An intelligent measurement and analysis system based on output data of deep-sea transducer array

Abstract

The application relates to the technical field of deep-sea exploration, in particular to an output data intelligent measurement and analysis system based on a deep-sea transducer array, which comprises a transducer array, a recording unit, a preprocessing unit, an integration unit, a calculation unit, an analysis unit and an adjustment unit; the recording unit collects output data of each transducer in real time; after preprocessing and integration, the calculation unit calculates output fluctuation characteristic values representing the overall stability of the array; the analysis unit judges the running state based on the values; if the values are unqualified, the analysis unit further locates the unqualified reasons by analyzing the variance of the sound pressure ratio of each transducer and generates corresponding processing instructions; and the adjustment unit adaptively adjusts the calculation parameters, the transducer working frequency or the data preprocessing parameters according to the instructions; through multi-level intelligent analysis and closed-loop feedback regulation, the application realizes automatic diagnosis and dynamic optimization of the running state of the deep-sea transducer array, and improves the stability and energy conversion efficiency of the array operation.

Description

Technical Field

[0001] This invention relates to the field of deep-sea exploration technology, and in particular to an intelligent measurement and analysis system for output data based on a deep-sea transducer array. Background Technology

[0002] In deep-sea environments, arrays composed of multiple transducers are core equipment for underwater acoustic communication, target detection, and marine environmental monitoring. Due to their long-term operation under harsh conditions such as high pressure, low temperature, complex ocean currents, and biofouling, the resonant frequency, acoustic performance, and energy conversion efficiency of these transducers are easily affected by environmental temperature fluctuations, external electromagnetic interference, and biofouling, leading to drift or degradation. Traditional maintenance methods mainly rely on periodic manual inspections or simple threshold alarms, which struggle to identify the specific causes of performance degradation in real time and with precision. This results in delayed maintenance response, low efficiency, and an inability to adaptively adjust parameters to maintain optimal overall array performance.

[0003] Chinese Patent Application No. CN120404916A discloses an underwater ultrasonic Doppler real-time analysis method and device based on a digital transducer, relating to the field of data analysis technology. The method includes: Step 1, emitting multiple beams of directional ultrasonic waves into the drilling fluid through a digital transducer array on the outer wall of the riser, and receiving echo signals reflected by the gas-liquid two-phase flow; performing real-time digital conversion on the echo signals to generate a raw digital signal containing phase and amplitude information; Step 2, extracting Doppler frequency shift features from the raw digital signal, and determining the real-time velocity and direction of air bubbles in the drilling fluid by calculating the frequency deviation between the reflected and emitted ultrasonic waves. This invention, through a digital transducer array and ultrasonic Doppler technology, achieves accurate measurement of air bubble motion parameters in the drilling fluid, real-time calculation of local gas content, and early warning and graded response to gas intrusion, improving the safety and intelligence level of drilling operations.

[0004] However, existing technologies still have the following problems:

[0005] Relying on fixed thresholds for single-dimensional status alarms makes it difficult to accurately distinguish whether the performance degradation of the transducer array is due to global environmental parameter fluctuations, local electromagnetic interference, or physical biological attachment. This prevents the system from performing adaptive closed-loop adjustments for different causes, making maintenance dependent on manual intervention and resulting in delayed responses. Summary of the Invention

[0006] To address this, the present invention provides an intelligent measurement and analysis system for output data based on a deep-sea transducer array. This system overcomes the limitations of existing technologies that rely on fixed thresholds for single-dimensional status alarms, making it difficult to accurately distinguish whether the performance degradation of the transducer array is due to global environmental parameter fluctuations, local electromagnetic interference, or physical biological adhesion. Consequently, the system is unable to perform adaptive closed-loop adjustments for different causes, and maintenance is reliant on manual intervention and suffers from delayed responses.

[0007] To achieve the above objectives, this invention provides an intelligent measurement and analysis system for output data based on a deep-sea transducer array. It includes:

[0008] A transducer array, consisting of several transducers arranged in a deep-sea region;

[0009] The recording unit, connected to the transducer array, includes several recording devices disposed in each transducer, for real-time acquisition and recording of the output data of the corresponding transducer;

[0010] A preprocessing unit, connected to the recording unit, is used to preprocess the output data;

[0011] An integration unit, connected to the preprocessing unit, is used to receive and integrate the preprocessed output data;

[0012] A computing unit, connected to the integration unit, is used to determine the output fluctuation characterization value of the transducer array based on the integrated output data.

[0013] An analysis unit, connected to the calculation unit, is used to determine whether the operating status of the transducer array is qualified based on the output fluctuation characterization value, and if it is not qualified, to determine the reason for the failure based on the variance of the sound pressure ratio of each transducer, and to generate corresponding processing instructions.

[0014] An adjustment unit is connected to the analysis unit, the preprocessing unit, and the transducer array, respectively, and is used to adjust at least one of the correction coefficients in the calculation unit, the operating frequency of the transducer array, or the data preprocessing parameters of the preprocessing unit according to the processing instructions generated by the analysis unit.

[0015] Furthermore, the computing unit determines the output fluctuation characterization value of the transducer array based on the integrated output data, wherein,

[0016] Calculate the sound pressure ratio of each transducer between the current cycle and the previous cycle to obtain the individual sound pressure ratio;

[0017] Calculate the average of the sound pressure ratios of all individuals to obtain the overall sound pressure ratio;

[0018] Obtain the current environmental parameters, and calculate a correction coefficient to characterize the degree of deviation of the environmental conditions based on the environmental parameters and the system's preset benchmark environmental parameters, wherein the greater the degree of deviation of the environmental conditions, the larger the correction coefficient;

[0019] Multiplying the overall sound pressure ratio by the correction coefficient yields the output fluctuation characterization value.

[0020] Furthermore, the analysis unit determines whether the operating status of the transducer array is qualified based on the output fluctuation characterization value, wherein,

[0021] If the output fluctuation characterization value is greater than the preset output fluctuation characterization value, the analysis unit determines that the operating state of the transducer array is unqualified, and further calculates the variance of the sound pressure ratio of each transducer, and determines the reason for the unqualification based on the variance.

[0022] If the output fluctuation characterization value is less than or equal to the preset output fluctuation characterization value, the analysis unit determines that the transducer array is in a qualified operating state.

[0023] Furthermore, the analysis unit determines the cause of non-compliance based on the variance, wherein,

[0024] If the variance is less than the preset variance, the analysis unit determines that the reason for non-compliance is fluctuation of environmental parameters;

[0025] If the variance is greater than or equal to the preset variance, the analysis unit determines that the reason for the non-compliance is a transducer malfunction and marks the abnormal transducer.

[0026] Furthermore, if the analysis unit determines that the cause of the non-compliance is fluctuation of environmental parameters, the adjustment unit adjusts the correction coefficient based on the temperature parameter, wherein...

[0027] Adjust the correction factor according to the temperature parameter;

[0028] The temperature parameter is the regional average temperature after correction based on depth and regional ocean current velocity.

[0029] The lower the temperature parameter, the greater the increase in the correction coefficient.

[0030] Furthermore, during the process of adjusting the correction coefficient based on the temperature parameter, the operating frequency of each transducer is simultaneously adjusted so that the ratio of the adjusted operating frequency to the current resonant frequency of the corresponding transducer is within a preset range.

[0031] Furthermore, after the adjustment unit adjusts the correction coefficient based on the temperature parameter, the analysis unit makes a second judgment on whether the operating status of the transducer array is qualified. If the analysis unit determines that the operating status of the transducer array is unqualified, it determines the processing method based on the historical curve constructed from the period and output fluctuation characterization values ​​in the historical records.

[0032] The analysis unit calculates the integral value of the historical curve within a preset period:

[0033] If the integral value is less than the preset integral value, the analysis unit determines that the reason for the failure is a transducer malfunction and marks the malfunctioning transducer.

[0034] If the integral value is greater than or equal to the preset integral value, the adjustment unit repeats the adjustment process of the correction coefficient.

[0035] Furthermore, the analysis unit marks abnormal transducers, wherein,

[0036] If the individual sound pressure ratio of a single transducer is not within the preset sound pressure ratio range, the analysis unit marks the transducer.

[0037] After the analysis unit marks the transducers, the analysis unit calculates the distribution distance of all marked transducers in the array;

[0038] If the distribution distance is greater than the preset distribution distance, the analysis unit determines that the reason for the non-compliance is external electromagnetic interference, and generates an adjustment instruction for the data preprocessing parameters of the preprocessing unit.

[0039] If the distribution distance is less than or equal to the preset distribution distance, the analysis unit determines that the reason for the non-compliance is biological attachment and generates a manual cleaning notification.

[0040] Furthermore, the adjustment unit adjusts the data preprocessing parameters based on the adjustment instructions of the data preprocessing parameters from the preprocessing unit, wherein,

[0041] Set a distance reference value, and calculate the ratio of the distribution distance to the distance reference value as an adjustment coefficient;

[0042] The cutoff frequency of the filtering algorithm is adjusted to be the product of the original cutoff frequency and the adjustment coefficient;

[0043] The filter order is adjusted to be the product of the original order and the adjustment coefficient.

[0044] Furthermore, after the adjustment unit adjusts the data preprocessing parameters based on the adjustment instructions of the preprocessing unit, the analysis unit again determines whether the operating status of the transducer array is qualified, wherein,

[0045] If the analysis unit determines again that the transducer array is not in good working order, the analysis unit determines that the reason for the failure is biological attachment and generates a manual cleaning notification.

[0046] Compared with existing technologies, the beneficial effects of this invention lie in its ability to achieve real-time, precise, and autonomous maintenance of the deep-sea transducer array's operating status by constructing a full-link system encompassing data acquisition, feature calculation, intelligent analysis, and closed-loop adjustment. Its core advantages are: the ability to intelligently distinguish the root causes of performance fluctuations, such as environmental changes, electromagnetic interference, or biofouling, and automatically trigger targeted parameter adjustments, such as compensation coefficients, operating frequencies, or filtering parameters. This proactively maintains the array's optimal operating state even in harsh environments, significantly improving system stability, energy efficiency, and operational intelligence, while effectively reducing manual maintenance costs and fault response time.

[0047] Furthermore, this invention constructs a three-level calculation framework of individual fluctuation, overall average, and environmental compensation. It captures the microscopic changes of each transducer by calculating the individual sound pressure ratio, reflects the overall trend of the array by obtaining the comprehensive sound pressure ratio, and intelligently compensates for the benchmark drift caused by environmental factors by introducing a correction coefficient positively correlated with the degree of environmental deviation. This method effectively integrates and distinguishes the impact of equipment performance fluctuations and environmental interference, making the final output fluctuation characterization value a key indicator that can truly and comprehensively reflect the comprehensive operating status of the array in complex deep-sea environments. Based on the core design principle that the larger the environmental deviation, the larger the correction coefficient, this calculation method ensures the accuracy of system evaluation and the correctness of guidance. When environmental conditions deteriorate (such as excessively low temperature or excessively high pressure), the increased correction coefficient amplifies the output fluctuation characterization value, thereby revealing the negative impact of the superposition of environmental pressure and equipment performance fluctuations in a timely and complete manner. This effectively avoids misjudgments or omissions that may be caused by changes in the environmental benchmark, providing a logically consistent and highly sensitive reliable basis for subsequent analysis units to determine whether the operating status is "unqualified."

[0048] Furthermore, this invention introduces a comprehensive temperature parameter corrected for depth and ocean current velocity, and adjusts the correction coefficient nonlinearly based on its value, achieving high-precision and adaptive compensation for the impact of environmental temperature fluctuations. This technique overcomes the shortcomings of simply using raw temperature data for linear compensation, significantly improving the accuracy of system state assessment in complex deep-sea environments and ensuring that subsequent diagnostic logic can operate reliably after excluding major environmental interferences.

[0049] Furthermore, by introducing a closed-loop operating frequency tracking and adjustment mechanism based on the measured resonant frequency while adjusting the environmental compensation parameters, this invention achieves dynamic locking of the transducer's operating frequency to its time-varying resonant characteristics. This technique effectively overcomes the transducer detuning problem caused by changes in ambient temperature, ensuring that each individual transducer always operates in a highly efficient state, thereby improving the energy conversion efficiency and output stability of the entire array from the source.

[0050] Furthermore, this invention introduces a secondary decision-making mechanism based on historical time series integration to achieve intelligent differentiation and triage of continuous environmental fluctuations and sudden equipment failures. This technical approach uses the time accumulation characteristics of fluctuation energy as a judgment basis, overcoming the randomness of single-point judgment, and enabling the system to make a more accurate root cause judgment after the first compensation is ineffective: whether to continue to deepen environmental compensation or to turn to equipment fault investigation, thereby greatly improving the pertinence of maintenance strategies and the reliability of system autonomy in complex scenarios.

[0051] Furthermore, by combining individual performance threshold criteria with the analysis of group spatial distribution characteristics, this invention achieves accurate identification of two very different types of faults: electromagnetic interference and biofouling. This technology upgrades the judgment of single numerical anomalies to intelligent pattern recognition that integrates equipment performance data and physical spatial information. This allows the system to accurately infer the underlying physical cause based on the spatial distribution pattern of anomalies, whether discrete or concentrated, thereby triggering adaptive filtering optimization at the signal level or manual maintenance guidance at the physical level. This greatly improves the accuracy of fault diagnosis and the pertinence of maintenance actions in complex deep-sea environments.

[0052] Furthermore, this invention achieves intelligent filtering of complex interference and final confirmation of the root cause of faults by introducing a parameter adaptive adjustment mechanism based on spatial distribution characteristics and a multi-round closed-loop verification decision process. This technical approach first accurately distinguishes the type of interference based on the abnormal distribution pattern and dynamically optimizes the signal processing link; then, through closed-loop verification of "adjustment-reassessment", the effectiveness of the measures is ensured; finally, after eliminating other possibilities, the physical fault of biological attachment is accurately identified and a precise maintenance command is triggered. This significantly improves the system's anti-interference capability, diagnostic certainty, and accuracy of maintenance guidance in real and complex deep-sea environments. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the intelligent measurement and analysis system for output data based on a deep-sea transducer array according to the present invention.

[0054] Figure 2 This is a flowchart of the analysis unit in the intelligent measurement and analysis system for output data of deep-sea transducer arrays based on the present invention. Detailed Implementation

[0055] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0056] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0057] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0058] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0059] Please see Figures 1-2 As shown, Figure 1 This is a schematic diagram of the intelligent measurement and analysis system for output data based on a deep-sea transducer array according to the present invention. Figure 2 This is a flowchart of the analysis unit in the intelligent measurement and analysis system for output data of deep-sea transducer arrays based on the present invention.

[0060] This invention relates to an intelligent measurement and analysis system for output data of a deep-sea transducer array, comprising:

[0061] A transducer array, consisting of several transducers arranged in a deep-sea region;

[0062] The recording unit, connected to the transducer array, includes several recording devices disposed in each transducer, for real-time acquisition and recording of the output data of the corresponding transducer;

[0063] A preprocessing unit, connected to the recording unit, is used to preprocess the output data;

[0064] An integration unit, connected to the preprocessing unit, is used to receive and integrate the preprocessed output data;

[0065] A computing unit, connected to the integration unit, is used to determine the output fluctuation characterization value of the transducer array based on the integrated output data.

[0066] An analysis unit, connected to the calculation unit, is used to determine whether the operating status of the transducer array is qualified based on the output fluctuation characterization value, and if it is not qualified, to determine the reason for the failure based on the variance of the sound pressure ratio of each transducer, and to generate corresponding processing instructions.

[0067] An adjustment unit is connected to the analysis unit, the preprocessing unit, and the transducer array, respectively, and is used to adjust at least one of the correction coefficients in the calculation unit, the operating frequency of the transducer array, or the data preprocessing parameters of the preprocessing unit according to the processing instructions generated by the analysis unit.

[0068] Specifically, there are no restrictions on the specific structure of the analyzer; it can be composed of logic components, including field-programmable processors, computers, and microprocessors within computers.

[0069] In this embodiment of the invention, the preprocessing of the output data includes data filtering: based on a preset effective value range or signal-to-noise ratio threshold, the original output data collected by the recording unit is initially filtered to remove obvious abnormal values ​​caused by instantaneous strong interference, sensor transient failure, or transmission packet loss; data noise reduction: the filtered data is processed using digital filtering algorithms (such as low-pass filtering, band-pass filtering, or adaptive filtering) to suppress and eliminate high-frequency environmental noise, inherent electronic noise of the system, and electromagnetic interference in specific frequency bands, and to extract effective signal components that reflect the true working state of the transducer.

[0070] Specifically, the computing unit determines the output fluctuation characterization value of the transducer array based on the integrated output data, wherein,

[0071] Calculate the sound pressure ratio of each transducer between the current cycle and the previous cycle to obtain the individual sound pressure ratio;

[0072] Calculate the average of the sound pressure ratios of all individuals to obtain the overall sound pressure ratio;

[0073] Obtain the current environmental parameters, and calculate a correction coefficient to characterize the degree of deviation of the environmental conditions based on the environmental parameters and the system's preset benchmark environmental parameters, wherein the greater the degree of deviation of the environmental conditions, the larger the correction coefficient;

[0074] Multiplying the overall sound pressure ratio by the correction coefficient yields the output fluctuation characterization value.

[0075] In this embodiment of the invention, the computing unit determines the output fluctuation characterization value of the transducer array based on the integrated output data through a series of steps. First, for each transducer in the array, the relative change value of the output sound pressure measured in the current monitoring cycle relative to the output sound pressure in the previous monitoring cycle is calculated. This value is called the individual sound pressure ratio, which is used to reflect the short-term change of the output energy of a single transducer. Next, the average value of the individual sound pressure ratios of all transducers is calculated to obtain a comprehensive sound pressure ratio that reflects the average relative change of the output energy of the entire array. At the same time, the system acquires the current actual environmental parameters, such as temperature and pressure. The system pre-stores baseline environmental parameters determined based on long-term observation data of the deployment area or laboratory calibration data. By comparing the current actual environmental parameters with the baseline environmental parameters, a correction coefficient is calculated. The core design principle of this correction coefficient is that the greater the deviation of the current environmental conditions from the preset baseline, the larger the calculated correction coefficient value. For example, the greater the difference between the deep-sea temperature and the baseline temperature, or the greater the difference between the pressure and the baseline pressure, the larger the correction coefficient. Finally, the calculated comprehensive sound pressure ratio is combined with the correction coefficient through multiplication to obtain the final output fluctuation characterization value. This design ensures that when environmental conditions deteriorate, the correction coefficient will amplify the final characterization value, so that the output fluctuation characterization value can more comprehensively and sensitively reflect the superimposed impact of adverse environmental changes and transducer performance fluctuations. The larger the value, the greater the negative impact on the overall operating status of the array.

[0076] This invention constructs a three-level calculation framework of individual fluctuation, overall average, and environmental compensation. It captures the microscopic changes of each transducer by calculating the individual sound pressure ratio, reflects the overall trend of the array by obtaining the comprehensive sound pressure ratio, and intelligently compensates for the benchmark drift caused by environmental factors by introducing a correction coefficient positively correlated with the degree of environmental deviation. This method effectively integrates and distinguishes the impact of equipment performance fluctuations and environmental interference, making the final output fluctuation characterization value a key indicator that truly and comprehensively reflects the overall operating status of the array in complex deep-sea environments. Based on the core design principle that the larger the environmental deviation, the larger the correction coefficient, this calculation method ensures the accuracy of system evaluation and the correctness of guidance. When environmental conditions deteriorate (such as excessively low temperature or excessively high pressure), the increased correction coefficient amplifies the output fluctuation characterization value, thereby revealing the negative impact of the superposition of environmental pressure and equipment performance fluctuations in a timely and complete manner. This effectively avoids misjudgments or omissions that may be caused by changes in the environmental benchmark, providing a logically consistent and highly sensitive reliable basis for subsequent analysis units to determine whether the operating status is "unqualified."

[0077] Specifically, the analysis unit determines whether the operating status of the transducer array is qualified based on the output fluctuation characterization value, wherein,

[0078] If the output fluctuation characterization value is greater than the preset output fluctuation characterization value, the analysis unit determines that the operating state of the transducer array is unqualified, and further calculates the variance of the sound pressure ratio of each transducer, and determines the reason for the unqualification based on the variance.

[0079] If the output fluctuation characterization value is less than or equal to the preset output fluctuation characterization value, the analysis unit determines that the transducer array is in a qualified operating state.

[0080] Specifically, the analysis unit determines the cause of non-compliance based on the variance, wherein,

[0081] If the variance is less than the preset variance, the analysis unit determines that the reason for non-compliance is fluctuation of environmental parameters;

[0082] If the variance is greater than or equal to the preset variance, the analysis unit determines that the reason for the non-compliance is a transducer malfunction and marks the abnormal transducer.

[0083] In this embodiment of the invention, taking a deep-sea array containing 8 transducers as an example, the method of the analysis unit for determining the state and making a preliminary judgment on the cause based on the output fluctuation characterization value is explained. During system operation, the calculation unit completes the calculation and inputs the output fluctuation characterization value of the current period to the analysis unit. The analysis unit stores a preset qualified threshold, which, as mentioned above, is determined through statistical analysis of historical normal data. For example, the threshold is set to 1.15. The analysis unit compares the current output fluctuation characterization value with the threshold (1.15). Scenario A: If the current value is 1.08, since it is less than the threshold 1.15, the analysis unit immediately determines that the entire transducer array is in a qualified operating state, without the need for subsequent variance calculation and root cause analysis, and the system enters the next monitoring cycle. Scenario B: If the current value is 1.25, since it is greater than the threshold of 1.15, the analysis unit determines that the array operation status is unqualified and immediately starts the next step of root cause localization analysis. After the unqualified status is determined, the analysis unit retrieves the individual sound pressure ratio data of all transducers calculated by the calculation unit. For example, the individual sound pressure ratios of the 8 transducers are: [0.95, 1.30, 1.28, 0.98, 1.31, 1.26, 0.96, 1.29]. Calculate the variance: The analysis unit first calculates the average value of this set of data (approximately 1.17), then calculates the square of the difference between each value and the average value, and then calculates the average of these squared values, which is the variance of the individual sound pressure ratio. This variance quantifies the consistency of the output fluctuations of all transducers. In this example, the calculated variance value is assumed to be 0.023. Variance threshold determination method: The determination of the preset variance (the threshold used for judgment) is similar to that of the qualified threshold, based on a large amount of individual sound pressure ratio data recorded by the system during long-term stable and fault-free operation. The variance of these historical data is calculated, and a certain percentile value (e.g., the 95th percentile) of its statistical distribution is taken as the preset variance threshold. For example, the preset variance threshold is set to 0.018. The calculated actual variance (0.023) is compared with the preset variance threshold (0.018). Case 1 (small variance): If the actual variance is less than 0.018, it indicates that the output of all transducers shows a highly consistent and unidirectional change (increasing or decreasing proportionally). This usually points to fluctuations in environmental parameters affecting the entire array (such as overall changes in temperature and pressure), rather than individual transducer failures. Case 2 (large variance): As in this example, the actual variance (0.023) is greater than or equal to 0.018, indicating that the output changes of each transducer are inconsistent and the fluctuations are significantly different. This strongly suggests that the problem may originate from the failure of some transducers themselves or be affected by local interference. The analysis unit will determine the cause of non-compliance as transducer failure based on this and provide a basis for subsequent labeling and refined diagnosis (such as distinguishing between electromagnetic interference and biofouling).

[0084] This invention achieves precise source tracing and intelligent initial screening of transducer array malfunctions through a two-level analysis and judgment mechanism based on output fluctuation characterization values ​​and individual sound pressure ratio variances. The mechanism first judges the overall health status through characterization values, and then, when an anomaly is detected, quickly distinguishes whether the problem originates from global environmental fluctuations or local transducer failures through variance analysis. This technical approach transforms the originally ambiguous problem of overall performance degradation into a clear classification that can be addressed in a targeted manner, providing an accurate decision-making basis for subsequent implementation of differentiated adaptive adjustments (such as environmental compensation or fault labeling), thereby significantly improving the intelligence level of system diagnosis and maintenance efficiency.

[0085] Specifically, when the analysis unit determines that the cause of the non-compliance is fluctuation of environmental parameters, the adjustment unit adjusts the correction coefficient based on the temperature parameter, wherein...

[0086] Adjust the correction factor according to the temperature parameter;

[0087] The temperature parameter is the regional average temperature after correction based on depth and regional ocean current velocity.

[0088] The lower the temperature parameter, the greater the increase in the correction coefficient.

[0089] In this embodiment of the invention, taking a deployment area at a depth of 3000 meters with a moderate ocean current as an example, the method of adaptively adjusting the correction coefficient based on temperature parameters is specifically explained. First, the system obtains the original average temperature of the area. This temperature is obtained by averaging measurements taken from multiple temperature sensors arranged around the transducer array; for example, a measured value of 2.0°C. Next, the original temperature is corrected for depth and ocean current to obtain more accurate temperature parameters that reflect the equivalent impact on transducer performance. Depth Correction: Since hydrostatic pressure increases with depth, increased pressure may suppress certain temperature sensitivities of the material. Therefore, a preset depth-pressure compensation coefficient table (obtained through experimental calibration) is consulted based on the array deployment depth (3000 meters). For example, for a depth of 3000 meters, the depth compensation coefficient obtained from the table is 0.98.

[0090] Ocean current velocity correction: The current ocean current velocity measured by the current meter is 0.3 m / s. Ocean currents accelerate heat exchange, which may cause a dynamic difference between the temperature measured by the sensor and the actual temperature of the transducer's core components. Based on the ocean current velocity, the system determines the ocean current correction coefficient using a preset empirical formula or lookup table. For example, for a moderate current velocity of 0.3 m / s, the ocean current correction coefficient is found to be 1.05. The final temperature parameter is calculated by multiplying the original average temperature of the region (2.0°C) by the depth compensation coefficient (0.98) and the ocean current correction coefficient (1.05), resulting in a corrected temperature parameter of 2.0 × 0.98 × 1.05 ≈ 2.06°C. This parameter more comprehensively reflects the actual impact of the environment's thermodynamic state on the transducer's performance than the original measurement. Then, the adjustment unit adjusts the correction coefficient used by the calculation unit (specifically, the temperature-related part) based on this temperature parameter (2.06°C). The system presets a reference temperature, such as 3.0°C, which corresponds to the optimal performance of the system design. The adjustment logic follows the principle that the lower the temperature parameter, the greater the increase in the correction coefficient: Calculate the temperature deviation: Subtract the current temperature parameter (2.06°C) from the reference temperature (3.0°C), resulting in a deviation of 0.94°C. Determine the adjustment amount: A non-linear adjustment function is pre-stored within the system. This function stipulates that for the same positive temperature deviation, the lower the temperature parameter (i.e., the colder the environment), the larger the increment of the correction coefficient per unit deviation. For example, assuming a temperature parameter of 2.5°C, a deviation of 0.94°C requires increasing the correction coefficient by 5%; while at the current temperature parameter of 2.06°C (lower), the same deviation of 0.94°C requires increasing the correction coefficient by 7%. Execute the adjustment: Based on the calculated adjustment amount (increase of 7%), the adjustment unit sends an instruction to the calculation unit to increase its current correction coefficient (assuming the original value is 1.0) used to calculate the output fluctuation characterization value by 7%, i.e., adjust it to 1.07. This adjustment aims to compensate for the sound propagation loss and transducer efficiency reduction caused by the decrease in temperature, so that the subsequently calculated output fluctuation characterization value can more realistically isolate the influence of ambient temperature and focus on the state of the equipment itself.

[0091] This invention achieves high-precision and adaptive compensation for the impact of environmental temperature fluctuations by introducing a comprehensive temperature parameter corrected for depth and ocean current velocity, and adjusting the correction coefficient nonlinearly according to its value. This technique overcomes the shortcomings of simply using raw temperature data for linear compensation, significantly improving the accuracy of system state assessment in complex deep-sea environments, and ensuring that subsequent diagnostic logic can operate reliably after eliminating major environmental interferences.

[0092] Specifically, during the process of adjusting the correction coefficient based on the temperature parameter, the operating frequency of each transducer is simultaneously adjusted so that the ratio of the adjusted operating frequency to the current resonant frequency of the corresponding transducer is within a preset range.

[0093] In this embodiment of the invention, it is assumed that the preset (nominal) operating frequency of a specific transducer in the array is 100kHz, and its preset resonant frequency is also 100kHz under standard laboratory conditions (e.g., 20°C, ambient pressure). In the low-temperature environment of the deep sea, the performance of its piezoelectric material changes, causing the current resonant frequency to drift. The system uses a built-in impedance analysis module or a frequency sweep excitation-response detection circuit to quickly scan the transducer and measure the frequency corresponding to its lowest impedance point or highest admittance point. This frequency is identified as its current resonant frequency; for example, the measured value has drifted to 102kHz. The adjustment unit calculates the ratio of the transducer's current operating frequency (still 100kHz) to its current resonant frequency (102kHz): 100 / 102 ≈ 0.980. The system's preset operating frequency-resonant frequency optimization range is 0.95 to 1.05. This range was determined experimentally to ensure the transducer's electrical-to-acoustic energy conversion efficiency remained above 95%. While the calculated ratio of 0.980 was within the preset range, it was close to the lower limit (0.95), indicating that the operating frequency was relatively low compared to its resonant frequency and not at its optimal state. Following the principle of bringing the ratio closer to 1, the adjustment unit issued a command to adjust the transducer's drive circuit, slightly increasing its operating frequency from 100kHz to 101.5kHz. After adjustment, the new frequency ratio was: 101.5 / 102≈0.995. This value is closer to 1 and firmly located in the central region of the preset range (0.95-1.05), indicating that the transducer has returned to its high-efficiency operating point. This frequency adjustment process is triggered synchronously and executed in parallel with the adjustment of the correction coefficient based on temperature parameters (as mentioned in the previous example, the correction coefficient is increased by 7% due to the decrease in temperature). The underlying logic is that temperature changes are the common cause of resonant frequency drift (requiring adjustment of the operating frequency tracking) and changes in sound propagation efficiency (requiring adjustment of the correction coefficient for compensation). The system corrects both of these effects simultaneously through a single diagnostic, thereby achieving comprehensive and multi-dimensional compensation for the impact of ambient temperature fluctuations, ensuring the stability of the overall array output performance.

[0094] This invention achieves dynamic locking of the transducer's operating frequency to its time-varying resonance characteristics by introducing a closed-loop operating frequency tracking and adjustment mechanism based on the measured resonant frequency while adjusting environmental compensation parameters. This technique effectively overcomes the transducer detuning problem caused by changes in ambient temperature, ensuring that each transducer always operates in a highly efficient state, thereby improving the energy conversion efficiency and output stability of the entire array from the source.

[0095] Specifically, after the adjustment unit adjusts the correction coefficient based on the temperature parameter, the analysis unit makes a second judgment on whether the operating status of the transducer array is qualified. If the analysis unit determines that the operating status of the transducer array is unqualified, it determines the processing method based on the historical curve constructed from the period and output fluctuation characterization values ​​in the historical records.

[0096] The analysis unit calculates the integral value of the historical curve within a preset period:

[0097] If the integral value is less than the preset integral value, the analysis unit determines that the reason for the failure is a transducer malfunction and marks the malfunctioning transducer.

[0098] If the integral value is greater than or equal to the preset integral value, the adjustment unit repeats the adjustment process of the correction coefficient.

[0099] In this embodiment of the invention, assuming an array containing 8 transducers, after the adjustment unit performs temperature-based correction coefficient adjustment and operating frequency synchronization tracking, the output fluctuation characterization value recalculated by the calculation unit is 1.22. This value is still greater than the preset qualified threshold (e.g., 1.15). At this time, the analysis unit performs a second judgment, confirming that the operating status is still unqualified, and then starts analysis based on historical curves. The analysis unit extracts the period-output fluctuation characterization value data pairs from the stored historical records for a recent period (e.g., the most recent 10 monitoring cycles), constructs a historical curve with the cycle number as the horizontal axis and the corresponding output fluctuation characterization value as the vertical axis. This curve intuitively shows the trend and amplitude of system performance fluctuations over time. The analysis unit calculates the integral value of this historical curve within a preset number of cycles (e.g., the most recent 5 cycles). The calculation of the integral value can be understood as calculating the area enclosed by the curve segment and the horizontal axis. This area value comprehensively reflects the cumulative severity and duration of abnormal system fluctuations within a specific time period. Assume the calculated integral value is 6.3 (dimensionless). Method for determining the preset integration threshold: The preset integration value is a key judgment threshold, which is determined as follows: Collect all historical event segments in the long-term operation of the system that were determined to be affected only by environmental fluctuations and eventually recovered to normal through compensation. Calculate the integration value of the historical curve of these event segments within the same preset number of periods (5 periods), and then take a higher percentile (e.g., 80th percentile) of these integration values ​​as the preset integration threshold. For example, the preset integration value is set to 7.0 through statistical calculation. The analysis unit compares the calculated actual integration value (6.3) with the preset integration value (7.0): Case 1 (smaller integration value): The actual integration value 6.3 is less than the preset integration value 7.0. This indicates that although recent abnormal fluctuations exist, their cumulative "severity-time" magnitude is relatively low and has not reached the level of typical continuous environmental interference. Based on this, the analysis unit infers that the problem is more likely to originate from a sudden failure or performance degradation of individual transducers, rather than continuous environmental factors. The system will determine the cause as "transducer abnormality" and enter the process of accurately locating and marking the abnormal transducer. Scenario 2 (Large Integral Value): If the actual integral value is greater than or equal to 7.0, it indicates that the anomaly is characterized by high intensity and long duration, which is highly consistent with typical environmental disturbance patterns. The analysis unit determines that the initial compensation adjustment may be insufficient or the environment is still changing. In this case, the system will instruct the adjustment unit to repeat the adjustment process of the correction coefficient (possibly with a larger adjustment step size or by introducing other environmental parameters for joint compensation) to cope with stronger environmental fluctuations.

[0100] This invention introduces a secondary decision-making mechanism based on historical time series integration to achieve intelligent differentiation and triage of continuous environmental fluctuations and sudden equipment failures. This technique uses the time accumulation characteristics of fluctuation energy as a judgment basis, overcoming the randomness of single-point judgment. This enables the system to make a more accurate root cause judgment after the first compensation is ineffective: whether to continue to deepen environmental compensation or to turn to equipment fault investigation, thereby greatly improving the pertinence of maintenance strategies and the reliability of system autonomy in complex scenarios.

[0101] Specifically, the analysis unit marks abnormal transducers, wherein,

[0102] If the individual sound pressure ratio of a single transducer is not within the preset sound pressure ratio range, the analysis unit marks the transducer.

[0103] After the analysis unit marks the transducers, the analysis unit calculates the distribution distance of all marked transducers in the array;

[0104] If the distribution distance is greater than the preset distribution distance, the analysis unit determines that the reason for the non-compliance is external electromagnetic interference, and generates an adjustment instruction for the data preprocessing parameters of the preprocessing unit.

[0105] If the distribution distance is less than or equal to the preset distribution distance, the analysis unit determines that the reason for the non-compliance is biological attachment and generates a manual cleaning notification.

[0106] In this embodiment of the invention, the analysis unit compares the calculated individual sound pressure ratio (SPR) of each transducer with its own preset normal operating range. This range is statistically derived from historical data of each transducer during long-term, fault-free, and stable operation. If the SPR of a transducer is higher than the upper limit of its range or lower than its lower limit, it is determined to be an output anomaly, and the analysis unit immediately electronically marks that transducer. Assume that several transducers in the array are marked during this detection cycle. Subsequently, the analysis unit calls the physical placement coordinates of the array to calculate the spatial distribution distance between all marked transducers. This calculation typically involves determining the geometric center of the marked points and calculating the average distance between each marked point and this center to quantify the dispersion or concentration of anomaly points in the array. A distance judgment threshold is preset within the system, which is experimentally set based on the array's physical dimensions and interference propagation characteristics. If the calculated distribution distance is greater than the preset threshold, it indicates that the abnormal transducers are widely distributed and spatially discrete within the array, lacking spatial correlation. This pattern closely matches the characteristics of wide-area electromagnetic interference (whose field strength may cover the entire array area, but the degree of influence on transducers at different locations and with different electrical characteristics is random). Based on this, the analysis unit determines that the failure is caused by external electromagnetic interference and generates instructions for the preprocessing unit, requiring it to adjust the data preprocessing parameters (such as increasing the filtering strength) to suppress the manifestation of such interference in the signal. If the calculated distribution distance is less than or equal to the preset threshold, it indicates that the abnormal transducers are spatially clustered and relatively concentrated. This pattern strongly points to local physical factors, the most typical of which is marine organism attachment. This is because biological attachment usually occurs on the surface of transducers in specific water layers, specific orientations, or specific materials, leading to a decrease in their acoustic performance and thus exhibiting clustered abnormal characteristics in spatial location. Based on this, the analysis unit determines that the failure is caused by biological attachment and generates a manual cleaning notification containing the location information of the abnormal transducers to guide maintenance personnel to perform precise operations.

[0107] This invention achieves accurate identification of two distinct types of faults: "electromagnetic interference" and "biofouling," by combining individual performance threshold criteria with analysis of group spatial distribution characteristics. This technology upgrades the judgment of single numerical anomalies to intelligent pattern recognition that integrates equipment performance data and physical spatial information. This allows the system to accurately infer the underlying physical cause based on the spatial distribution pattern (discrete or concentrated) of anomalies, thereby triggering adaptive filtering optimization at the signal level or manual maintenance guidance at the physical level. This greatly improves the accuracy of fault diagnosis and the targeting of maintenance actions in the complex environment of the deep sea.

[0108] Specifically, the adjustment unit adjusts the data preprocessing parameters based on the adjustment instructions of the data preprocessing parameters of the preprocessing unit, wherein,

[0109] Set a distance reference value, and calculate the ratio of the distribution distance to the distance reference value as an adjustment coefficient;

[0110] The cutoff frequency of the filtering algorithm is adjusted to be the product of the original cutoff frequency and the adjustment coefficient;

[0111] The filter order is adjusted to be the product of the original order and the adjustment coefficient.

[0112] Specifically, after the adjustment unit adjusts the data preprocessing parameters based on the adjustment instructions of the preprocessing unit, the analysis unit again determines whether the operating status of the transducer array is qualified.

[0113] If the analysis unit determines again that the transducer array is not in good working order, the analysis unit determines that the reason for the failure is biological attachment and generates a manual cleaning notification.

[0114] In this embodiment of the invention, the system pre-sets a distance reference value based on the typical physical size and layout density of the array. This value represents a typical scale of the random, discrete spatial distribution of abnormal transducers. After the analysis unit calculates the actual distribution distance of all marked transducers, the adjustment unit compares the two and calculates the ratio of the distribution distance to the distance reference value. This ratio serves as the scaling factor for this adjustment. Subsequently, the adjustment unit dynamically adjusts the key parameters of the digital filtering algorithm in the preprocessing unit based on this scaling factor. Specifically, the cutoff frequency of the currently used filtering algorithm is set to the product of the original cutoff frequency and the scaling factor; simultaneously, the filter order is also set to the product of the original order and the same scaling factor. The core logic is that a larger distribution distance indicates a more broad-spectrum random characteristic of the suspected interference, and the scaling factor is greater than one. Therefore, by increasing the cutoff frequency and the filter order, stronger suppression of wider-band interference is achieved; conversely, fine-tuning is performed. After completing the above adaptive parameter adjustment, the system immediately starts a new and complete data acquisition, preprocessing, integration, calculation, and analysis process. Based on the latest data, the analysis unit re-determines whether the transducer array's operating status is acceptable. If the result is acceptable, it proves that the parameter adjustments are effective, the system has successfully suppressed electromagnetic interference, and stable operation has been restored. If the result is still unacceptable, it indicates that the anomaly persists even after enhanced filtering for electromagnetic interference. At this point, the system performs a final attribution: since the possibility of global environmental fluctuations and wide-area electromagnetic interference has been ruled out, and the abnormal transducers exhibit a spatially clustered distribution (previously determined to be small in distance), the root cause points solely to the local physical factor of biological attachment. The analysis unit then generates a clear manual cleaning notification containing specific location information.

[0115] This invention achieves intelligent filtering of complex interference and final confirmation of the root cause of faults by introducing a parameter adaptive adjustment mechanism based on spatial distribution characteristics and a multi-round closed-loop verification decision process. This technical approach first accurately distinguishes the type of interference based on the abnormal distribution pattern and dynamically optimizes the signal processing link; then, through closed-loop verification of "adjustment-reassessment", the effectiveness of the measures is ensured; finally, after ruling out other possibilities, the physical fault of biological attachment is accurately identified and a precise maintenance command is triggered. This significantly improves the system's anti-interference capability, diagnostic certainty, and accuracy of maintenance guidance in real complex deep-sea environments.

[0116] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0117] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent measurement and analysis system for output data based on a deep-sea transducer array, characterized in that, include: A transducer array, consisting of several transducers arranged in a deep-sea region; The recording unit, connected to the transducer array, includes several recording devices disposed in each transducer, for real-time acquisition and recording of the output data of the corresponding transducer; A preprocessing unit, connected to the recording unit, is used to preprocess the output data; An integration unit, connected to the preprocessing unit, is used to receive and integrate the preprocessed output data; A computing unit, connected to the integration unit, is used to determine the output fluctuation characterization value of the transducer array based on the integrated output data. An analysis unit, connected to the calculation unit, is used to determine whether the operating status of the transducer array is qualified based on the output fluctuation characterization value, and if it is not qualified, to determine the reason for the failure based on the variance of the sound pressure ratio of each transducer, and to generate corresponding processing instructions. An adjustment unit is connected to the analysis unit, the preprocessing unit, and the transducer array, respectively, and is used to adjust at least one of the correction coefficients in the calculation unit, the operating frequency of the transducer array, or the data preprocessing parameters of the preprocessing unit according to the processing instructions generated by the analysis unit. The computing unit determines the output fluctuation characterization value of the transducer array based on the integrated output data, wherein, Calculate the sound pressure ratio of each transducer between the current cycle and the previous cycle to obtain the individual sound pressure ratio; Calculate the average of the sound pressure ratios of all individuals to obtain the overall sound pressure ratio; Obtain the current environmental parameters, and calculate a correction coefficient to characterize the degree of deviation of the environmental conditions based on the environmental parameters and the system's preset benchmark environmental parameters, wherein the greater the degree of deviation of the environmental conditions, the larger the correction coefficient; Multiplying the overall sound pressure ratio by the correction coefficient yields the output fluctuation characterization value; The adjustment unit adjusts the data preprocessing parameters based on the adjustment instructions of the data preprocessing parameters from the preprocessing unit, wherein, Set a distance reference value, and calculate the ratio of the distribution distance to the distance reference value as an adjustment coefficient; Adjust the cutoff frequency of the filtering algorithm to the product of the original cutoff frequency and the adjustment coefficient; Adjust the filter order to the product of the original order and the adjustment coefficient.

2. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 1, characterized in that, The analysis unit determines whether the operating status of the transducer array is qualified based on the output fluctuation characterization value, wherein, If the output fluctuation characterization value is greater than the preset output fluctuation characterization value, the analysis unit determines that the operating status of the transducer array is unqualified, and further calculates the variance of the sound pressure ratio of each transducer, and determines the reason for the unqualification based on the variance. If the output fluctuation characterization value is less than or equal to the preset output fluctuation characterization value, the analysis unit determines that the transducer array is in a qualified operating state.

3. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 1, characterized in that, The analysis unit determines the cause of non-compliance based on the variance, wherein, If the variance is less than the preset variance, the analysis unit determines that the reason for non-compliance is fluctuation of environmental parameters; If the variance is greater than or equal to the preset variance, the analysis unit determines that the reason for the non-compliance is a transducer malfunction and marks the abnormal transducer.

4. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 3, characterized in that, If the analysis unit determines that the cause of the non-compliance is fluctuation of environmental parameters, the adjustment unit adjusts the correction coefficient based on the temperature parameter, wherein... Adjust the correction factor according to the temperature parameters; The temperature parameter is the regional average temperature after correction based on depth and regional ocean current velocity. The lower the temperature parameter, the greater the increase in the correction coefficient.

5. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 4, characterized in that, During the process of adjusting the correction coefficient based on the temperature parameter, the operating frequency of each transducer is adjusted synchronously so that the ratio of the adjusted operating frequency to the current resonant frequency of the corresponding transducer is within a preset range.

6. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 4, characterized in that, After the adjustment unit adjusts the correction coefficient based on the temperature parameter, the analysis unit makes a second judgment on whether the operating status of the transducer array is qualified. If the analysis unit determines that the operating status of the transducer array is unqualified, it determines the processing method based on the historical curve constructed from the period and output fluctuation characterization values ​​in the historical records. The analysis unit calculates the integral value of the historical curve within a preset period: If the integral value is less than the preset integral value, the analysis unit determines that the reason for the failure is a transducer malfunction and marks the malfunctioning transducer. If the integral value is greater than or equal to the preset integral value, the adjustment unit repeats the adjustment process of the correction coefficient.

7. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 6, characterized in that, The analysis unit marks abnormal transducers, wherein, If the individual sound pressure ratio of a single transducer is not within the preset sound pressure ratio range, the analysis unit marks the transducer. After the analysis unit marks the transducers, the analysis unit calculates the distribution distance of all marked transducers in the array; If the distribution distance is greater than the preset distribution distance, the analysis unit determines that the reason for the non-compliance is external electromagnetic interference, and generates an adjustment instruction for the data preprocessing parameters of the preprocessing unit. If the distribution distance is less than or equal to the preset distribution distance, the analysis unit determines that the reason for the non-compliance is biological attachment and generates a manual cleaning notification.

8. The intelligent measurement and analysis system for output data based on a deep-sea transducer array according to claim 7, characterized in that, After the adjustment unit adjusts the data preprocessing parameters based on the adjustment instructions of the preprocessing unit, the analysis unit again determines whether the operating status of the transducer array is qualified. If the analysis unit determines again that the transducer array is not in good working order, the analysis unit determines that the reason for the failure is biological attachment and generates a manual cleaning notification.

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