A method, device and system for diagnosing cable faults in a tethered underwater robot.

Abstract

This invention relates to the field of cable fault diagnosis technology, specifically to a method, apparatus, and system for diagnosing cable faults in a tethered underwater robot. The method includes acquiring cable voltage data and motor rotation data of the underwater robot within a target time period, where the motor rotation data includes the motor rotation rate. The target time period is the time from the underwater robot's launch to its descent to shore. The cable voltage data is segmented based on the motor rotation data to obtain multiple voltage ranges. Fault analysis is performed on these multiple voltage ranges to obtain the cable detection results of the underwater robot. If the cable detection results are abnormal, an alarm signal and fault diagnosis information are generated. This invention, by collecting and analyzing cable voltage data and motor rotation data of the underwater robot, identifies potential cable problems, promptly detects anomalies, and quickly generates alarm signals and fault diagnosis information, thus improving the accuracy and timeliness of fault detection.

Description

Technical Field

[0001] This invention relates to the field of cable fault diagnosis technology, and specifically to a cable fault diagnosis method, device and system for a tethered underwater robot. Background Technology

[0002] Tethered underwater vehicles (ROVs) are specialized robots widely used in marine exploration, seabed construction, search and rescue, and other fields. Their cables serve not only as a medium for transmitting power but also as a crucial channel for remote control and data communication.

[0003] The cables of tethered underwater robots provide a continuous power supply and stable signal transmission, ensuring that the underwater robot can receive commands and send feedback. Due to the complexity of the underwater environment, changes in water flow can cause abnormal changes in water pressure on the cables. These changes in water pressure may cause additional mechanical stress on the cables, affecting their structural integrity and even leading to cable breakage and ultimately compromising the normal operation of the underwater robot. Summary of the Invention

[0004] To address the technical problem that tethered underwater robots cannot accurately detect anomalies underwater, thus hindering their timely discovery and handling, this invention aims to provide a cable fault diagnosis method, device, and system for tethered underwater robots. The specific technical solution adopted is as follows:

[0005] In a first aspect, embodiments of the present invention provide a cable fault diagnosis method for a tethered underwater robot, applied to a cable fault diagnosis system for a tethered underwater robot, the method comprising:

[0006] Acquire cable voltage data and motor rotation data of the underwater robot within a target time period. The motor rotation data includes the motor rotation rate. The target time period is the time from when the underwater robot is launched into the water to when it comes ashore.

[0007] The cable voltage data is segmented based on the motor rotation data to obtain multiple voltage ranges;

[0008] Fault analysis was performed on the multiple voltage ranges to obtain the cable inspection results of the underwater robot;

[0009] If the cable detection result is abnormal, an alarm signal and fault diagnosis information will be generated.

[0010] Secondly, embodiments of the present invention provide a cable fault diagnosis system for a tethered underwater robot, including a memory and a processor. The memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the cable fault diagnosis system for the tethered underwater robot implements the cable fault diagnosis method for the tethered underwater robot as described in the first aspect.

[0011] Thirdly, a computer device is provided, including a memory and a processor, the memory being connected to the processor, the processor being configured to execute one or more computer programs stored in the memory, wherein when the processor executes the one or more computer programs, the computer device enables the cable fault diagnosis method for a tethered underwater robot as described in the first aspect.

[0012] In a fourth aspect, embodiments of the present invention provide a cable fault diagnosis device for a tethered underwater robot, applied to a cable fault diagnosis system for a tethered underwater robot, the device comprising:

[0013] The acquisition unit is used to acquire cable voltage data and motor rotation data of the underwater robot within a target time period. The motor rotation data includes the motor rotation rate. The target time period is the time period from when the underwater robot is launched into the water to when it comes ashore.

[0014] The processing unit is used to segment the cable voltage data according to the motor rotation data to obtain multiple voltage ranges;

[0015] The analysis unit is used to perform fault analysis on the multiple voltage ranges to obtain the cable detection results of the underwater robot.

[0016] The generation unit is used to generate an alarm signal and fault diagnosis information if the cable detection result is an abnormal detection result.

[0017] In a fifth aspect, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the cable fault diagnosis method for a tethered underwater robot as described in the first aspect.

[0018] The present invention has the following beneficial effects: By acquiring cable voltage data and motor rotation speed during the underwater robot's operation from underwater to ashore, the present invention can monitor the robot's operating status in real time, ensuring the integrity and accuracy of the data; by segmenting the voltage data according to the motor rotation speed, the relationship between voltage changes and motor speed can be accurately identified, thereby more accurately locating potential cable fault points; fault analysis of multiple voltage ranges helps to identify potential cable problems, detect anomalies in a timely manner, and avoid greater losses caused by faults; once an anomaly is detected, the system can quickly generate alarm signals and fault diagnosis information, notify relevant personnel for timely handling, reduce downtime and maintenance costs, ensure the continuity and safety of underwater robot operations, and avoid operation interruptions or equipment damage caused by cable faults. Attached Figure Description

[0019] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a cable fault diagnosis method for a tethered underwater robot according to an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of the structure of a cable fault diagnosis device for a tethered underwater robot provided in one embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of the structure of a computer device provided in one embodiment of the present invention. Detailed Implementation

[0023] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a cable fault diagnosis method for a tethered underwater robot proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0025] The present invention will now be described in detail through specific embodiments.

[0026] An embodiment of the present invention provides a cable fault diagnosis system for a tethered underwater robot. The cable fault diagnosis system for a tethered underwater robot may be composed of the following components: a data acquisition module, a data transmission module, a ground control center, and an alarm and display module.

[0027] The data acquisition module includes a data acquisition card and a signal conditioning module. The data acquisition card converts the analog signals collected by the sensors into digital signals for computer processing. The signal conditioning module amplifies, filters, and isolates the sensor signals to ensure signal quality.

[0028] The communication interface in the data transmission module enables data transmission between the underwater robot and the ground control center, which can be wired or wireless. The data transmission cable / wireless module is used to transmit data between the underwater robot and the ground station.

[0029] The ground control center includes a data processing unit and fault diagnosis software. The data processing unit, comprising computer hardware and software, is used to receive, store, process, and analyze the acquired data. The fault diagnosis software is used to perform data preprocessing, spectrum analysis, fault feature extraction, and diagnostic algorithms.

[0030] The alarm and display module emits an audible and visual alarm when a fault is detected, notifying the operator, and displays voltage data, motor speed, and fault diagnosis results in real time.

[0031] Through the coordinated work of these components, the cable fault diagnosis system can effectively monitor the cable status of underwater robots, promptly detect potential faults, and take corresponding maintenance measures to ensure the safety and efficiency of underwater operations.

[0032] The following describes in detail, with reference to the accompanying drawings, a specific scheme for diagnosing cable faults in a tethered underwater robot provided by the present invention.

[0033] Please see Figure 1 This document illustrates a flowchart of a cable fault diagnosis method for a tethered underwater robot according to an embodiment of the present invention. Applied to a cable fault diagnosis system for a tethered underwater robot, the method includes the following steps:

[0034] S10. Obtain cable voltage data and motor rotation data of the underwater robot within a target time period. The motor rotation data includes the motor rotation rate. The target time period is the time from when the underwater robot is launched into the water to when it comes ashore.

[0035] Underwater robots are typically equipped with various sensors to collect cable voltage and motor rotation data. These sensors may include, but are not limited to, voltage testing modules and motor encoders. The voltage testing module monitors voltage changes in the cable in real time, while the motor encoder provides precise data on motor rotation, including speed and direction. Specifically, the sampling rate is set to 30 ks / s, with 3000 samples per cycle, and data collection for 20 seconds under normal conditions.

[0036] The cable voltage data includes the cable's real-time voltage value, voltage fluctuation, peak value, valley value, etc., which can reflect the electrical health status of the cable.

[0037] Among them, motor rotation data includes the motor speed (rotation rate), rotation direction, rotation frequency, etc. Motor rotation data helps to analyze the motor's workload and efficiency.

[0038] The target time period refers to the entire period from when the underwater robot is launched into the water until it returns to shore after completing its mission. During this time period, the underwater robot needs to perform a series of predetermined tasks, therefore the time range for data acquisition must cover the entire operation cycle.

[0039] Furthermore, based on the target time period, ensure that cable voltage data and motor rotation data are recorded synchronously on the same time axis for correlation analysis.

[0040] As can be seen, by acquiring data from the underwater robot within the target time period, this embodiment ensures that the cable and motor status of the underwater robot are effectively monitored throughout the entire operation cycle, thereby improving the safety and reliability of the operation.

[0041] S20. The cable voltage data is segmented according to the motor rotation data to obtain multiple voltage ranges.

[0042] The specific implementation process of S20 can be found in the detailed descriptions of S101-S103, and will not be repeated here.

[0043] As mentioned in S10, the motor rotation data and cable voltage data are synchronized in time, thus accurately segmenting the voltage data according to the motor status.

[0044] The segmentation process divides the continuous voltage data stream into stages based on the motor's rotation, with each stage corresponding to a voltage data interval. Specifically, a sliding window method or an event-based segmentation method can be used to ensure the accuracy and effectiveness of the segmentation. Segmentation makes it easier to extract the characteristics of each voltage interval, thus providing a better understanding of the relationship between the motor's operating state and the voltage.

[0045] In practice, motor rotation data is analyzed to determine segmentation criteria. For example, segmentation can be based on points of change in motor speed, stable speed ranges, or specific speed thresholds. If the motor speed remains stable over a period of time, the voltage data within that period can be divided into a voltage range. If the motor speed changes significantly, such as accelerating or decelerating, the voltage data can be segmented into different ranges at these points of change. If the motor performs specific actions or events (such as starting, stopping, or commutating), voltage ranges can be defined based on these events. Feature extraction and analysis are performed on each voltage range, including calculating statistical indicators such as the average voltage, standard deviation, peak value, and valley value. The segmentation is then checked for rationality to ensure that each voltage range accurately reflects the motor's operating state at that speed.

[0046] Therefore, voltage anomalies can be more easily detected within different voltage ranges, thereby diagnosing potential motor or cable problems.

[0047] As can be seen, this embodiment uses segmented processing to analyze voltage data more effectively, providing support for the condition monitoring and maintenance of underwater robots.

[0048] S30. Perform fault analysis on the multiple voltage ranges to obtain the cable detection results of the underwater robot.

[0049] The specific implementation process of S20 can be found in the detailed descriptions of S104-S107, and will not be repeated here.

[0050] Fault analysis aims to identify and diagnose potential anomalies or faults in cables, ensuring the safety and reliability of underwater robots during operation. By analyzing voltage ranges, problems can be detected early, preventing equipment downtime or damage due to cable faults.

[0051] By analyzing the voltage characteristics of each voltage range, common fault modes can be identified, such as overvoltage, undervoltage, and abnormal voltage fluctuations. These fault modes can be identified and classified using signal processing techniques and data analysis tools (such as spectrum analysis and time-domain analysis).

[0052] The cable testing results include both abnormal and normal test results.

[0053] As can be seen, this embodiment uses fault analysis to ensure that the underwater robot's cables remain in good working condition during mission execution, reducing operation interruptions and safety risks caused by cable failures.

[0054] S40. If the cable detection result is an abnormal detection result, generate an alarm signal and fault diagnosis information.

[0055] The alarm signal can take many forms, such as audible and visual alarms, vibration alerts, etc., to ensure effective transmission in different environments.

[0056] Fault diagnosis information typically includes abnormal voltage and current data, historical fault records, etc. It provides detailed data on the type, location, and severity of the fault. If the fault is severe, immediate adjustments or suspension of the mission may be necessary, along with the development of contingency plans to protect equipment and mission objectives. Repair may require dispatching divers or using remotely operated underwater vehicles (ROVs) for on-site inspection and repair. The chosen repair method depends on the depth and complexity of the fault.

[0057] Optionally, after repair, system testing must be performed to ensure the problem has been resolved. Testing includes functional testing and safety verification to ensure the cable is back to normal and meets all operating standards. Test results will be recorded for future reference and analysis.

[0058] As can be seen, this embodiment can significantly improve the safety and reliability of underwater robot operations by providing timely alarms and detailed fault diagnosis information, and reduce downtime and potential safety risks caused by cable failures.

[0059] The present invention has the following beneficial effects: By acquiring cable voltage data and motor rotation speed during the underwater robot's operation from underwater to ashore, the present invention can monitor the robot's operating status in real time, ensuring the integrity and accuracy of the data; by segmenting the voltage data according to the motor rotation speed, the relationship between voltage changes and motor speed can be accurately identified, thereby more accurately locating potential cable fault points; fault analysis of multiple voltage ranges helps to identify potential cable problems, detect anomalies in a timely manner, and avoid greater losses caused by faults; once an anomaly is detected, the system can quickly generate alarm signals and fault diagnosis information, notify relevant personnel for timely handling, reduce downtime and maintenance costs, ensure the continuity and safety of underwater robot operations, and avoid operation interruptions or equipment damage caused by cable faults.

[0060] S101. In one embodiment, the motor rotation data includes the motor rotation direction. The step of segmenting the cable voltage data based on the motor rotation data to obtain multiple voltage intervals includes: plotting the motor rotation rate within the target time period to obtain a motor rotation rate curve; segmenting the motor rotation rate curve according to a first preset algorithm to obtain a motor speed subsequence corresponding to each motor rotation rate; analyzing the motor rotation rate curve to obtain the maximum and minimum rotation rates; dividing the motor rotation rate into intervals based on the maximum and minimum rotation rates to obtain multiple first speed rate intervals and speed difference values; matching each motor speed subsequence with the multiple first speed rate intervals to obtain multiple second speed rate intervals containing the corresponding motor speed subsequences; processing the multiple second speed rate intervals based on the motor rotation direction and the speed difference values ​​to obtain multiple third speed rate intervals; and segmenting the cable voltage data based on the multiple third speed rate intervals to obtain multiple voltage intervals.

[0061] The first preset algorithm can be the PAA (Piecewise Aggregate Approximation) algorithm. PAA is a time series data dimensionality reduction method that approximates the original time series by dividing the time series into equal-length segments and aggregating (usually taking the average) each segment. When processing motor rotation speed curves, PAA can effectively extract key features while reducing the amount of data, facilitating subsequent analysis.

[0062] The PAA algorithm divides the entire motor speed curve into a fixed number of segments. The length of each segment is the original sequence length divided by the number of segments. For each segment, the PAA algorithm calculates the average value of all data points within that segment; this average value represents the characteristic value of that segment. After PAA processing, the original motor speed curve is transformed into a simplified time series composed of these average values, i.e., a motor speed subsequence. These subsequences retain the main trends and characteristics of the original sequence but have a smaller data volume, making them easier to process and analyze.

[0063] The plotting process can utilize data visualization tools such as Matplotlib or Excel to visualize the change in motor rotation speed over time as a motor rotation speed curve. The motor rotation speed curve should clearly show the fluctuations and trends in rotational speed.

[0064] In the process of dividing the motor rotation speed into intervals based on the maximum and minimum rotation speeds to obtain multiple first speed speed intervals and speed difference values, the following formula can be used as a reference:

[0065]

[0066] in, This represents the difference in rotational speed between different intervals. This represents the boundary value where the rotational speed is relatively small in the i-th interval. This represents the boundary value where the rotational speed is relatively large in the i-th interval. Indicates the maximum rotational speed and Indicates the minimum rotational speed. Indicates the speed range.

[0067] Each motor speed subsequence is matched with multiple first speed rate intervals to determine the interval to which they belong, resulting in multiple second speed rate intervals containing the corresponding motor speed subsequences.

[0068] The specific implementation process of segmenting the cable voltage data according to the multiple third rotation speed ranges to obtain multiple voltage ranges can be referred to the description in S102, and will not be repeated here.

[0069] The specific implementation process of segmenting the cable voltage data according to the multiple third rotation speed ranges to obtain multiple voltage ranges can be referred to the description in S103, and will not be repeated here.

[0070] As can be seen, this embodiment accurately analyzes the motor's operating state and how the cable voltage responds to changes in motor speed, thereby providing data support for fault diagnosis and performance optimization.

[0071] S102. In one embodiment, the step of processing the plurality of second speed rate intervals according to the motor rotation direction and the speed difference value to obtain a plurality of third speed rate intervals includes: obtaining a first target speed rate interval and the first motor rotation direction corresponding to the first target speed rate interval, a second target speed rate interval and the second motor rotation direction corresponding to the second target speed rate interval, wherein the first target speed rate interval and the second target speed rate interval are any two adjacent speed rate intervals among the plurality of second speed rate intervals; processing the first target speed rate interval and the first motor rotation direction corresponding to the first target speed rate interval, the second target speed rate interval... The rotation direction of the second motor corresponding to the second target speed range and the speed difference value are calculated to obtain the fluctuation degree between the first target speed range and the second target speed range. If the fluctuation degree is less than the preset fluctuation degree, the first target speed range and the second target speed range are merged to obtain the merged third target speed range. Multiple target speed ranges are traversed to obtain multiple third speed ranges. The multiple third speed ranges include multiple third target speed ranges and multiple fourth target speed ranges. The fourth target speed range is the target speed range when the fluctuation degree is greater than or equal to the preset fluctuation degree.

[0072] Specifically, any two adjacent intervals are selected from multiple second speed ranges and labeled as the first target speed range and the second target speed range, respectively. Simultaneously, the motor rotation directions corresponding to these two intervals are obtained and labeled as the first motor rotation direction and the second motor rotation direction, respectively.

[0073] Specifically, in calculating the fluctuation degree between the first target speed range and the second target speed range by considering the first target speed range and the corresponding rotation direction of the first motor, the second target speed range and the corresponding rotation direction of the second motor, and the speed difference value, the following formula can be used as a reference:

[0074]

[0075] in, and Let represent the angles of the motor direction in the v-th and v+1-th segments, respectively. Indicates the degree of change in the angle between two directions. and These represent the motor speeds of the v-th and v+1-th segments, respectively. This indicates the range of rotational speeds within each speed range. The larger this value, the greater the voltage fluctuation. The degree of fluctuation between the first target speed range and the second target speed range.

[0076] in, It is a function commonly used in multi-class classification problems, which transforms any real vector into a probability distribution. This is used to standardize the calculated volatility so that its sum is 1, so that the result can be interpreted as a probability distribution of volatility between different intervals.

[0077] in, This is a sine function used to calculate the ratio of the side opposite an angle to the hypotenuse in a right triangle. In this scheme... Used to calculate the degree of change in the angle between two directions. The sine function has a value between -1 and 1, and it can be used to measure the similarity or degree of change between two directions. Specifically, if the two directions are completely aligned (i.e., the angle is 0 degrees), the sine value is 0; if the angle is 90 degrees, the sine value is 1, indicating the greatest change. In this way, It can help assess the degree of change between the directions of the two motors.

[0078] in, This represents the angle between the directions of the v-th and v+1-th segment motors. This represents the sine value of the angle between the motor directions of the v-th and v+1-th segments. The sine value reflects the degree of change between the two directions.

[0079] in, and It can be obtained from the rotation direction of the first motor and the rotation direction of the second motor.

[0080] The preset fluctuation level is used to determine whether to merge intervals. The preset fluctuation level needs to be determined based on the specific application scenario and motor performance requirements. The preset fluctuation level can be 0.1, and is not a unique limitation.

[0081] Specifically, when the fluctuation level is less than the preset fluctuation level, it indicates that the voltage of the two segments may be in the same stage. Due to the direction of motor rotation, the motor speed may fluctuate. Therefore, it is considered that the two adjacent intervals are relatively stable in terms of speed change, and they can be merged into a larger interval, namely the third target speed range.

[0082] Specifically, the above process is repeated, traversing all second speed ranges to determine which ranges can be merged. The resulting multiple third speed ranges will include merged ranges (third target speed ranges) and unmerged ranges (fourth target speed ranges).

[0083] As can be seen, in this embodiment, the degree of fluctuation is used to determine whether to merge adjacent intervals. Merging adjacent speed range intervals can reduce the number of unnecessary intervals, simplify the data analysis process, and also reduce misjudgments caused by small fluctuations, thereby improving the accuracy and efficiency of fault detection.

[0084] S103. In one embodiment, the step of segmenting the cable voltage data according to the plurality of third rotation speed ranges to obtain a plurality of voltage ranges includes: obtaining a time period corresponding to each of the plurality of third rotation speed ranges to obtain a plurality of first time periods; segmenting the cable voltage data within the target time period according to the plurality of first time periods to obtain a plurality of voltage ranges, wherein each voltage range corresponds to the third rotation speed range within the same time period.

[0085] Specifically, for each third rotational speed range, its specific location within the original target time period is determined, thereby obtaining the corresponding time period, which is called the first time period.

[0086] The first time period is used to segment the cable voltage data within the target time period. Therefore, each voltage range will correspond to a specific third rotation speed range, and these voltage ranges are collected within the same time period.

[0087] The segmented processing ensures that the time stamps of the third speed range correspond one-to-one with the time stamps of the cable voltage data, thereby correctly matching the voltage data with the speed range.

[0088] Specifically, for each third rotational speed range, the start and end time points in the original time series are found, and the corresponding voltage values ​​are extracted from the cable voltage data based on these time points to form a voltage range.

[0089] Each voltage range should have a clear correspondence, meaning it is associated with only one specific third speed range. This correspondence will be used in subsequent analysis to understand the relationship between voltage changes and motor speed.

[0090] As can be seen, this embodiment can link the changes in motor speed with the changes in cable voltage by using the correspondence of time periods, providing detailed data support for analyzing the working status of the motor and the health status of the cable.

[0091] S104. In one embodiment, the step of performing fault analysis on the plurality of voltage ranges to obtain the cable detection result of the underwater robot includes: performing wavelet transform on the plurality of voltage ranges according to a preset wavelet function to obtain the spectrum curve corresponding to each voltage range; obtaining the standard spectrum corresponding to each voltage range according to the spectrum curve corresponding to each voltage range; performing anomaly processing on the standard spectrum corresponding to each voltage range and the spectrum curve corresponding to each voltage range to obtain the anomaly value of each voltage range; if the anomaly value is greater than a preset anomaly threshold, then the cable detection result of the underwater robot is obtained, and the cable detection result is the anomaly detection result.

[0092] Wavelet transform is a time-frequency analysis tool that decomposes a signal into components of different frequencies and displays how these components change over time. Through wavelet transform, the spectral curve corresponding to each voltage range can be obtained, reflecting the energy distribution of the voltage signal at different frequencies.

[0093] The standard spectrum can be seen as the spectral characteristics of a voltage signal under normal conditions, and is used for comparison and identification of anomalies.

[0094] Anomaly handling aims to detect deviations in voltage signals from the normal pattern, which may indicate faults or abnormal conditions in cables or electrical systems.

[0095] Outliers can be quantitative indicators of spectral differences, such as energy differences or frequency component differences.

[0096] The preset abnormal threshold can be manually set or pre-set; there is no single limitation. The preset abnormal threshold can be 0.8. If it exceeds this value, it indicates that the cable segment may have experienced an abnormal voltage.

[0097] The specific process of obtaining the standard spectrum corresponding to each voltage range based on the spectral curve corresponding to each voltage range can be referred to the specific description in S105-S106, and will not be repeated here.

[0098] The specific process of performing anomaly processing on the standard spectrum corresponding to each voltage range and the spectrum curve corresponding to each voltage range to obtain the abnormal value of each voltage range can be referred to the specific description in S107, and will not be repeated here.

[0099] As can be seen, this embodiment effectively monitors the health status of the underwater robot's cables through fault analysis, promptly identifies and prevents potential problems, and ensures the stable operation of the system.

[0100] S105. In one embodiment, obtaining the standard spectrum corresponding to each voltage interval based on the spectral curve corresponding to each voltage interval includes: segmenting each voltage interval into voltage segments to obtain at least one voltage segment in each voltage interval; obtaining the spectral region corresponding to at least one voltage segment in each voltage interval from the spectral curve corresponding to each voltage interval; performing intersection processing on the spectral regions corresponding to all voltage segments in each voltage interval to obtain a first spectral interval in each voltage interval, wherein the first spectral interval is the intersection of the spectral regions corresponding to all voltage segments; and performing data processing on the spectral region corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the standard spectrum corresponding to each voltage interval.

[0101] Voltage segmentation involves dividing a continuous voltage signal into multiple smaller intervals to analyze the characteristics within each interval more precisely, thereby capturing the details of voltage changes more accurately. These voltage segments can be of equal length or based on specific voltage characteristics.

[0102] The spectral region shows the frequency components and corresponding energy distribution of the voltage segments.

[0103] In each voltage interval, the spectral regions corresponding to all voltage segments within that voltage interval are intersected to obtain a first spectral interval for that voltage interval. The specific implementation of this first spectral interval being the intersection of the spectral regions corresponding to all voltage segments can be referenced using the following formula:

[0104]

[0105] in, This represents the number of voltage segments in the u-th rotational speed range. This represents the spectral region of the i-th voltage segment in the u-th rotational speed range. This represents the first frequency spectrum interval (the intersection of the frequency spectrum regions corresponding to all voltage segments).

[0106] The purpose of intersection processing is to find the common characteristics of all voltage segment spectral regions, that is, the frequency components that appear in all segments, to help identify the core spectral features of the voltage range.

[0107] The first spectral interval represents the common characteristics of all voltage segments within that voltage interval, that is, the common part of the spectral region of all voltage segments.

[0108] Optionally, data processing may include calculating the average spectrum, standardizing the spectrum, removing outliers, etc., to obtain a standard spectrum that represents the characteristics of the voltage range.

[0109] The specific process of processing the spectral region corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the standard spectrum corresponding to each voltage interval can be referred to the specific description in S106, and will not be repeated here.

[0110] As can be seen, this embodiment ensures that the standard spectrum reflects the most common and stable frequency characteristics within the voltage range through intersection processing, thereby analyzing the voltage signal more accurately and providing strong data support for cable fault detection and performance evaluation.

[0111] S106. In one embodiment, the step of processing the spectral region corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the standard spectrum corresponding to each voltage interval includes: performing similarity analysis on the spectral region corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the similarity between each voltage segment in each voltage interval and the first spectral interval in each voltage interval; if the similarity is greater than a preset similarity threshold, then at least one target voltage segment is obtained, the target voltage segment being a voltage segment greater than the preset similarity threshold; extracting the spectral peak value of the at least one target voltage segment; and performing mean processing on the spectral peak value to obtain the standard spectrum corresponding to each voltage interval.

[0112] Similarity analysis assesses the degree of similarity between two spectral regions.

[0113] In the specific implementation of performing similarity analysis on the spectral region corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the similarity between each voltage segment in each voltage interval and the first spectral interval in each voltage interval, the following formula can be used as a reference:

[0114]

[0115] in, This represents the spectral region of the i-th voltage segment in the u-th rotational speed range. This represents the peak value of the j-th peak in the spectrum of the i-th voltage segment within the u-th speed range. The spectral range representing the intersection In the spectrum, the peak value of the peak closest to the j-th peak of the i-th voltage segment in the u-th speed range. This represents the number of peaks in the spectrum of the i-th voltage segment within the u-th rotational speed range. The intersection represents the spectral portion that exists in both spectral intervals. Represents the spectrum With the first frequency range Frequency distance between them It measures the proportion or difference of the intersection region in the entire spectrum. Therefore, the larger the value, the greater the probability that the spectrum segment belongs to a standard spectral peak. The similarity between each voltage segment in each voltage range and the first spectral range in each voltage range.

[0116] in, The calculation methods include the following:

[0117] (1) Euclidean distance: Calculate the Euclidean distance between the intersection region and the entire spectrum region on the frequency axis; (2) Normalized distance: Normalize and compare the frequency range of the intersection region with the frequency range of the entire spectrum region; (3) Weighted distance: Consider the weight of each frequency component and calculate the weighted distance between the frequency components of the intersection region and the entire spectrum region; (4) Similarity quantification: By calculating the frequency distance, the similarity between two spectra can be quantified. The smaller the distance, the more similar the two spectra are; the larger the distance, the greater the difference between the two spectra.

[0118] Specifically, find center frequency and Center frequency, calculate the first absolute difference between these two center frequencies; find frequency range and Given the frequency range, calculate the difference between these two frequency ranges; for example, you can calculate the second absolute difference between their minimum and maximum frequencies. Therefore... = First absolute difference * a + (1-a) * Second absolute difference, where a is a weighting factor used to balance the importance of center frequency difference and frequency range difference.

[0119] The preset similarity threshold is a filtering standard that ensures only voltage segments that are highly consistent with the overall characteristics are selected. The preset similarity threshold can be 0.7, but it is not a fixed requirement.

[0120] If the similarity is greater than a preset similarity threshold, the voltage segment is marked as the target voltage segment. The target voltage segment represents the part with typical characteristics within the voltage range.

[0121] Among them, spectral peaks are the frequency components with the highest energy in the spectrum, which usually represent the main characteristics of the signal. In practice, signal processing tools (such as the find_peaks function in Python's SciPy library) are used to automatically detect local maxima in the spectrum and extract these local maxima as spectral peaks.

[0122] The averaging process involves calculating the average of the peak values ​​in the spectrum to generate a standard spectrum representing the voltage range. This standard spectrum can then serve as a benchmark for monitoring voltage signal changes and identifying anomalies. Specifically, statistical tools (such as Python's NumPy library) can be used to calculate the average of the peak values.

[0123] As can be seen, in this embodiment, similarity analysis is used to identify which voltage segments are most similar to the typical characteristics of the entire voltage range in terms of spectral features, thereby selecting reliable data for the construction of a standard spectrum. Furthermore, based on the extraction of spectral peaks, key frequency components in the signal are identified. By averaging the spectral peaks, the influence of individual outliers can be reduced, resulting in a more stable and reliable standard spectrum. Therefore, meaningful spectral features can be effectively extracted from voltage data, and a standard spectrum for subsequent analysis and fault detection can be constructed, which helps to improve the accuracy and efficiency of fault detection.

[0124] S107. In one embodiment, the step of performing anomaly processing on the standard spectrum corresponding to each voltage interval and the spectrum curve corresponding to each voltage interval to obtain the anomaly value of each voltage interval includes: extracting a first spectrum parameter from the standard spectrum corresponding to each voltage interval, extracting a second spectrum parameter from the spectrum curve corresponding to each voltage interval; and calculating the first spectrum parameter and the second spectrum parameter to obtain the anomaly value of each voltage interval.

[0125] The first spectral parameter is a specific spectral parameter extracted from the standard spectrum corresponding to each voltage range. These parameters can be frequency, amplitude, phase, energy, etc. The first spectral parameter represents the typical spectral characteristics of the voltage range and serves as a reference value under normal operating conditions.

[0126] The extraction process can utilize signal processing tools (such as FFT transform) to analyze the spectrum.

[0127] The second spectral parameter is extracted from the spectral curves corresponding to each voltage range, and the second spectral parameter reflects the spectral characteristics actually measured within the voltage range.

[0128] The calculation process for the outlier values ​​in each voltage range by calculating the first and second spectral parameters is shown in the following formula:

[0129]

[0130] in, This represents the length of the spectrum of the i-th voltage segment in the u-th rotational speed range. This represents the length of the standard spectrum for the u-th rotational speed range; The smaller this value, the more concentrated the current voltage spectrum distribution and the more concentrated the energy. This represents the number of peaks in the spectrum of the i-th voltage segment within the u-th rotational speed range. and These represent the minimum and maximum frequency values ​​corresponding to the peaks of the standard spectrum in the u-th rotational speed range; This represents the frequency value corresponding to the j-th peak in the spectrum of the i-th voltage segment within the u-th speed range. The larger this value, the more the current peak distribution is characterized by high frequencies. These are the outliers for each voltage range.

[0131] Outliers quantify the deviation between the actual spectrum curve and the standard spectrum. The magnitude of the outlier indicates whether there are any abnormalities within the voltage range. The larger the outlier, the greater the difference between the actual spectrum and the standard spectrum, potentially indicating a fault or anomaly.

[0132] As can be seen, this embodiment achieves quantitative analysis of the spectral characteristics of voltage signals by extracting spectral parameters and calculating outliers between the actual and standard values, and effectively identifies potential faults or abnormal situations.

[0133] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0134] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0135] As another aspect of this application, this application provides a cable fault diagnosis device based on a tethered underwater robot. The cable fault diagnosis device based on the tethered underwater robot can be a software module. This software module includes several instructions stored in a memory. A processor can access the memory, call the instructions, and execute them to complete the cable fault diagnosis method for the tethered underwater robot described in the various embodiments above.

[0136] See Figure 2, Figure 2 This is a schematic diagram of the structure of a cable fault diagnosis device for a tethered underwater robot provided in an embodiment of this application. Figure 2 As shown, the cable fault diagnosis device 200 based on a tethered underwater robot includes:

[0137] The acquisition unit 201 is used to acquire cable voltage data and motor rotation data of the underwater robot within a target time period. The motor rotation data includes the motor rotation rate. The target time period is the time period from when the underwater robot is launched into the water to when it comes ashore.

[0138] Processing unit 202 is used to segment the cable voltage data according to the motor rotation data to obtain multiple voltage ranges;

[0139] Analysis unit 203 is used to perform fault analysis on the multiple voltage ranges to obtain the cable detection results of the underwater robot;

[0140] The generation unit 204 is used to generate an alarm signal and fault diagnosis information if the cable detection result is an abnormal detection result.

[0141] The present invention has the following beneficial effects: By acquiring cable voltage data and motor rotation speed during the underwater robot's operation from underwater to ashore, the present invention can monitor the robot's operating status in real time, ensuring the integrity and accuracy of the data; by segmenting the voltage data according to the motor rotation speed, the relationship between voltage changes and motor speed can be accurately identified, thereby more accurately locating potential cable fault points; fault analysis of multiple voltage ranges helps to identify potential cable problems, detect anomalies in a timely manner, and avoid greater losses caused by faults; once an anomaly is detected, the system can quickly generate alarm signals and fault diagnosis information, notify relevant personnel for timely handling, reduce downtime and maintenance costs, ensure the continuity and safety of underwater robot operations, and avoid operation interruptions or equipment damage caused by cable faults.

[0142] In one embodiment, where the motor rotation data includes the motor rotation direction, and the processing unit 202 is further configured to: plot the motor rotation rate within the target time period to obtain a motor rotation rate curve; segment the motor rotation rate curve according to a first preset algorithm to obtain a motor speed subsequence corresponding to each motor rotation rate; analyze the motor rotation rate curve to obtain the maximum and minimum rotation rates; divide the motor rotation rate into intervals based on the maximum and minimum rotation rates to obtain multiple first speed rate intervals and speed difference values; match each motor speed subsequence with the multiple first speed rate intervals to obtain multiple second speed rate intervals containing the corresponding motor speed subsequences; process the multiple second speed rate intervals according to the motor rotation direction and the speed difference values ​​to obtain multiple third speed rate intervals; and segment the cable voltage data according to the multiple third speed rate intervals to obtain multiple voltage intervals.

[0143] In one embodiment, in the step of processing the plurality of second speed rate intervals according to the motor rotation direction and the speed difference value to obtain a plurality of third speed rate intervals, the processing unit 202 is further configured to: obtain a first target speed rate interval and the first motor rotation direction corresponding to the first target speed rate interval, a second target speed rate interval and the second motor rotation direction corresponding to the second target speed rate interval, wherein the first target speed rate interval and the second target speed rate interval are any two adjacent speed rate intervals among the plurality of second speed rate intervals; and process the first target speed rate interval and the first motor rotation direction corresponding to the first target speed rate interval, the second target speed rate interval, and the third target speed rate interval. The rotation direction of the second motor corresponding to the speed range and the second target speed range, and the speed difference value are calculated to obtain the fluctuation degree between the first target speed range and the second target speed range; if the fluctuation degree is less than the preset fluctuation degree, the first target speed range and the second target speed range are merged to obtain the merged third target speed range; multiple target speed ranges are traversed to obtain multiple third speed ranges, the multiple third speed ranges include multiple third target speed ranges and multiple fourth target speed ranges, the fourth target speed range is the target speed range when the fluctuation degree is greater than or equal to the preset fluctuation degree.

[0144] In one embodiment, in the process of segmenting the cable voltage data according to the plurality of third rotational speed ranges to obtain a plurality of voltage ranges, the processing unit 202 is further configured to obtain the time period corresponding to each of the plurality of third rotational speed ranges to obtain a plurality of first time periods; and to segment the cable voltage data within the target time period according to the plurality of first time periods to obtain a plurality of voltage ranges, wherein each voltage range corresponds to the third rotational speed range within the same time period.

[0145] In one embodiment, in the process of performing fault analysis on the plurality of voltage ranges to obtain the cable detection results of the underwater robot, the analysis unit 203 is further configured to: perform wavelet transform on the plurality of voltage ranges according to a preset wavelet function to obtain the spectrum curve corresponding to each voltage range; obtain the standard spectrum corresponding to each voltage range according to the spectrum curve corresponding to each voltage range; perform anomaly processing on the standard spectrum corresponding to each voltage range and the spectrum curve corresponding to each voltage range to obtain the anomaly value of each voltage range; if the anomaly value is greater than a preset anomaly threshold, then the cable detection result of the underwater robot is obtained, and the cable detection result is the anomaly detection result.

[0146] In one embodiment, in obtaining the standard spectrum corresponding to each voltage interval based on the spectral curve corresponding to each voltage interval, the analysis unit 203 is further configured to: segment each voltage interval to obtain at least one voltage segment in each voltage interval; obtain the spectral region corresponding to at least one voltage segment in each voltage interval from the spectral curve corresponding to each voltage interval; perform intersection processing on the spectral regions corresponding to all voltage segments in each voltage interval to obtain a first spectral interval in each voltage interval, wherein the first spectral interval is the intersection of the spectral regions corresponding to all voltage segments; and perform data processing on the spectral region corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the standard spectrum corresponding to each voltage interval.

[0147] In one embodiment, in the process of processing the spectral regions corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the standard spectrum corresponding to each voltage interval, the analysis unit 203 is further configured to: perform similarity analysis on the spectral regions corresponding to at least one voltage segment in each voltage interval and the first spectral interval in each voltage interval to obtain the similarity between each voltage segment in each voltage interval and the first spectral interval in each voltage interval; if the similarity is greater than a preset similarity threshold, then at least one target voltage segment is obtained, the target voltage segment being a voltage segment greater than the preset similarity threshold; extract the spectral peak value of the at least one target voltage segment; and perform mean processing on the spectral peak value to obtain the standard spectrum corresponding to each voltage interval.

[0148] In one embodiment, in the process of performing anomaly processing on the standard spectrum corresponding to each voltage range and the spectrum curve corresponding to each voltage range to obtain the anomaly value of each voltage range, the analysis unit 203 is further configured to: extract a first spectral parameter from the standard spectrum corresponding to each voltage range, extract a second spectral parameter from the spectrum curve corresponding to each voltage range; and calculate the first spectral parameter and the second spectral parameter to obtain the anomaly value of each voltage range.

[0149] It should be noted that the above-described cable fault diagnosis device based on a tethered underwater robot can execute the cable fault diagnosis method for a tethered underwater robot provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the embodiments of the cable fault diagnosis device based on a tethered underwater robot can be found in the cable fault diagnosis method for a tethered underwater robot provided in the embodiments of this application.

[0150] See Figure 3 , Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 3 As shown, the computer device 300 includes a processor 301 and a memory 302. The processor 301 is communicatively connected to the memory 302.

[0151] Processor 301 is configured to support the computer device in performing the corresponding functions in the cable fault diagnosis method for the tethered underwater robot in the above method embodiments. The processor 301 may be a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof. The aforementioned hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0152] Specifically, the processor 301 may include a transmitting card, a receiving card, and a driver chip.

[0153] Memory 302 is used to store program code, etc. Memory 302 may include volatile memory (VM), such as random access memory (RAM); memory 302 may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); memory 302 may also include combinations of the above types of memory.

[0154] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the cable fault diagnosis method for a tethered underwater robot as described in the foregoing embodiments.

[0155] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

Claims

1. A cable fault diagnosis method for a tethered underwater robot, characterized by, The method is applied to a cable fault diagnosis system of a tethered underwater robot, and the method comprises the following steps: obtaining cable voltage data and motor rotation data of the underwater robot in a target time period, the motor rotation data comprising a motor rotation rate, and the target time period being a time period from launching to landing of the underwater robot; segmenting the cable voltage data according to the motor rotation data to obtain a plurality of voltage intervals; performing fault analysis on the plurality of voltage intervals to obtain a cable detection result of the underwater robot; generating an alarm signal and fault diagnosis information if the cable detection result is an abnormal detection result; the motor rotation data comprises a motor rotation direction, and the step of segmenting the cable voltage data according to the motor rotation data to obtain a plurality of voltage intervals comprises the following steps: plotting the motor rotation rate in the target time period to obtain a motor rotation rate curve; segmenting the motor rotation rate curve according to a first preset algorithm to obtain a motor rotation rate sub-sequence corresponding to each motor rotation rate; analyzing the motor rotation rate curve to obtain a maximum rotation rate and a minimum rotation rate; dividing the motor rotation rate into intervals according to the maximum rotation rate and the minimum rotation rate to obtain a plurality of first rotation rate intervals and a rotation rate difference value; matching each motor rotation rate sub-sequence with the plurality of first rotation rate intervals to obtain a plurality of second rotation rate intervals containing the corresponding motor rotation rate sub-sequence; performing data processing on the plurality of second rotation rate intervals according to the motor rotation direction and the rotation rate difference value to obtain a plurality of third rotation rate intervals; segmenting the cable voltage data according to the plurality of third rotation rate intervals to obtain a plurality of voltage intervals; the step of performing data processing on the plurality of second rotation rate intervals according to the motor rotation direction and the rotation rate difference value to obtain a plurality of third rotation rate intervals comprises the following steps: obtaining a first target rotation rate interval, a first motor rotation direction corresponding to the first target rotation rate interval, a second target rotation rate interval, and a second motor rotation direction corresponding to the second target rotation rate interval, the first target rotation rate interval and the second target rotation rate interval being any two adjacent rotation rate intervals in the plurality of second rotation rate intervals; calculating the first target rotation rate interval, the first motor rotation direction corresponding to the first target rotation rate interval, the second target rotation rate interval, the second motor rotation direction corresponding to the second target rotation rate interval, and the rotation rate difference value to obtain a fluctuation degree between the first target rotation rate interval and the second target rotation rate interval; if the fluctuation degree is less than a preset fluctuation degree, merging the first target rotation rate interval and the second target rotation rate interval to obtain a merged third target rotation rate interval; The plurality of target rotating speed rate intervals are traversed to obtain a plurality of third rotating speed rate intervals, the plurality of third rotating speed rate intervals including a plurality of the third target rotating speed rate intervals and a plurality of fourth target rotating speed rate intervals, the fourth target rotating speed rate interval being a target rotating speed rate interval when the fluctuation degree is greater than or equal to a preset fluctuation degree; The fault analysis on the plurality of voltage intervals is performed to obtain a cable detection result of the underwater robot, including: According to a preset wavelet function, wavelet transform is performed on the plurality of voltage intervals to obtain a frequency spectrum curve corresponding to each voltage interval; According to the frequency spectrum curve corresponding to each voltage interval, a standard frequency spectrum corresponding to each voltage interval is obtained; The standard frequency spectrum corresponding to each voltage interval is abnormally processed with the frequency spectrum curve corresponding to each voltage interval to obtain an abnormal value of each voltage interval; If the abnormal value is greater than a preset abnormal threshold, a cable detection result of the underwater robot is obtained, and the cable detection result is the abnormal detection result; The abnormal value of each voltage interval is obtained by abnormally processing the standard frequency spectrum corresponding to each voltage interval with the frequency spectrum curve corresponding to each voltage interval, including: A first frequency spectrum parameter in the standard frequency spectrum corresponding to each voltage interval is extracted, and a second frequency spectrum parameter in the frequency spectrum curve corresponding to each voltage interval is extracted; The first frequency spectrum parameter and the second frequency spectrum parameter are calculated to obtain the abnormal value of each voltage interval.

2. The cable fault diagnosis method for the tethered underwater robot according to claim 1, characterized by, The plurality of third rotating speed rate intervals are traversed to obtain a plurality of third rotating speed rate intervals, the plurality of third rotating speed rate intervals including a plurality of the third target rotating speed rate intervals and a plurality of fourth target rotating speed rate intervals, the fourth target rotating speed rate interval being a target rotating speed rate interval when the fluctuation degree is greater than or equal to a preset fluctuation degree; According to the plurality of third rotating speed rate intervals, the cable voltage data is segmented to obtain a plurality of voltage intervals, including: A time period corresponding to each third rotating speed rate interval in the plurality of third rotating speed rate intervals is obtained to obtain a plurality of first time periods; 3. The cable fault diagnosis method for the tethered underwater robot according to claim 1, characterized by, According to the plurality of first time periods, the cable voltage data in the target time period is segmented to obtain a plurality of voltage intervals, wherein each voltage interval corresponds to the third rotating speed rate interval in the same time period. According to the frequency spectrum curve corresponding to each voltage interval, a standard frequency spectrum corresponding to each voltage interval is obtained, including: Each voltage interval is voltage segmented to obtain at least one voltage segment in each voltage interval; In the frequency spectrum curve corresponding to each voltage interval, a frequency spectrum region corresponding to at least one voltage segment in each voltage interval is obtained; In each voltage interval, the frequency spectrum regions corresponding to all voltage segments in each voltage interval are processed by intersection to obtain a first frequency spectrum interval in each voltage interval, the first frequency spectrum interval being an intersection of the frequency spectrum regions corresponding to all voltage segments; 4. The cable fault diagnosis method of the tethered underwater robot according to claim 3, characterized by, The frequency spectrum regions corresponding to at least one voltage segment in each voltage interval and the first frequency spectrum interval in each voltage interval are processed by data to obtain the standard frequency spectrum corresponding to each voltage interval. The frequency spectrum regions corresponding to at least one voltage segment in each voltage interval and the first frequency spectrum interval in each voltage interval are processed by data to obtain the standard frequency spectrum corresponding to each voltage interval, including: performing similarity analysis on a first frequency spectrum interval in each voltage interval corresponding to a frequency spectrum region of at least one voltage segment in the voltage interval, to obtain similarity between each voltage segment in the voltage interval and the first frequency spectrum interval in the voltage interval; if the similarity is greater than a preset similarity threshold, obtaining at least one target voltage segment, the target voltage segment being a voltage segment greater than the preset similarity threshold; extracting a frequency spectrum peak of the at least one target voltage segment; performing mean value processing on the frequency spectrum peak to obtain a standard frequency spectrum corresponding to each voltage interval.

5. A cable fault diagnosis system for a tethered underwater robot, characterized by, The cable fault diagnosis system of the tethered underwater robot comprises a memory and a processor, the memory is connected to the processor, the processor is used to execute one or more computer programs stored in the memory, and the processor, when executing the one or more computer programs, enables the cable fault diagnosis system of the tethered underwater robot to implement the cable fault diagnosis method of the tethered underwater robot according to any one of claims 1-4.

6. A cable fault diagnosis device for a tethered underwater robot, characterized by comprising: The device is applied to the cable fault diagnosis system of the tethered underwater robot in claim 5, and the device comprises: an acquisition unit configured to acquire cable voltage data and motor rotation data of the underwater robot in a target time period, the motor rotation data comprising a motor rotation rate, and the target time period being a time period during which the underwater robot is in water and on land; a processing unit configured to perform segmentation processing on the cable voltage data according to the motor rotation data, to obtain a plurality of voltage intervals; an analysis unit configured to perform fault analysis on the plurality of voltage intervals, to obtain a cable detection result of the underwater robot; a generation unit configured to generate an alarm signal and fault diagnosis information if the cable detection result is an abnormal detection result.

Images