An early warning system for the operation of flow measuring instruments for hydroacoustic detection based on data analysis

Abstract

The present invention belongs to the field of hydroacoustic detection, relates to data analysis technology, and is used to solve the problem that the existing technology cannot monitor the actual measurement accuracy defects of ultrasonic flowmeters. Specifically, it is an operation warning system for a flow measuring instrument for hydroacoustic detection based on data analysis, including an operation warning platform, and the operation warning platform is communicatively connected with an accuracy test module, an accuracy warning module, a stability evaluation module and a database; the accuracy test module is used to perform accuracy test and analysis on the flow measuring instrument for hydroacoustic detection: an ultrasonic flowmeter for hydroacoustic detection is marked as a test object, and the test object is tested and analyzed several times and the turbidity critical value of the test object in each test and analysis process is obtained; the present invention can determine whether the turbidity warning coefficient of the measured fluid meets the accuracy guarantee range of the monitored object by regularly monitoring the turbidity warning coefficient of the measured fluid. Under the premise of regularly performing accuracy test and analysis, the turbidity monitoring of the measured fluid can ensure the measurement accuracy of the monitored object.

Description

Technical Field

[0001] The invention belongs to the field of hydroacoustic detection and relates to data analysis technology, in particular to an operation early warning system of a flow measuring instrument for hydroacoustic detection based on data analysis. Background Art

[0002] In view of the complex ocean environment and diverse target types, the existing single surface and underwater platform single sensor has limited detection capabilities and poor stability, and it is difficult to meet the future needs of accurate detection and identification of hydroacoustic targets. In order to adapt to the complex ocean environment and obtain richer and more accurate target information, more and more various types of underwater detection equipment and sensors are being developed, tested and applied.

[0003] Ultrasonic flow meters, which are widely used in hydroacoustic detection, are suitable for non-contact measurement and do not interfere with fluid flow. They have the advantages of a wide range of applications, high measurement accuracy, and low initial measurement. Due to the non-contact working characteristics of ultrasonic flow meters, they generally do not suffer from corrosion, blockage, and other faults that seriously affect measurement accuracy. Therefore, the traditional method of performing accuracy assessment based on the monitoring data output by the instrument is usually unable to monitor the actual measurement accuracy defects of the ultrasonic flow meter.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a water acoustic detection flow measuring instrument operation early warning system based on data analysis, which is used to solve the problem that the existing technology cannot monitor the actual measurement accuracy defects of ultrasonic flow meters;

[0006] The technical problem to be solved by the present invention is: how to provide an operation warning system for a flow measuring instrument for hydroacoustic detection based on data analysis that can monitor the actual measurement accuracy defects of an ultrasonic flow meter.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The data analysis-based hydroacoustic detection flow measuring instrument operation warning system includes an operation warning platform, wherein the operation warning platform is communicatively connected with an accuracy test module, an accuracy warning module, a stability evaluation module and a database;

[0009] The accuracy test module is used to perform accuracy test analysis on the flow measuring instrument for hydroacoustic detection: mark the ultrasonic flow meter for hydroacoustic detection as the test object, perform several test analyses on the test object and obtain the turbidity critical value of the test object in each test analysis process; form a critical set from the turbidity critical values ​​of all test analysis processes, perform data cleaning on the critical set to obtain the turbidity limit value of the test object; determine whether the test object has passed the accuracy test analysis by the turbidity limit value; send the turbidity limit values ​​of all test objects that have passed the accuracy test analysis to the database for storage through the operation early warning platform;

[0010] The precision warning module is used to perform precision monitoring and warning analysis on the flow measuring instrument for hydroacoustic detection: when the test object passes the precision test analysis and performs the flow measurement task, the test object is marked as a monitoring object, a number of monitoring time points are generated during the monitoring object's execution of the flow measurement task, the turbidity warning coefficient of the task fluid is obtained at the monitoring time point, the turbidity limit value of the monitoring object is retrieved through the database, the turbidity warning coefficient is compared with the turbidity limit value, and the turbidity of the task fluid is judged whether it meets the test precision requirement of the monitoring object through the comparison result;

[0011] The stability evaluation module is used to evaluate and analyze the operational stability of the flow measuring instrument for hydroacoustic detection.

[0012] Furthermore, the process of obtaining the turbidity critical value of the test object in the test and analysis process includes: each test and analysis process includes several test time points, the test object is carried on a drone, the flow value of the test fluid is collected by a Doppler radar and marked as a flow test value, and the test error value and turbidity coefficient of the test object are obtained at the test time point; the turbidity grayscale threshold and the test error threshold are retrieved through the database, and the minimum value of the turbidity coefficient at the test time point in the test analysis process where the test error value is not greater than the test error threshold is marked as the turbidity critical value of the test and analysis process.

[0013] Furthermore, the process of obtaining the test error value and turbidity coefficient of the test object at the test time point includes: obtaining the flow value of the test fluid through a calibrated contact flow tester and marking it as a flow calibration value, marking the absolute value of the difference between the flow calibration value and the flow test value at the test time point as the test error value at the test time point, photographing the test fluid through a high-definition camera carried by a drone at the test time point to obtain a test image, enlarging the test image into a pixel grid image and performing a grayscale transformation, marking the pixel grids in the test image whose grayscale values ​​are less than the turbidity grayscale threshold as turbid grids, and marking the ratio of the number of turbid grids to the total number of pixel grids in the test image as the turbidity coefficient of the test image.

[0014] Furthermore, the specific process of performing data cleaning processing on the critical set includes: performing variance calculation on all elements in the critical set to obtain the concentration coefficient, obtaining the concentration threshold through the database, and comparing the concentration coefficient with the concentration threshold: if the concentration coefficient is less than the concentration threshold, the data cleaning processing is determined to be completed, and the minimum element in the critical set is marked as the turbidity limit value of the test object; if the concentration coefficient is greater than or equal to the concentration threshold, the maximum element and the minimum element in the critical set are eliminated, and then the concentration coefficient of the critical set is recalculated, and so on, until the concentration coefficient is less than the concentration threshold.

[0015] Furthermore, the specific process of determining whether the test object has passed the precision test analysis includes: obtaining the turbidity limit threshold through the database, and comparing the turbidity limit value of the test object with the turbidity limit threshold: if the turbidity limit value is less than the turbidity limit threshold, then the test object is determined to have passed the precision test analysis; if the turbidity limit value is greater than or equal to the turbidity limit threshold, then the test object is determined to have failed the precision test analysis, and a preprocessing signal is generated and sent to the mobile phone terminal of the manager through the operation early warning platform.

[0016] Furthermore, the process of obtaining the turbidity warning coefficient of the mission fluid at the monitoring time point includes: taking images of the mission fluid by a high-definition camera carried by a drone, marking the captured images as monitoring images, enlarging the monitoring images into pixel grid images and performing grayscale transformation, marking the pixels in the monitoring images whose grayscale values ​​are less than the turbidity grayscale threshold as warning grids, and marking the ratio of the number of warning grids to the number of all pixel grids in the monitoring image as the turbidity warning coefficient of the monitoring image.

[0017] Furthermore, the specific process of determining whether the turbidity of the task fluid meets the test accuracy requirements of the monitored object includes: if the turbidity warning coefficient is less than the turbidity limit value, it is determined that the turbidity of the task fluid does not meet the test accuracy requirements of the monitored object, and an accuracy warning signal is generated and sent to the mobile phone terminal of the manager through the operation warning platform; if the turbidity warning coefficient is greater than or equal to the turbidity limit value, it is determined that the turbidity of the task fluid meets the test accuracy requirements of the monitored object.

[0018] Furthermore, the specific process of the stability assessment module evaluating and analyzing the operating stability of the flow measuring instrument for hydroacoustic detection includes: obtaining the flow value of the task fluid in real time during the execution of the flow measurement task by the monitored object and marking it as the flow monitoring value, a monitoring period is composed of two adjacent monitoring time points, and at the end of the monitoring period, the quantity difference data LC, interval data JG and floating data FD are obtained and numerically calculated to obtain the stability coefficient WD of the monitored object during the monitoring period, and whether the operating stability of the monitored object during the monitoring period meets the requirements is judged by the stability coefficient WD.

[0019] Furthermore, the process of acquiring the quantity difference data LC includes: marking the maximum value and the minimum value of the flow monitoring value in the monitoring period as the high quantity value and the low quantity value respectively, and marking the difference between the high quantity value and the low quantity value as the quantity difference data LC; the interval data JG is the time interval between the high quantity value and the low quantity value at corresponding time points in the monitoring period, and the process of acquiring the floating data FD includes: marking the average value of the flow monitoring value in the monitoring period as the flow mean value, an upper float period is formed by the continuous time length when the flow monitoring value is greater than the flow mean value, and a lower float period is formed by the continuous time length when the flow monitoring value is less than the flow mean, and the sum of the number of upper float periods and the number of lower float periods in the monitoring period is marked as floating data FD.

[0020] Furthermore, the specific process of determining whether the operation stability of the monitored object during the monitoring period meets the requirements includes: obtaining the stability threshold WDmax through the database, and comparing the stability coefficient WD of the monitoring period with the stability threshold WDmax: if the stability coefficient WD is less than the stability threshold WDmax, it is determined that the operation stability of the monitored object during the monitoring period meets the requirements; if the stability coefficient WD is greater than or equal to the stability threshold WDmax, it is determined that the operation stability of the monitored object during the monitoring period does not meet the requirements, and a stability abnormality signal is generated and sent to the mobile terminal of the manager through the operation early warning platform.

[0021] The present invention has the following beneficial effects:

[0022] 1. The accuracy test module can be used to perform accuracy test and analysis on flow measuring instruments for hydroacoustic detection. In view of the fact that ultrasonic flow meters have certain requirements on the concentration of suspended particles or bubbles in the fluid, and are not suitable for the application characteristics of transparent fluids or fluids without suspended particles, a comprehensive analysis is performed by combining the calibration flow measurement error with the turbidity of the fluid to obtain the critical turbidity value under the test accuracy of the test object, providing data support for accuracy early warning analysis;

[0023] 2. The accuracy early warning module can be used to conduct accuracy monitoring and early warning analysis on the flow measuring instrument for hydroacoustic detection. By regularly monitoring the turbidity early warning coefficient of the measured fluid, it can be judged whether it meets the accuracy guarantee range of the monitored object. The measurement accuracy of the monitored object is less affected by external factors, but it is closely related to the clarity of the measured fluid. Under the premise of regular accuracy testing and analysis, monitoring the turbidity of the measured fluid can ensure the measurement accuracy of the monitored object;

[0024] 3. The stability assessment module can be used to evaluate and analyze the operating stability of the flow measuring instrument used for hydroacoustic detection, process the output values ​​of the monitored object to obtain multiple operating stability parameters, and comprehensively analyze and calculate multiple operating stability parameters to obtain the stability coefficient. Feedback on the operating stability of the monitored object is given based on the stability coefficient, and timely feedback and early warning are given when stability anomalies occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0027] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] Embodiment 1: Figure 1 As shown, the operation warning system of the flow measuring instrument for hydroacoustic detection based on data analysis includes an operation warning platform, and the operation warning platform is communicatively connected with an accuracy test module, an accuracy warning module, a stability evaluation module and a database.

[0030] Ultrasonic flow meters have certain requirements on the concentration of suspended particles or bubbles in the fluid and are not suitable for transparent fluids or fluids without suspended particles. At the same time, ultrasonic flow meters have the application characteristics of non-contact measurement and do not interfere with the flow of fluids. In view of the non-contact measurement method, the probability of sudden failure of ultrasonic flow meters is low, and their overall measurement accuracy is highly correlated with the clarity of the measured fluid and the loading stability of the drone. Therefore, traditional accuracy monitoring methods are less applicable to ultrasonic flow meters.

[0031] The accuracy test module is used to regularly perform accuracy test and analysis on flow measuring instruments for hydroacoustic detection: the ultrasonic flow meter for hydroacoustic detection is marked as the test object, and the test object is tested and analyzed several times. Each test and analysis process includes several test time points. The test object is carried on a drone, and the flow value of the test fluid is collected by Doppler radar and marked as the flow test value. At the test time point, the flow value of the test fluid is obtained by a calibrated contact flow tester and marked as the flow verification value. The absolute value of the difference between the flow verification value and the flow test value at the test time point is marked as the test error value at the test time point. At the test time point, the high-definition camera carried by the drone is used to The test fluid is imaged to obtain a test image, the test image is enlarged into a pixel grid image and grayscale transformation is performed, the turbidity grayscale threshold and the test error threshold are retrieved through the database, the pixel grids in the test image whose grayscale value is less than the turbidity grayscale threshold are marked as turbid grids, and the ratio of the number of turbid grids to the total number of pixel grids in the test image is marked as the turbidity coefficient of the test image; the minimum value of the turbidity coefficient at the test time point when the test error value in the test analysis process is not greater than the test error threshold is marked as the turbidity critical value of the test analysis process; the turbidity critical values ​​of all test analysis processes constitute a critical set, and data cleaning processing is performed on the critical set: variance calculation is performed on all elements in the critical set The concentration coefficient is calculated, and the concentration threshold is obtained through the database. The concentration coefficient is compared with the concentration threshold: if the concentration coefficient is less than the concentration threshold, the data cleaning process is determined to be completed, and the minimum element in the critical set is marked as the turbidity limit value of the test object; the turbidity limit value of the test object is updated regularly; if the concentration coefficient is greater than or equal to the concentration threshold, the maximum element and the minimum element in the critical set are eliminated, and then the concentration coefficient of the critical set is recalculated, and so on, until the concentration coefficient is less than the concentration threshold; the turbidity limit threshold is obtained through the database, and the turbidity limit value of the test object is compared with the turbidity limit threshold: if the turbidity limit value is less than the turbidity limit threshold, the test object is determined to be The object passes the precision test analysis; if the turbidity limit value is greater than or equal to the turbidity limit threshold, the test object is judged to have failed the precision test analysis, and a preprocessing signal is generated and sent to the administrator's mobile terminal through the operation warning platform; the turbidity limit values ​​of all test objects that have passed the precision test analysis are sent to the database for storage through the operation warning platform; in view of the fact that the ultrasonic flowmeter has certain requirements on the concentration of suspended particles or bubbles in the fluid, it is not suitable for the application characteristics of transparent or non-suspended particle fluids. A comprehensive analysis is performed on the flow measurement error and the fluid turbidity to obtain the turbidity critical value under the test accuracy of the test object, providing data support for the precision warning analysis.

[0032] The precision warning module is used to perform precision monitoring and warning analysis on flow measuring instruments for hydroacoustic detection: when the test object passes the precision test analysis and performs the flow measurement task, the test object is marked as a monitoring object, and several monitoring time points are generated during the monitoring object's execution of the flow measurement task. The task fluid is imaged by a high-definition camera carried by a drone, and the captured image is marked as a monitoring image. The monitoring image is enlarged into a pixel grid image and grayscale transformation is performed. The pixel grids in the monitoring image whose grayscale value is less than the turbidity grayscale threshold are marked as warning grids, and the ratio of the number of warning grids to the number of all pixel grids in the monitoring image is marked as the turbidity warning coefficient of the monitoring image. The turbidity boundary value of the monitoring object is retrieved from the database, and the turbidity warning coefficient is compared with the turbidity threshold value. The turbidity limit value is compared: if the turbidity warning coefficient is less than the turbidity limit value, it is determined that the turbidity of the task fluid does not meet the test accuracy requirements of the monitored object, and an accuracy warning signal is generated and sent to the mobile phone terminal of the manager through the operation warning platform; if the turbidity warning coefficient is greater than or equal to the turbidity limit value, it is determined that the turbidity of the task fluid meets the test accuracy requirements of the monitored object; by regularly monitoring the turbidity warning coefficient of the measured fluid to determine whether it meets the accuracy guarantee range of the monitored object, the measurement accuracy of the monitored object is less affected by external factors, but is closely related to the clarity of the measured fluid. Under the premise of regular accuracy test analysis, turbidity monitoring of the measured fluid can ensure the measurement accuracy of the monitored object.

[0033] The stability evaluation module is used to evaluate and analyze the operation stability of the flow measuring instrument for hydroacoustic detection: the flow value of the task fluid is obtained in real time during the process of the monitored object performing the flow measurement task and marked as the flow monitoring value, and a monitoring period is composed of two adjacent monitoring time points. At the end of the monitoring period, the quantity difference data LC, the interval data JG and the floating data FD are obtained. The process of obtaining the quantity difference data LC includes: marking the maximum value and the minimum value of the flow monitoring value in the monitoring period as the high value and the low value, respectively, and marking the difference between the high value and the low value as the quantity difference data LC; the interval data JG is the time interval between the high value and the low value at the corresponding time point in the monitoring period, and the process of obtaining the floating data FD includes: marking the average value of the flow monitoring value in the monitoring period as the flow mean value, forming an upper float period by the continuous time length when the flow monitoring value is greater than the flow mean, and forming a lower float period by the continuous time length when the flow monitoring value is less than the flow mean, and marking the sum of the number of upper float periods and the number of lower float periods in the monitoring period as the floating data F D. The stability coefficient WD of the monitored object during the monitoring period is obtained through the formula WD=(k1*LC+k2*FD) / (k3*JG), where k1, k2 and k3 are all proportional coefficients, and k3>k2>k1. The stability threshold WDmax is obtained through the database, and the stability coefficient WD of the monitoring period is compared with the stability threshold WDmax: if the stability coefficient WD is less than the stability threshold WDmax, it is determined that the operation stability of the monitored object during the monitoring period meets the requirements; if the stability coefficient WD is greater than or equal to the stability threshold WDmax, it is determined that the operation stability of the monitored object during the monitoring period does not meet the requirements, and a stability abnormality signal is generated and sent to the mobile phone terminal of the manager through the operation early warning platform; the output values ​​of the monitored object are processed to obtain multiple operation stability parameters, and the multiple operation stability parameters are comprehensively analyzed and calculated to obtain the stability coefficient, and feedback is given to the operation stability of the monitored object according to the stability coefficient, so as to provide timely feedback and early warning when stability abnormalities occur.

[0034] Embodiment 2: Figure 2 As shown, the method for early warning of the operation of a flow measuring instrument for hydroacoustic detection based on data analysis includes the following steps:

[0035] Step 1: Perform accuracy test and analysis on the flow measuring instrument for hydroacoustic detection: mark the ultrasonic flow meter for hydroacoustic detection as the test object, perform several test analyses on the test object, and obtain the turbidity critical value of the test analysis process; the turbidity critical values ​​of all test analysis processes constitute a critical set, and perform data cleaning on the critical set to obtain the turbidity limit value of the test object;

[0036] Step 2: Perform precision monitoring and early warning analysis on the flow measuring instrument for hydroacoustic detection: When the test object passes the precision test analysis and performs the flow measurement task, the test object is marked as a monitoring object. When the monitoring object performs the flow measurement task, the turbidity early warning coefficient is obtained regularly, and the turbidity of the task fluid is judged by the turbidity early warning coefficient to determine whether it meets the requirements;

[0037] Step 3: Evaluate and analyze the operational stability of the flow measuring instrument for hydroacoustic detection: a monitoring period is composed of two adjacent monitoring time points, and the stability coefficient WD of the monitoring period is obtained. The stability coefficient WD is used to determine whether the operational stability of the monitored object meets the requirements.

[0038] The data analysis-based hydroacoustic detection flow measurement instrument operation warning system, when working, marks the hydroacoustic detection ultrasonic flow meter as a test object, performs several test analyses on the test object, and obtains the turbidity critical value of the test analysis process; the turbidity critical values ​​of all test analysis processes constitute a critical set, and the critical set is subjected to data cleaning processing to obtain the turbidity limit value of the test object; when the test object passes the precision test analysis and performs the flow measurement task, the test object is marked as a monitoring object, and the turbidity warning coefficient is obtained regularly when the monitoring object performs the flow measurement task process, and whether the turbidity of the task fluid meets the requirements is judged by the turbidity warning coefficient; a monitoring period is constituted by two adjacent monitoring time points, and the stability coefficient WD of the monitoring period is obtained, and whether the operation stability of the monitoring object meets the requirements is judged by the stability coefficient WD.

[0039] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0040] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula WD=(k1*LC+k2*FD) / (k3*JG); technicians in this field collect multiple groups of sample data and set corresponding stability coefficients for each group of sample data; substitute the set stability coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of k1, k2 and k3 as 3.25, 2.41 and 2.06 respectively;

[0041] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding stability coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the stability coefficient is proportional to the value of the quantitative difference data.

[0042] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0043] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A hydroacoustic detection flow measuring instrument operation early warning system based on data analysis, characterized in that: It includes an operation warning platform, which is communicatively connected with an accuracy test module, an accuracy warning module, a stability assessment module and a database; The accuracy test module is used to perform accuracy test analysis on the flow measuring instrument for hydroacoustic detection: mark the ultrasonic flow meter for hydroacoustic detection as the test object, perform several test analyses on the test object and obtain the turbidity critical value of the test object in each test analysis process; form a critical set from the turbidity critical values ​​of all test analysis processes, perform data cleaning on the critical set to obtain the turbidity limit value of the test object; determine whether the test object has passed the accuracy test analysis by the turbidity limit value; send the turbidity limit values ​​of all test objects that have passed the accuracy test analysis to the database for storage through the operation early warning platform; The precision warning module is used to perform precision monitoring and warning analysis on the flow measuring instrument for hydroacoustic detection: when the test object passes the precision test analysis and performs the flow measurement task, the test object is marked as a monitoring object, a number of monitoring time points are generated during the monitoring object's execution of the flow measurement task, the turbidity warning coefficient of the task fluid is obtained at the monitoring time point, the turbidity limit value of the monitoring object is retrieved through the database, the turbidity warning coefficient is compared with the turbidity limit value, and the turbidity of the task fluid is judged whether it meets the test precision requirement of the monitoring object through the comparison result; The stability evaluation module is used to evaluate and analyze the operational stability of the flow measuring instrument for hydroacoustic detection; The process of obtaining the turbidity critical value of the test object in the test and analysis process includes: each test and analysis process includes several test time points, the test object is carried on a drone, the flow value of the test fluid is collected by Doppler radar and marked as the flow test value, and the test error value and turbidity coefficient of the test object are obtained at the test time point; the turbidity grayscale threshold and the test error threshold are retrieved through the database, and the minimum value of the turbidity coefficient at the test time point when the test error value in the test and analysis process is not greater than the test error threshold is marked as the turbidity critical value of the test and analysis process.

2. The hydroacoustic detection flow measuring instrument operation early warning system based on data analysis according to claim 1 is characterized in that: The process of obtaining the test error value and turbidity coefficient of the test object at the test time point includes: obtaining the flow value of the test fluid through a calibrated contact flow tester and marking it as a flow calibration value, marking the absolute value of the difference between the flow calibration value and the flow test value at the test time point as the test error value at the test time point, photographing the test fluid through a high-definition camera carried by a drone at the test time point to obtain a test image, enlarging the test image into a pixel grid image and performing grayscale transformation, marking the pixel grids in the test image whose grayscale values ​​are less than the turbidity grayscale threshold as turbid grids, and marking the ratio of the number of turbid grids to the total number of pixel grids in the test image as the turbidity coefficient of the test image.

3. The hydroacoustic detection flow measuring instrument operation early warning system based on data analysis according to claim 2 is characterized in that: The specific process of data cleaning processing for the critical set includes: performing variance calculation on all elements in the critical set to obtain the concentration coefficient, obtaining the concentration threshold through the database, and comparing the concentration coefficient with the concentration threshold: if the concentration coefficient is less than the concentration threshold, the data cleaning processing is determined to be completed, and the minimum element in the critical set is marked as the turbidity limit value of the test object; if the concentration coefficient is greater than or equal to the concentration threshold, the maximum element and the minimum element in the critical set are eliminated, and then the concentration coefficient of the critical set is recalculated, and so on, until the concentration coefficient is less than the concentration threshold.

4. The hydroacoustic detection flow measuring instrument operation early warning system based on data analysis according to claim 3 is characterized in that: The specific process of determining whether the test object has passed the precision test analysis includes: obtaining the turbidity limit threshold through the database, and comparing the turbidity limit value of the test object with the turbidity limit threshold: if the turbidity limit value is less than the turbidity limit threshold, then the test object is determined to have passed the precision test analysis; if the turbidity limit value is greater than or equal to the turbidity limit threshold, then the test object is determined to have failed the precision test analysis, and a preprocessing signal is generated and sent to the mobile phone terminal of the manager through the operation early warning platform.

5. The hydroacoustic detection current measuring instrument operation early warning system based on data analysis according to claim 4 is characterized in that: The process of obtaining the turbidity warning coefficient of the mission fluid at the monitoring time point includes: taking images of the mission fluid with a high-definition camera carried by a drone, marking the captured images as monitoring images, enlarging the monitoring images into pixel grid images and performing grayscale transformation, marking the pixels in the monitoring images whose grayscale values ​​are less than the turbidity grayscale threshold as warning grids, and marking the ratio of the number of warning grids to the number of all pixel grids in the monitoring image as the turbidity warning coefficient of the monitoring image.

6. The hydroacoustic detection current measuring instrument operation early warning system based on data analysis according to claim 5 is characterized in that: The specific process of determining whether the turbidity of the task fluid meets the test accuracy requirements of the monitored object includes: if the turbidity warning coefficient is less than the turbidity limit value, it is determined that the turbidity of the task fluid does not meet the test accuracy requirements of the monitored object, and an accuracy warning signal is generated and sent to the mobile phone terminal of the manager through the operation warning platform; if the turbidity warning coefficient is greater than or equal to the turbidity limit value, it is determined that the turbidity of the task fluid meets the test accuracy requirements of the monitored object.

7. The hydroacoustic detection current measuring instrument operation early warning system based on data analysis according to claim 6 is characterized in that: The specific process of the stability assessment module evaluating and analyzing the operating stability of the flow measuring instrument for hydroacoustic detection includes: obtaining the flow value of the task fluid in real time during the flow measurement task of the monitored object and marking it as the flow monitoring value; a monitoring period is composed of two adjacent monitoring time points; at the end of the monitoring period, the quantity difference data LC, interval data JG and floating data FD are obtained and numerically calculated to obtain the stability coefficient WD of the monitored object during the monitoring period; and whether the operating stability of the monitored object during the monitoring period meets the requirements is judged by the stability coefficient WD.

8. The hydroacoustic detection current measuring instrument operation early warning system based on data analysis according to claim 7 is characterized in that: The process of obtaining the quantity difference data LC includes: marking the maximum value and the minimum value of the flow monitoring value in the monitoring period as the high value and the low value respectively, and marking the difference between the high value and the low value as the quantity difference data LC; the interval data JG is the time interval between the high value and the low value at the corresponding time points in the monitoring period, and the process of obtaining the floating data FD includes: marking the average value of the flow monitoring value in the monitoring period as the flow mean value, an upper float period is formed by the continuous time length that the flow monitoring value is greater than the flow mean value, and a lower float period is formed by the continuous time length that the flow monitoring value is less than the flow mean, and the sum of the number of upper float periods and the number of lower float periods in the monitoring period is marked as floating data FD.

9. The hydroacoustic detection current measuring instrument operation early warning system based on data analysis according to claim 8 is characterized in that: The specific process of determining whether the operation stability of the monitored object during the monitoring period meets the requirements includes: obtaining the stability threshold WDmax through the database, and comparing the stability coefficient WD of the monitoring period with the stability threshold WDmax: if the stability coefficient WD is less than the stability threshold WDmax, it is determined that the operation stability of the monitored object during the monitoring period meets the requirements; if the stability coefficient WD is greater than or equal to the stability threshold WDmax, it is determined that the operation stability of the monitored object during the monitoring period does not meet the requirements, and a stability abnormality signal is generated and sent to the mobile terminal of the manager through the operation early warning platform.

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