scale information flow based on information theory in the second acoustic wave detection, the degree of hidden danger of acoustic wave signal interaction in the high-risk area of ​​the hatch cover is assessed; Signal chaos evaluation module: Performs sensitivity analysis on the acoustic signal based on chaos theory to evaluate the possibility of chaotic behavior of the acoustic signal in the second acoustic detection; Detection accuracy assessment module: Through comprehensive analysis of the hidden dangers of acoustic signal interaction in the high-risk area of ​​the hatch cover and the possibility of chaotic behavior of acoustic signals in the second acoustic wave detection, the accuracy of the second acoustic wave detection process is evaluated in real time; Test report generation module: after the second ultrasonic test is completed, a hatch cover tightness test report is generated based on the preliminary ultrasonic test and the second ultrasonic test; Report generation and analysis module: evaluates the overall accuracy of the second acoustic inspection process and obtains the proportion of high-risk areas of the hatch cover during the initial acoustic inspection of the hatch cover; Report generation judgment module: Based on the comprehensive accuracy of the second ultrasonic inspection process and the proportion of high-risk areas of the hatch cover during the initial ultrasonic inspection of the hatch cover, it is judged whether to trust the hatch cover tightness inspection report.

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