Abnormal fault analysis method for echo signal of echo sounder of transshipment barge

Abstract

The invention relates to a transshipment barge echo sounder echo signal abnormity fault analysis method, and relates to the field of underwater sounding technology, and the method comprises the following steps: S1, building an echo signal abnormity database, extracting various fault waveform features through equipment, and building a database; step S2, fault analysis: obtaining barge state monitoring data and working information of an echo sounder, performing detection fault analysis based on the navigation information of the barge and the working information of the echo sounder, and determining an anomaly type; and S3, detection adjustment: carrying out frequency modulation processing on the echo sounder according to the fault type. The reliability of the echo sounder can be improved, and normal operation of the echo sounder is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of underwater depth sounding technology, and in particular to a method for analyzing abnormal faults of echo signals of an echo sounder on a transfer barge. Background Art

[0002] The transshipment barge can be used as a new type of mobile offshore terminal, which has the advantage of not occupying land and shoreline resources. It can realize the cargo transfer between large cargo ships and transport barges without changing the original berth capacity and transformation cost of the terminal.

[0003] In the prior art, in order to ensure the normal operation of the transfer barge, an echo sounder is often installed on the bottom of the transfer barge. The echo sounder is used to measure the water depth in real time to ensure that the barge avoids running aground and hitting the bottom during navigation.

[0004] However, in actual applications, the echo sounder may be interfered by many factors. If the swing angle of the barge is too large, it is easy for the detection signal to be reflected and not be received by the receiving transducer of the echo sounder. If the barge is sailing too fast with a small load, the bow of the barge is tilted too much, the hull swings left and right with a large amplitude, or the hull swings left and right with a fast frequency, it is easy to cause an increase in the amount of bubbles in the water. The increase in the amount of bubbles can easily absorb the detection pulse signal emitted by the transmitting transducer of the echo sounder, making it difficult for the receiving transducer of the echo sounder to receive the echo signal, resulting in the failure of the echo sounder test. It is difficult to meet the depth measurement needs during the navigation of the barge, and the reliability is low. Summary of the invention

[0005] In order to improve the reliability of the echo sounder, the present application provides a method for analyzing abnormal faults of echo signals of an echo sounder of a transfer barge.

[0006] The present application provides a method for analyzing abnormal faults of echo signals of echo sounders on transshipment barges, which adopts the following technical solutions: A method for analyzing abnormal faults of echo signals of an echo sounder of a transfer barge, characterized in that it comprises the following steps: Step S1, establishing an abnormal echo signal database, extracting various fault waveform features through equipment, and establishing a database; Step S2, fault analysis, obtaining the barge status monitoring data and the echo sounder working information, performing fault detection analysis based on the barge navigation information and the echo sounder working information, and determining the abnormality type; Step S3: detection adjustment: frequency modulation of the echo sounder according to the fault type.

[0007] By adopting the above technical solution, during the operation of the echo sounder, when the echo sounder cannot receive the echo signal, the data can be matched from the database based on the status monitoring data of the barge and the working information of the echo sounder, and the abnormal state of the echo sounder can be analyzed for faults. The echo sounder can be frequency-modulated according to the data based on the analysis results, so that the frequency of the detection signal emitted by the transmitting transducer of the echo sounder changes to facilitate the re-reception of the echo signal. When the echo signal is abnormal, the frequency modulation response can be carried out in time, thereby improving the reliability of the echo sounder.

[0008] Preferably, step S1 comprises the following steps: Step S11, collecting the detection signal sent by the transmitting transducer of the echo sounder and the echo signal received by the receiving transducer of the echo sounder; Step S12, performing time domain analysis on the echo signal, and marking the data for which no echo signal is received as abnormal echo data; Step S13, obtaining status monitoring data of the barge during navigation, wherein the status monitoring data includes barge load, barge speed, bow upturn angle, hull swing angle, and hull swing frequency; based on the status monitoring data, signal strength of echo signal, emission frequency of detection signal, and signal strength of detection signal, the abnormal data is calibrated as swing lost echo abnormality, bubble absorption echo abnormality, fish scattering echo abnormality, and receiving transducer failure abnormality.

[0009] By adopting the above technical scheme, the echo signal loss anomaly can be classified into sway loss echo anomaly and bubble absorption echo anomaly according to the characteristics of the echo loss through the barge load, barge speed, bow upturned angle, hull sway angle, hull sway frequency, detection signal strength, detection signal frequency and echo signal strength. This makes it easier to match the cause of the barge's echo signal loss through the barge load, barge speed, bow upturned angle, hull sway angle, hull sway frequency, detection signal strength, detection signal frequency and echo signal strength when the subsequent echo signal is abnormal.

[0010] Preferably, the step S13 comprises the following steps: Step S131, determining the abnormal time point of the abnormal data of the echo signal, and determining the detection signal data and the status monitoring data at the abnormal time point; Step S132, obtaining the beam angle and the hull swing angle of the detection signal at the abnormal time point, and calculating whether the hull swing angle is too large to exceed the receiving range of the echo signal. If so, the abnormal data is marked as a swing lost echo abnormality; if not, bubble prediction calculation is performed; Step S133, based on the state monitoring data, calculate whether the bubble prediction amount at the time point when the abnormal data occurs exceeds the bubble amount threshold through the bubble prediction amount formula, if so, mark the abnormal data as bubble absorption echo abnormality; if not, perform fish scattering abnormality judgment; Step S134, obtaining echo signal data before the echo signal is lost, performing target detection through image cropping and YOLO algorithm, obtaining information about fish schools in the area, and if there are fish schools, determining that the fish school scattered echo is abnormal; if there are no fish schools, determining that the receiving transducer is faulty.

[0011] By adopting the above technical scheme, since the beam angle of the detection pulse is related to the detection range of the echo sounder, when the swing angle of the barge is greater than half of the transmitting angle, the receiving transducer of the echo sounder cannot receive the echo signal. Therefore, when the echo signal cannot be received, by comparing the transmitting angle of the frequency with the swing angle of the barge, it can be determined whether the echo signal is lost due to the excessive swing angle of the barge; since the amount of bubbles in the water body is affected by the barge load, barge speed, bow end upturned angle, hull swing angle, and hull swing frequency, when the receiving transducer cannot receive the echo signal and the hull swing angle does not exceed the maximum swing angle, the predicted bubble amount can be calculated based on the barge load, barge speed, bow end upturned angle, hull swing angle, and hull swing frequency, and compared with the bubble amount threshold in the database to determine whether the echo sounder loses the echo signal due to bubble absorption. By extracting the image data of the first few frames before the echo signal is lost, cropping the image, and performing target detection based on the YOLO algorithm, the information of the fish school in the area can be obtained to determine whether there is a school of fish in the detection area. If there is a school of fish, it can be determined that the loss of the echo signal is caused by the scattering and absorption of the school of fish, and the fault type can be determined as abnormal scattering echo of the school of fish. If there is both scattering by the school of fish and non-bubble absorption, the fault type of the echo sounder can be determined as abnormal fault of the receiving transducer.

[0012] Preferably, the step S133 includes the following steps: Step S1331, obtaining historical bubble prediction data, detection signal strength, and echo signal strength at the same detection signal frequency; Step S1332, based on the historical bubble prediction quantity data and the echo signal strength data, the bubble prediction quantity data corresponding to the signal strength of the echo signal attenuating to 0 dB is calculated through a linear regression model, and the bubble prediction quantity data is calibrated as the bubble quantity threshold data of the detection signal of the frequency, and stored in the database.

[0013] By adopting the above technical solution, through the waveform data of the historical echo signal, since the signal strength attenuation values ​​corresponding to different bubble amounts under the same detection signal frequency are different, generally speaking, the more bubbles there are, the greater the signal strength attenuation value. By collecting historical data and based on the linear regression model, the bubble prediction value corresponding to when the signal strength of the echo signal attenuates to 0dB can be calculated based on the signal strength of the echo signal, and it can be used as the bubble amount threshold for the echo signal loss.

[0014] Preferably, step S2 comprises the following steps: Step S21, obtaining status monitoring data, detection signal data, and echo signal data during the navigation of the barge; Step S22, matching the maximum hull swing angle and bubble volume threshold data from the database based on the transmission frequency of the detection signal; Step S23: performing abnormality type analysis based on the current barge hull sway angle data and bubble prediction data.

[0015] By adopting the above technical scheme, when the echo signal is lost and the echo sounder cannot receive the echo signal during the navigation of the barge, the corresponding maximum swing angle data and bubble volume threshold data can be matched based on the frequency of the detection signal emitted by the echo sounder, and by performing abnormal type analysis on the maximum swing angle data and the bubble volume threshold data, it is convenient to match the corresponding emergency control according to the echo abnormality type to ensure the normal use of the echo sounder.

[0016] Preferably, step S23 comprises the following steps: Step S231, judging whether the current swing amplitude of the barge exceeds the maximum swing angle of the current transmission frequency of the detection signal, if so, judging that the fault type of the echo sounder is swing loss echo abnormality; if not, performing bubble prediction measurement comparison; Step S232, judging whether the bubble prediction amount of the current barge exceeds the bubble amount threshold value, if so, judging that the fault type of the echo sounder is the bubble absorption echo abnormality; if not, calculating the bubble prediction amount; Step S233, obtaining echo signal data before the echo signal is lost, performing target detection through image cropping and YOLO algorithm, and determining whether there is a school of fish in the acquisition area. If there is a school of fish in the area, the fault type of the echo sounder is determined to be abnormal fish scattered echo; if not, it is determined to be an abnormal receiving transducer fault.

[0017] By adopting the above technical scheme, when the echo signal is lost during the navigation of the barge, the hull sway angle can be compared in advance to determine whether the echo signal is lost because the hull sway angle of the barge is too large; if the echo signal is lost not because the hull sway angle of the barge is too large, the bubble prediction amount is calculated based on the barge's load data, speed data, bow end upturned angle, hull left and right sway angle, and hull sway frequency to determine whether the bubble amount is too large, resulting in bubble absorption and abnormal echo; if the bubble prediction amount does not exceed the bubble amount threshold and the hull sway angle is not too large, a few frames of image data before the echo signal is lost can be extracted, and target detection can be performed through image cropping and YOLO algorithm to determine whether there are fish schools in the detection area. If there are fish schools in the area, it can be determined that the fish scattering echo is abnormal; if no abnormalities occur, it can be determined that the receiving transducer of the echo sounder is faulty.

[0018] Preferably, step S3 comprises the following steps: Step S31, installing a frequency-adjustable multi-beam echo sounder on the bottom of the transfer barge; Step S32, determine the abnormal type of the echo signal. If the abnormal type of the echo signal is a swing lost echo abnormality or a bubble absorption echo abnormality, lower the frequency of the echo sounder transmitting the detection signal until the echo signal is received again; if the receiving transducer of the echo sounder fails, issue a fault alarm signal.

[0019] By adopting the above technical solution, since the lower the frequency of ultrasonic waves, the larger the beam angle, the stronger the ability to penetrate bubbles, when the hull swaying angle of the barge is too large or the amount of bubbles in the water is too much, the transmission frequency of the detection signal emitted by the echo sounder can be lowered to ensure the normal operation of the echo sounder; if the hull swaying angle of the barge does not exceed the maximum swaying angle and the predicted amount of bubbles does not exceed the bubble amount threshold, it can be determined that the receiving transducer of the echo sounder is faulty, and an alarm signal is issued to prompt the relevant personnel in the control room of the cabin to switch the remaining echo sounders.

[0020] In summary, the present invention provides a method for analyzing abnormal faults of echo signals of an echo sounder of a transfer barge, which includes at least one of the following beneficial technical effects: 1. During the operation of the echo sounder, when the echo sounder cannot receive the echo signal, the abnormal state of the echo sounder can be analyzed by matching data from the database based on the status monitoring data of the barge and the working information of the echo sounder. The echo sounder is frequency modulated according to the analysis results, so that the frequency of the detection signal emitted by the transmitting transducer of the echo sounder changes to facilitate the re-reception of the echo signal. When the echo signal is abnormal, the frequency modulation response can be carried out in time to improve the reliability of the echo sounder; 2. Since the beam angle of the detection pulse is related to the detection range of the echo sounder, when the swing angle of the barge is greater than half of the transmission angle, the receiving transducer of the echo sounder cannot receive the echo signal. Therefore, when the echo signal cannot be received, by comparing the transmission angle of the frequency with the swing angle of the barge, it can be determined whether the echo signal is lost due to the excessive swing angle of the barge; by extracting the image data of the first few frames before the echo signal is lost, the image is cropped, and target detection is performed based on the YOLO algorithm to obtain the information of the fish school in the area. It can be determined whether there is a school of fish in the detection area. If there is a school of fish, it can be determined that the loss of the echo signal is caused by the scattering and absorption of the fish school, and the The fault type is determined to be abnormal fish scattering echo; if there is both fish scattering and non-bubble absorption, the fault type of the echo sounder can be determined as abnormal receiving transducer failure; since the amount of bubbles in the water body is affected by factors such as barge load, barge speed, bow upturned angle, hull sway angle, and hull sway frequency, when the receiving transducer cannot receive the echo signal and the hull sway angle does not exceed the maximum sway angle, the predicted bubble amount can be calculated based on the barge load, barge speed, bow upturned angle, hull sway angle, and hull sway frequency, and compared with the bubble amount threshold in the database to determine whether the echo sounder lost the echo signal due to bubble absorption. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of Example 1 of the present application for demonstrating the main process of the echo signal abnormal fault analysis method.

[0022] Figure 2 It is a schematic diagram of Example 1 of the present application for illustrating the overall process of step S13.

[0023] Figure 3 It is a schematic diagram used to illustrate the overall process of step S2 in Example 1 of the present application.

[0024] Figure 4 This is a schematic diagram of Example 2 of the present application for showing the installation positions of the first echo sounder and the second echo sounder.

[0025] Figure 5 It is a schematic diagram of Example 2 of the present application for demonstrating the overall structure of the air deflector.

[0026] Explanation of the accompanying reference numerals: 1. bottom plate; 2. side plate; 3. steel pipe; 4. first echo sounder; 5. second echo sounder. DETAILED DESCRIPTION

[0027] The following is combined with Figure 1-Figure 5 This application is described in further detail.

[0028] Example 1 The present application embodiment discloses a method for analyzing abnormal faults of echo signals of an echo sounder of a transfer barge. Figure 1-Figure 3 , which mainly includes the following steps: Step S1, establishing an abnormal echo signal database, extracting various fault waveform features through equipment, and establishing a database; Step S2, fault analysis, obtaining the barge status monitoring data and the echo sounder working information, performing fault detection analysis based on the barge navigation information and the echo sounder working information, and determining the abnormality type; Step S3: detection adjustment: frequency modulation of the echo sounder according to the fault type.

[0029] During the navigation of the barge and the operation of the echo sounder, when the echo sounder cannot receive the echo signal, the waveform of the detection signal corresponding to the echo signal that cannot be received can be recorded, and the frequency, emission intensity and other data of the detection signal can be obtained. Combined with the historical status monitoring data of the barge, the abnormal data of the barge's received echo signal can be classified, and different abnormal data at different frequencies can be analyzed, classified and stored in the database.

[0030] When the barge is sailing and the abnormal situation of echo signal loss occurs again, the abnormal situation of echo sounder can be identified by combining the information of detection signal emitted by echo sounder and the status monitoring data of barge, and corresponding emergency measures can be taken. The technical effect of automatically identifying the abnormal type and automatically adjusting the frequency of the emitted detection signal can be achieved, which can effectively improve the reliability of echo sounder.

[0031] Wherein, step S1 includes the following steps: step S11, collecting the detection signal sent by the transmitting transducer of the echo sounder and the echo signal received by the receiving transducer of the echo sounder; Step S12, performing time domain analysis on the echo signal, and marking the data for which no echo signal is received as abnormal echo data; Step S13, obtaining status monitoring data of the barge during navigation, wherein the status monitoring data includes barge load, barge speed, bow upturn angle, hull swing angle, and hull swing frequency; based on the status monitoring data, signal strength of echo signal, emission frequency of detection signal, and signal strength of detection signal, the abnormal data is calibrated as swing lost echo abnormality, bubble absorption echo abnormality, fish scattering echo abnormality, and receiving transducer failure abnormality.

[0032] By analyzing the barge load, barge speed, bow upturned angle, hull swing angle, hull swing frequency, detection signal strength, detection signal frequency and echo signal strength, the echo signal loss anomaly can be classified into swing loss echo anomaly and bubble absorption echo anomaly according to the characteristics of the echo loss. This makes it easier to match the cause of the barge's echo signal loss through the barge load, barge speed, bow upturned angle, hull swing angle, hull swing frequency, detection signal strength, detection signal frequency and echo signal strength when the echo signal is abnormal in the future.

[0033] Specifically, step S13 includes the following steps: Step S131, determining the abnormal time point of the abnormal data of the echo signal, and determining the detection signal data and the status monitoring data at the abnormal time point; Step S132, obtaining the beam angle and the hull swing angle of the detection signal at the abnormal time point, and calculating whether the hull swing angle is too large to exceed the receiving range of the echo signal. If so, the abnormal data is marked as a swing lost echo abnormality; if not, bubble prediction calculation is performed; Step S133, based on the state monitoring data, calculate whether the bubble prediction amount at the time point when the abnormal data occurs exceeds the bubble amount threshold through the bubble prediction amount formula, if so, mark the abnormal data as bubble absorption echo abnormality; if not, perform fish scattering abnormality judgment; Step S134, obtaining echo signal data before the echo signal is lost, performing target detection through image cropping and YOLO algorithm, obtaining information about fish schools in the area, and if there are fish schools, determining that the fish school scattered echo is abnormal; if there are no fish schools, determining that the receiving transducer is faulty.

[0034] The calculation formula of bubble prediction is: R= ; Where R is the bubble prediction; m is the barge load, in tons; M is the weight of the barge when fully loaded, in tons; V represents the barge's navigation speed, in meters per second; Indicates the bow tilt angle of the barge, in degrees; Indicates the barge's hull swing angle, in degrees; It indicates the frequency of the barge's left-right swing, in Hz.

[0035] Wherein, step S133 includes the following steps: Step S1331, obtaining historical bubble prediction data, detection signal strength, and echo signal strength at the same detection signal frequency; Step S1332, based on the historical bubble prediction quantity data and the echo signal strength data, the bubble prediction quantity data corresponding to the signal strength of the echo signal attenuating to 0 dB is calculated through a linear regression model, and the bubble prediction quantity data is calibrated as the bubble quantity threshold data of the detection signal of the frequency, and stored in the database.

[0036] For example, the frequency of the detection signal emitted by the transmitting transducer of the echo sounder is 125kHz, and the beam angle of the ultrasonic wave emitted by the transmitting transducer of the echo sounder is 64.2 degrees. Greater than half of the beam angle, that is When the angle is greater than 64.2÷2=32.1 degrees, the echo sounder cannot receive the echo signal. It can be determined that the echo sounder lost the echo due to the excessive swing angle of the barge.

[0037] If the barge's hull swing angle is less than 32.1 degrees and the echo signal cannot be received, the current bubble prediction value of the barge can be calculated by the bubble prediction value calculation formula. For example, the barge's load m = 12630 tons, the barge's full load load M = 20000 tons, the barge's current sailing speed V = 16.6 meters per second; the barge's bow end tilt angle =12.4 degrees; the barge's left-right swing angle =16.2 degrees; the frequency of the barge's hull swaying from side to side is 3Hz, so the bubble prediction value of the barge is R=145.3.

[0038] Table 1 shows the signal strength data of the received echo signal corresponding to different bubble prediction quantities when the echo sounder maintains the detection signal frequency at 125 kHz.

[0039] Table 1: Among them, the linear regression model shows that when the bubble prediction amount R=172.6, the intensity of the echo signal is 0, then the bubble prediction amount R=172.6 can be calibrated as the bubble amount threshold when the frequency of the detection signal is 125kHz. If the transmission frequency of the detection signal is 125kHz and the bubble prediction amount R≥172.6, the echo sounder cannot receive the echo signal and the echo signal is lost.

[0040] Then, when the echo signal disappears, the barge's hull swing angle is monitored. ≥32.1 degrees, it can be determined that the echo sounder has lost the echo signal due to the large swaying angle of the barge; if the swaying angle of the barge is <32.1 degrees, and the echo signal cannot be received, the bubble prediction value is compared. If the bubble prediction value R ≥ 172.6, it is determined that the detection signal emitted by the echo sounder is completely absorbed by the bubbles in the water, resulting in the loss of the echo signal; if the barge hull swing angle <32.1 degrees, and the bubble prediction amount R<172.6, it can be determined that the echo signal of the echo sounder is lost, excluding the situation where the hull swing angle is too large and there are too many bubbles in the water. At this time, fish detection is performed to determine whether the echo signal is lost due to fish scattering.

[0041] When judging the abnormality of the scattered echo of the school of fish, the echo image data of the first few frames before the echo signal is lost can be extracted, and the echo image data can be scaled to a 448×448 image. The scaled image data is sent to the convolutional neural network for prediction; the confidence threshold is processed through the prediction result to obtain the final result. The YOLO algorithm sends the scaled image to the convolutional neural network to separate the scaled image into S×S grids. Each grid predicts B bboxes containing x, y, w, h, and confidence parameters, where x and y are the offsets of the center point of the bbox, w and h are the width and depth of the center point of the bbox, and confidence is the confidence. The image cropping calculation process is w'=x2-x1, h'=y2-y1, where (x1, y1) is the coordinate of the upper left corner of the divided area, (x2, y2) is the coordinate of the lower right corner, w' and h' are the length and width after cropping, and w' and y' are normalized; Confidence; Where C is the confidence, P is the probability of the bbox in the object, Strue is the true area size, Spre is the predicted area size, and Smer is the size of the combined area of ​​the two areas. The prediction result value can be judged by the confidence size of different categories; The fish school information detected by the YOLO detection algorithm is identified, and the center point change information is collected according to the continuous change of the center point of the fish school information in the same coordinate system, and the convolutional neural network is used to obtain the motion trajectory equation of the fish school: Q=j(x, y, w, h)+p; Among them, (x, y, w, h) are the coordinates of the center point of the fish school, j is the weight, and p is the bias value; by preprocessing the echo signal and detecting the preprocessed data, the fish school can be identified from the cluttered signal, and the fish school can be automatically identified according to its movement and the size, depth, bubbles, etc. of the fish school can be intelligently identified. At the same time, the size, depth, moving direction and speed of the fish school can be tracked and judged. Based on the size, depth, moving direction and moving speed of the fish school, combined with the navigation direction and navigation speed of the barge, it can be determined whether the echo signal loss is caused by fish school scattering.

[0042] If no fish is detected in the detection area, the bubble prediction value is less than the bubble volume threshold, and the hull swing angle of the barge is less than half of the beam angle of the detection signal, it can be determined that the fault type of the echo sounder is a malfunction of the receiving transducer.

[0043] Wherein, step S2 comprises the following steps: Step S21, obtaining status monitoring data, detection signal data, and echo signal data during the navigation of the barge; Step S22, matching the maximum hull swing angle and bubble volume threshold data from the database based on the transmission frequency of the detection signal; Step S23: performing abnormality type analysis based on the current barge hull sway angle data and bubble prediction data.

[0044] Wherein, step S23 comprises the following steps: Step S231, judging whether the current swing amplitude of the barge exceeds the maximum swing angle of the current transmission frequency of the detection signal, if so, judging that the fault type of the echo sounder is swing loss echo abnormality; if not, performing bubble prediction measurement comparison; Step S232, judging whether the bubble prediction amount of the current barge exceeds the bubble amount threshold value, if so, judging that the fault type of the echo sounder is the bubble absorption echo abnormality; if not, calculating the bubble prediction amount; Step S233, obtaining echo signal data before the echo signal is lost, performing target detection through image cropping and YOLO algorithm, and determining whether there is a school of fish in the acquisition area. If there is a school of fish in the area, the fault type of the echo sounder is determined to be abnormal fish scattered echo; if not, it is determined to be an abnormal receiving transducer fault.

[0045] When the barge is sailing along the route, if the echo signal of the echo sounder is lost, the beam angle of the detection signal and the bubble amount threshold of the detection signal can be retrieved from the database based on the frequency of the detection signal emitted by the echo sounder. The reason why the echo sounder lost the echo signal can be determined by the barge's current bubble prediction data, the barge's beam angle data, and whether there are fish schools in the detection area.

[0046] Wherein, step S3 comprises the following steps: Step S31, installing a frequency-adjustable multi-beam echo sounder on the bottom of the transfer barge; Step S32, determine the abnormal type of the echo signal. If the abnormal type of the echo signal is a swing lost echo abnormality, a bubble absorption echo abnormality, or a fish scattering echo abnormality, lower the frequency of the echo sounder transmitting the detection signal until the echo signal is received again; if the receiving transducer of the echo sounder fails, issue a fault alarm signal.

[0047] After obtaining the type of abnormal echo signal of the barge's echo sounder, if the abnormal echo signal type is a swing lost echo abnormality, a bubble absorption echo abnormality or a fish scattering echo abnormality, the beam angle range or penetration of the detection signal can be improved by adjusting the frequency of the detection signal transmitted by the echo sounder. The detection signal frequency of the echo sounder can be adjusted in time under harsh external environment conditions so that the echo sounder can resume normal measurement. If the echo sounder fails for its own receiving transducer, a fault alarm signal is issued, which can be displayed on the display in the control cabin to prompt the relevant operator to switch to an echo sounder with normal function.

[0048] The implementation principle of the abnormal fault analysis method of the echo signal of the echo sounder of the transfer barge in the embodiment of the present application is as follows: since the beam angle of the detection pulse is related to the detection range of the echo sounder, when the swing angle of the barge is greater than half of the transmission angle, the receiving transducer of the echo sounder cannot receive the echo signal. Therefore, when the echo signal cannot be received, by comparing the transmission angle of the frequency with the swing angle of the barge, it can be determined whether the echo signal is lost due to the excessive swing angle of the barge. Since the amount of bubbles in the water body is affected by the barge load, barge speed, bow end upturn angle, hull swing angle, hull swing frequency, when the receiving transducer cannot receive the echo signal, the echo signal is lost. When the echo signal is detected and the hull sway angle does not exceed the maximum sway angle, the predicted bubble volume can be calculated based on the barge load, barge speed, bow upturned angle, hull sway angle, and hull sway frequency, and compared with the bubble volume threshold in the database to determine whether the echo sounder loses the echo signal due to bubble absorption; by extracting the image data of the first few frames before the echo signal is lost, the image is cropped, and the target detection is performed based on the YOLO algorithm to obtain the fish school information in the area, it can be determined whether there are fish schools in the detection area. If there are fish schools, it can be determined that the echo signal loss is caused by fish school scattering absorption, and the fault type is determined as fish school scattering echo abnormality. If there is both fish school scattering and non-bubble absorption, the fault type of the echo sounder can be determined as abnormal receiving transducer fault; if there is no abnormality, it can be determined that the receiving transducer of the echo sounder is faulty. When the barge's hull swings too far or there are too many bubbles in the water, the frequency of the detection signal emitted by the echo sounder can be lowered to expand the beam angle of the ultrasonic signal emitted by the echo sounder, and at the same time improve the penetration ability of the emitted detection signal on the bubbles in the water, so as to ensure that the receiving transducer of the echo sounder can receive the echo signal and ensure the normal operation of the echo sounder. When the receiving transducer of the echo sounder is damaged, a warning signal can be displayed on the display in the control cabin to prompt the operator to switch the echo sounder or perform emergency maintenance on the echo sounder.

[0049] Example 2 In this embodiment, a first echo sounder 4 and a second echo sounder 5 are installed at the bottom of the barge. The frequency of the detection signal emitted by the first echo sounder 4 is 50kHz, and the frequency of the detection signal emitted by the second echo sounder 5 is 200kHz. The first echo sounder 4 and the second echo sounder 5 are both located in the middle of the bottom of the barge.

[0050] More specifically, refer to Figure 4 The first echo sounder 4 is installed at 500mm rearward of #34, and the second echo sounder 5 is installed at 1300mm forward of #27. The first echo sounder 4 and the second echo sounder 5 are both located near the flat keel in the middle of the ship and kept as horizontal as possible. Compared with installing the first echo sounder 4 and the second echo sounder 5 in the area close to the bow, the influence of vibration on the first echo sounder 4 and the second echo sounder 5 can be reduced, and the adverse effects of the propeller and the thruster on the first echo sounder 4 and the second echo sounder 5 can be reduced.

[0051] Among them, the second echo sounder 5 is usually used for depth measurement. When the swaying angle of the barge is greater than half of the beam angle of the second echo sounder 5 and there are too many bubbles in the water, the first echo sounder 4 can be switched to lower the frequency of the detection signal, expand the beam angle of the detection signal, and enhance the ability of the detection signal to penetrate bubbles, thereby ensuring the terrain measurement needs during the navigation of the barge and ensuring the reliability of the echo sounder.

[0052] In addition, when the receiving transducer of the second echo sounder 5 fails and cannot receive the echo signal, an alarm signal can be displayed on the display in the control cabin to prompt the operator to switch to the first echo sounder 4.

[0053] In order to further improve the anti-bubble interference performance of the first echo sounder 4 and the second echo sounder 5, in the present embodiment, a deflector is installed on the outer side of the transmitting transducer and the receiving transducer of the first echo sounder 4 and the second echo sounder 5, respectively.

[0054] Please refer to Figure 5 The fairing is mainly composed of a side plate 2, a bottom plate 1 and a steel pipe 3. The side plate 2 and the steel pipe 3 are fixed to the bottom plate 1 by welding. The side plate 2 is arranged in a streamlined cylindrical shape, and the side plate 2 is arranged in an outward expansion shape from the bow end of the barge to the stern end. The transmitting transducer and the receiving transducer of the first echo sounder 4 and the second echo sounder 5 are respectively installed in the steel pipe 3 of the fairing.

[0055] The streamlined design of the side plate 2 can enhance the diversion effect on the water body, reduce the amount of bubble accumulation in the water body below the first echo sounder 4 and the second echo sounder 5 during the navigation of the barge, and further enhance the reliability of the first echo sounder 4 and the second echo sounder 5.

[0056] It should be noted that in some other embodiments, according to the actual measurement needs, more than two multi-beam echo sounders can be installed on the bottom of the barge to meet the use requirements of detection signals of different frequencies, which is not limited or elaborated here.

[0057] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for analyzing abnormal faults of echo signals of echo sounders on transshipment barges, characterized in that: The following steps are involved: Step S1, establishing an abnormal echo signal database, extracting various fault waveform features through equipment, and establishing a database; Step S2, fault analysis, obtaining the barge status monitoring data and the echo sounder working information, performing fault detection analysis based on the barge navigation information and the echo sounder working information, and determining the abnormality type; Step S3: detection adjustment: frequency modulation of the echo sounder according to the fault type.

2. The method for analyzing abnormal fault of echo signal of echo sounder of transfer barge according to claim 1 is characterized in that: The step S1 comprises the following steps: Step S11, collecting the detection signal sent by the transmitting transducer of the echo sounder and the echo signal received by the receiving transducer of the echo sounder; Step S12, performing time domain analysis on the echo signal, and marking the data for which no echo signal is received as abnormal echo data; Step S13, obtaining status monitoring data of the barge during navigation, wherein the status monitoring data includes barge load, barge speed, bow upturn angle, hull swing angle, and hull swing frequency; based on the status monitoring data, signal strength of echo signal, emission frequency of detection signal, and signal strength of detection signal, the abnormal data is calibrated as swing lost echo abnormality, bubble absorption echo abnormality, fish scattering echo abnormality, and receiving transducer failure abnormality.

3. The method for analyzing abnormal fault of echo signal of echo sounder of transfer barge according to claim 2 is characterized in that: The step S13 comprises the following steps: Step S131, determining the abnormal time point of the abnormal data of the echo signal, and determining the detection signal data and the status monitoring data at the abnormal time point; Step S132, obtaining the beam angle and the hull swing angle of the detection signal at the abnormal time point, and calculating whether the hull swing angle is too large to exceed the receiving range of the echo signal. If so, the abnormal data is marked as a swing lost echo abnormality; if not, bubble prediction calculation is performed; Step S133, based on the state monitoring data, calculate whether the bubble prediction amount at the time point when the abnormal data occurs exceeds the bubble amount threshold through the bubble prediction amount formula, if so, mark the abnormal data as bubble absorption echo abnormality; if not, perform fish scattering abnormality judgment; Step S134, obtaining echo signal data before the echo signal is lost, performing target detection through image cropping and YOLO algorithm, obtaining information about fish schools in the area, and if there are fish schools, determining that the fish school scattered echo is abnormal; if there are no fish schools, determining that the receiving transducer is faulty.

4. The method for analyzing abnormal fault of echo signal of echo sounder of transfer barge according to claim 3 is characterized in that: The step S133 comprises the following steps: Step S1331, obtaining historical bubble prediction data, detection signal strength, and echo signal strength at the same detection signal frequency; Step S1332, based on the historical bubble prediction quantity data and the echo signal strength data, the bubble prediction quantity data corresponding to the signal strength of the echo signal attenuating to 0 dB is calculated through a linear regression model, and the bubble prediction quantity data is calibrated as the bubble quantity threshold data of the detection signal of the frequency, and stored in the database.

5. The method for analyzing abnormal fault of echo signal of echo sounder of transfer barge according to claim 4 is characterized in that: The step S2 comprises the following steps: Step S21, obtaining status monitoring data, detection signal data, and echo signal data during the navigation of the barge; Step S22, matching the maximum hull swing angle and bubble volume threshold data from the database based on the transmission frequency of the detection signal; Step S23: performing abnormality type analysis based on the current barge hull sway angle data and bubble prediction data.

6. The method for analyzing abnormal fault of echo signal of echo sounder of transfer barge according to claim 5 is characterized in that: The step S23 comprises the following steps: Step S231, judging whether the current swing amplitude of the barge exceeds the maximum swing angle of the current transmission frequency of the detection signal, if so, judging that the fault type of the echo sounder is swing loss echo abnormality; if not, performing bubble prediction measurement comparison; Step S232, judging whether the bubble prediction amount of the current barge exceeds the bubble amount threshold value, if so, judging that the fault type of the echo sounder is the bubble absorption echo abnormality; if not, calculating the bubble prediction amount; Step S233, obtaining echo signal data before the echo signal is lost, performing target detection through image cropping and YOLO algorithm, and determining whether there is a school of fish in the acquisition area. If there is a school of fish in the area, the fault type of the echo sounder is determined to be abnormal fish scattered echo; if not, it is determined to be an abnormal receiving transducer fault.

7. The method for analyzing abnormal fault of echo signal of echo sounder of transfer barge according to claim 6 is characterized in that: The step S3 comprises the following steps: Step S31, installing a frequency-adjustable multi-beam echo sounder on the bottom of the transfer barge; Step S32, determine the abnormal type of the echo signal. If the abnormal type of the echo signal is a swing lost echo abnormality, a bubble absorption echo abnormality, or a fish scattering echo abnormality, lower the frequency of the echo sounder transmitting the detection signal until the echo signal is received again; if the receiving transducer of the echo sounder fails, issue a fault alarm signal.

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