A system for analyzing inclination errors of an environmental monitoring instrument

Abstract

The application relates to the technical field of instrument error monitoring, and discloses an environmental monitoring instrument tendency error analysis system which comprises a multidimensional acquisition module and an intelligent analysis module. The thermosalinograph tendency error analysis system obtains the conductivity data, temperature data and water depth data of a measured water body through the multidimensional acquisition module, classifies and forms a data set, the intelligent analysis module analyzes the time difference between different physical parameters, generates a time difference data set, analyzes the fluctuation range of different physical parameters, generates a fluctuation data set, quickly locates the measurement deviation, the intelligent analysis module analyzes the authenticity of each measurement result, generates a credibility index, dynamically evaluates the credibility of single measurement, can adapt to the monitoring requirements of more complex environments, accurately diagnoses the error source, the intelligent analysis module sets a fixed range threshold, evaluates the influence factors leading to the thermosalinograph tendency error and the authenticity of the measurement result, and outputs corresponding management suggestions, and the automatic operation and maintenance has high practicability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of instrument error monitoring, in particular to an environmental monitoring instrument inclination error analysis system. BACKGROUND

[0002] There are many types of environmental monitoring instruments, including water quality monitoring instruments, atmospheric environment monitoring instruments, radiation monitoring instruments, etc. Among them, the temperature-salinity-depth instrument is an instrument used to measure the physical parameters of water bodies, which can simultaneously measure the conductivity, temperature and depth of seawater. Through these data, the salinity and other related physical parameters of seawater, such as sound speed, can be calculated. The temperature-salinity-depth instrument mainly consists of an underwater probe, a recording display and a connecting cable. The underwater probe contains a thermosensitive element and a pressure-sensitive element for sensing temperature and pressure, and the recording display is responsible for receiving, processing, recording and displaying data from the probe and serving as the manipulator of the entire device. The inclination error of the temperature-salinity-depth instrument refers to the long-term error caused by the system itself. This error can be caused by a variety of factors, including but not limited to sensor failure, calibration error, attachment error, etc. These single-cause errors can seriously affect data quality and may lead users to draw incorrect scientific conclusions or decision-making basis. To solve the inclination error of the temperature-salinity-depth instrument, methods such as regular calibration, artificial intelligence recognition and optimized sampling can be used. By regularly calibrating and maintaining the temperature-salinity-depth instrument, system errors can be detected and corrected in a timely manner to ensure the accuracy and stability of the device. Artificial intelligence technology can also be used to dynamically constrain and automatically identify the data collected by the temperature-salinity-depth instrument, effectively identifying various flying point conditions, and then establishing a corresponding error knowledge base based on the flying point distribution matrix of the temperature-salinity-depth instrument. When deploying the temperature-salinity-depth instrument, the sampling scheme can be optimized to reduce the impact of inclination error.

[0003] Currently, the traditional environmental monitoring instrument inclination error analysis system requires manual error diagnosis, which is time-consuming and inefficient. Since the calibration process involves precise control of multiple factors, the entire calibration process is both tedious and time-consuming, making it difficult to meet the actual needs of rapid diagnosis at sea and lacking practicality. SUMMARY

[0004] (I) Technical problems solved

[0005] To solve the problems of the prior art, the present application provides an environmental monitoring instrument inclination error analysis system, which has the advantages of precise error diagnosis, automatic operation and maintenance, and strong practicality, and solves the problems of the traditional environmental monitoring instrument inclination error analysis system, which requires manual error diagnosis and is difficult to meet the actual needs of rapid diagnosis at sea, and lacks practicality.

[0006] (II) Technical solutions

[0007] In order to achieve the above object, the present application provides the following technical scheme: an environmental monitoring instrument tendency error analysis system, comprising a multi-dimensional acquisition module and an intelligent analysis module;

[0008] The multi-dimensional acquisition module is composed of a conductivity measurement unit, a temperature measurement unit and a water depth measurement unit, the conductivity measurement unit collects a conductivity data set through a network connection with a CTD, the temperature measurement unit collects a temperature data set through a network connection with the CTD, and the water depth measurement unit collects a water depth data set through a network connection with the CTD;

[0009] The intelligent analysis module is composed of a time difference analysis unit, a fluctuation analysis unit, a measurement analysis unit and an error management unit, the time difference analysis unit analyzes a time difference data group Scsj between physical parameters according to the conductivity data set, the temperature data set and the water depth data set, the fluctuation analysis unit analyzes a fluctuation data group Bdsj of the physical parameters according to the conductivity data set, the temperature data set and the water depth data set, the measurement analysis unit analyzes a credibility index Kxzs of each measurement result according to the conductivity data set, the temperature data set and the water depth data set, the error management unit is provided with a fixed range of time difference threshold SCY, conductivity threshold DBY, temperature threshold WBY, depth threshold HBY and credibility threshold KXY, and further evaluates the influencing factors causing the CTD tendency error and the authenticity of the measurement result, and outputs corresponding management suggestions.

[0010] Preferably, the conductivity data set has an expression of {D1 s , D2 s , D3 s ,..., Dn s}, D1 s to Dn s represent the conductivity measured for the first time to the n-th time, and s represents the time point at which the conductivity is obtained.

[0011] Preferably, the temperature data set has an expression of {W1 j , W2 j , W3 j ,..., Wn j}, W1 j to Wn j represent the temperature value measured for the first time to the n-th time, and j represents the time point at which the temperature value is obtained.

[0012] Preferably, the water depth data set has an expression of {H1 m , H2 m , H3 m ,..., Hn m}, H1 m to Hn mThe first measurement to the depth value of the n-th measurement, m represents the time point of obtaining the depth value.

[0013] Preferably, the time difference data set Scsj calculation process as follows:

[0014] According to the conductivity data set, temperature data set and water depth data set, the conductivity, temperature value and depth value of the i-th measurement are extracted, and the time point of obtaining the conductivity of the i-th time is marked as i s The time point of obtaining the temperature value of the i-th time is marked as i j The time point of obtaining the depth value of the i-th time is marked as i m ;

[0015]

[0016] In the formula, The time difference of obtaining conductivity and temperature value in each measurement process is calculated in turn, The time difference of obtaining conductivity and depth value in each measurement process is calculated in turn, The time difference of obtaining depth value and temperature value in each measurement process is calculated in turn.

[0017] Preferably, the fluctuation data set Bdsj calculation process as follows:

[0018]

[0019]

[0020] In the formula, The average conductivity of the measured water body, The average temperature value of the measured water body, The average depth value of the measured water body, Dk s The conductivity of the k-th measurement, Wk j The temperature value of the k-th measurement, Hk m The depth value of the k-th measurement, The fluctuation range of conductivity calculated according to the standard deviation formula, The fluctuation range of temperature value calculated according to the standard deviation formula, The fluctuation range of depth value calculated according to the standard deviation formula.

[0021] Preferably, the calculation process of the credibility index Kxzs as follows:

[0022]

[0023] In the formula, BD represents a standard value for measuring conductivity, β1 represents a weight for a standard value and conductivity ratio, BW represents a standard value for measuring temperature value, β2 represents a weight for a standard value and temperature value ratio, BH represents a standard value for measuring depth value, β3 represents a weight for a standard value and depth value ratio, β1, β2 and β3 are all constants, and β1+β2+β3=1, Kxzs represents a confidence index of the kth measurement result calculated according to the β1, β2 and β3 weights. k .

[0024] Preferably, when any value in the time difference data set Scsj exceeds the time difference threshold SCY, it indicates that the response delay causes the CTD to be prone to errors, and the delay time difference should be corrected in time.

[0025] Preferably, when the fluctuation range of conductivity in the fluctuation data set Bdsj exceeds the conductivity threshold DBY, the fluctuation range of temperature value exceeds the temperature threshold WBY, or the fluctuation range of depth value exceeds the depth threshold HBY, it indicates that the attachment causes the CTD to be prone to errors, and the probe in the water should be cleaned in time.

[0026] Preferably, when the confidence index Kxzs exceeds the confidence threshold KXY, it indicates that the authenticity of the measurement result is abnormal, and the measurement scheme should be optimized.

[0027] Compared with the prior art, the present application provides an environmental monitoring instrument tendency error analysis system, which has the following beneficial effects:

[0028] 1、The present application connects the CTD through a multi-dimensional acquisition module network, obtains the conductivity data, temperature data and water depth data of the measured water body, and classifies and forms conductivity data set, temperature data set and water depth data set, ensuring the time sequence integrity and traceability of multi-dimensional data, avoiding the errors that may be introduced by traditional manual recording, improving the data acquisition efficiency, the intelligent analysis module analyzes the time difference between different physical parameters according to the conductivity data set, temperature data set and water depth data set, and generates the corresponding time difference data set Scsj, which helps to eliminate the systematic error caused by the different time sequences of the sensors, and analyzes the fluctuation range of different physical parameters, generates the corresponding fluctuation data set Bdsj, quickly locates the measurement deviation caused by biological attachment or mechanical failure, the intelligent analysis module analyzes the authenticity of each measurement result, and generates the corresponding confidence index Kxzs, flexibly adjusts the weight coefficient, dynamically evaluates the confidence of single measurement, can adapt to more complex environmental monitoring needs, and accurately diagnoses the error source.

[0029] 2、The application sets a fixed range of time difference threshold SCY, conductivity threshold DBY, temperature threshold WBY, depth threshold HBY and trust threshold KXY through the intelligent analysis module, and then combines the time difference data set Scsj, fluctuation data set Bdsj and trust index Kxzs to evaluate the influencing factors causing the CTD inclination error and the authenticity of the measurement results. When any value in the time difference data set Scsj exceeds the time difference threshold SCY, it indicates that the response delay causes the CTD inclination error, and it is suggested to correct the delayed time difference in time. When the fluctuation range of conductivity in the fluctuation data set Bdsj exceeds the conductivity threshold DBY, the fluctuation range of temperature value exceeds the temperature threshold WBY or the fluctuation range of depth value exceeds the depth threshold HBY, it indicates that the attached objects cause the CTD inclination error, and it is suggested to clean the underwater probe in time. When the trust index Kxzs exceeds the trust threshold KXY, it indicates that the authenticity of the measurement results is abnormal, and it is suggested to optimize the measurement scheme. The automatic operation and maintenance support reduces the artificial inspection cost and improves the equipment maintenance efficiency, and is especially suitable for the long-term unattended marine monitoring scene, and has strong practicality. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 The system flowchart of the application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0032] Since the traditional CTD inclination error analysis system needs manual error diagnosis, the calibration intensity is high and the efficiency is low. Since the calibration process involves accurate control of various factors, the entire calibration process is not only complicated but also time-consuming, and it is difficult to meet the actual needs of rapid diagnosis at sea, and the practicability is poor. Therefore, a CTD inclination error analysis system is provided. Please refer to Figure 1 A CTD inclination error analysis system comprises a multi-dimensional acquisition module and an intelligent analysis module.

[0033] The multi-dimensional acquisition module comprises a conductivity measurement unit, a temperature measurement unit and a water depth measurement unit. The conductivity measurement unit collects conductivity data sets of the CTD through network connection. The conductivity data sets comprise conductivity data of the measured water body. The expression of the conductivity data sets is {D1 s , D2 s , D3 s ,..., Dn s}, D1 s to Dns represents the conductivity measured from the first measurement to the nth measurement, and s represents the time point at which the conductivity is obtained;

[0034] The temperature measurement unit collects a temperature data set by connecting the CTD through the network, and the temperature data set includes temperature data of the measured water body, and the expression of the temperature data set is {W1 j , W2 j , W3 j ,..., Wn j}, W1 j to Wn j represent the temperature values measured from the first measurement to the nth measurement, and j represents the time point at which the temperature value is obtained;

[0035] The water depth measurement unit collects a water depth data set by connecting the CTD through the network, and the water depth data set includes water depth data of the measured water body, and the expression of the water depth data set is {H1 m , H2 m , H3 m ,..., Hn m}, H1 m to Hn m represent the depth values measured from the first measurement to the nth measurement, and m represents the time point at which the depth value is obtained, ensuring the time series integrity and traceability of multi-dimensional data, avoiding errors that may be introduced by traditional manual recording, and improving data collection efficiency;

[0036] The intelligent analysis module is composed of a time difference analysis unit, a fluctuation analysis unit, a measurement analysis unit and an error management unit. The time difference analysis unit analyzes the time difference between different physical parameters according to the conductivity data set, the temperature data set and the water depth data set, and generates a corresponding time difference data group Scsj, and the calculation process is as follows:

[0037] According to the conductivity data set, the temperature data set and the water depth data set, the conductivity, the temperature value and the depth value measured at the ith time are extracted, and the time point at which the conductivity is obtained at the ith time is marked as i s , the time point at which the temperature value is obtained at the ith time is marked as i j , and the time point at which the depth value is obtained at the ith time is marked as i m ;

[0038]

[0039] In the formula, represents the time difference between the conductivity and the temperature value obtained in each measurement process, represents the time difference between the conductivity and the depth value obtained in each measurement process, The time difference of obtaining the depth value and the temperature value in each measurement process is calculated in sequence, which helps to eliminate systematic errors caused by different sensor timing.

[0040] The fluctuation analysis unit analyzes the fluctuation range of different physical parameters according to the conductivity data set, the temperature data set and the water depth data set, and generates the corresponding fluctuation data set Bdsj, and the calculation process is as follows:

[0041]

[0042] In the formula, represents the average conductivity of the measured water body, represents the average temperature value of the measured water body, represents the average depth value of the measured water body, Dk s represents the conductivity measured in the kth measurement, Wk j represents the temperature value measured in the kth measurement, Hk m represents the depth value measured in the kth measurement, represents the fluctuation range of the conductivity calculated according to the standard deviation formula, represents the fluctuation range of the temperature value calculated according to the standard deviation formula, represents the fluctuation range of the depth value calculated according to the standard deviation formula, which can quickly locate the measurement deviation caused by biological attachment or mechanical failure;

[0043] The measurement analysis unit analyzes the authenticity of each measurement result according to the conductivity data set, the temperature data set and the water depth data set, and generates the corresponding credibility index Kxzs, and the calculation process is as follows:

[0044]

[0045] In the formula, BD represents the standard value for measuring conductivity, β1 represents the weight of the ratio of the standard value to the conductivity, BW represents the standard value for measuring temperature value, β2 represents the weight of the ratio of the standard value to the temperature value, BH represents the standard value for measuring depth value, β3 represents the weight of the ratio of the standard value to the depth value, β1, β2 and β3 are constants, and β1+β2+β3=1, represents the credibility index Kxzs of the kth measurement result calculated according to the weights β1, β2 and β3 k , which can dynamically evaluate the credibility of single measurement by flexibly adjusting the weight coefficient, and can adapt to the monitoring needs of more complex environments and accurately diagnose error sources;

[0046] The error management unit is provided with a fixed range of time difference threshold SCY, conductivity threshold DBY, temperature threshold WBY, depth threshold HBT and trust threshold KXY, combined with time difference data set Scsj, fluctuation data set Bdsj and trust index Kxzs, to evaluate the influencing factors causing the CTD inclination error and the authenticity of the measurement results. When any value in the time difference data set Scsj exceeds the time difference threshold SCY, it indicates that the response delay causes the CTD inclination error, and it is suggested to correct the delayed time difference in time. When the fluctuation range of conductivity in the fluctuation data set Bdsj exceeds the conductivity threshold DBY, the fluctuation range of temperature value exceeds the temperature threshold WBY, or the fluctuation range of depth value exceeds the depth threshold HBY, it indicates that the attached objects cause the CTD inclination error, and it is suggested to clean the underwater probe in time. When the trust index Kxzs exceeds the trust threshold KXY, it indicates that the authenticity of the measurement results is abnormal, and it is suggested to optimize the measurement scheme. The automatic operation and maintenance support reduces the cost of manual inspection and improves the efficiency of equipment maintenance, and is especially suitable for long-term unattended marine monitoring scenes, and has strong practicality in automatic operation and maintenance support.

[0047] Embodiment 1

[0048] In this experiment, the sea area with a maximum depth of 30 meters is selected as the experimental object, and three measurements are performed on this sea area, with measurement depths of 10 meters, 20 meters and 30 meters. According to statistics, the time point of the first conductivity measurement is 100 seconds, the time point of the first temperature measurement is 105 seconds, the time point of the first depth measurement is 110 seconds, the time point of the second conductivity measurement is 200 seconds, the time point of the second temperature measurement is 202 seconds, the time point of the second depth measurement is 208 seconds, the time point of the third conductivity measurement is 300 seconds, the time point of the third temperature measurement is 303 seconds, and the time point of the third depth measurement is 310 seconds. The calculation process of the time difference data set Scsj of the three measurements is as follows:

[0049]

[0050] In the formula, i s -i j = 100-105 represents the time difference between conductivity and temperature values during the first measurement, i s -i j = 200-202 represents the time difference between conductivity and temperature values during the second measurement, i s -i j = 300-303 represents the time difference between conductivity and temperature values during the third measurement, i s -i m = 100-110 represents the time difference between conductivity and depth values during the first measurement, i s -i m= 200-208 represents the time difference of conductivity and depth values in the second measurement process, i s -i m = 300-310 represents the time difference of conductivity and depth values in the third measurement process, i m -i j = 110-105 represents the time difference of depth and temperature values in the first measurement process, i m -i j = 208-202 represents the time difference of depth and temperature values in the second measurement process, i m -i j = 310-303 represents the time difference of depth and temperature values in the third measurement process, the time difference threshold SCY is set to -1-1 second, and it is judged that each value in the time difference data set Scsj corresponding to the three measurements has exceeded the time difference threshold SCY, indicating that the response delay causes the CTD to be prone to errors, and it is suggested to correct the delay time difference in time.

[0051] Example 2:

[0052] In this experiment, the measurement data of the CTD in June is selected as the experimental data, and the measurement frequency is once a day. According to statistics, on June 12, the conductivity is 1.2 mS / cm, the temperature is 22°C, and the depth is 16 meters. The calculation process of the reliability index Kxzs of the measurement result is as follows:

[0053]

[0054] In the formula, BD = 1.0 mS / cm represents the standard value for measuring conductivity, β1 = 0.5 represents the weight of the ratio of the standard value to the conductivity, BW = 20°C represents the standard value for measuring temperature, β2 = 0.3 represents the weight of the ratio of the standard value to the temperature, BH = 15 meters represents the standard value for measuring depth, and β3 = 0.2 represents the weight of the ratio of the standard value to the depth. β1, β2 and β3 are constants, and 0.5 + 0.3 + 0.2 = 1. According to the weights β1, β2 and β3, the reliability index Kxzs of the measurement result is calculated to be 0.8769. k The reliability threshold KXY is set to 0.5-1.2, and it is judged that the reliability index Kxzs of the measurement result does not exceed the reliability threshold KXY, indicating that the authenticity of the measurement result is not abnormal, and the measurement scheme does not need to be optimized. k

[0055] Although embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made thereto without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.​

Claims

1. An environmental monitoring instrument bias error analysis system, characterized by: The application relates to a multi-dimensional acquisition and intelligent analysis system for ocean environment monitoring. The multi-dimensional acquisition module is composed of an electric conductivity measuring unit, a temperature measuring unit and a water depth measuring unit; the electric conductivity measuring unit is connected with a CTD (conductivity, temperature and depth) through a network to acquire an electric conductivity data set; the temperature measuring unit is connected with the CTD through the network to acquire a temperature data set; and the water depth measuring unit is connected with the CTD through the network to acquire a water depth data set. The intelligent analysis module is composed of a time difference analysis unit, a fluctuation analysis unit, a measurement analysis unit and an error management unit The time difference analysis unit analyzes time difference data groups among physical parameters according to the conductance data set, the temperature data set and the water depth data set The fluctuation analysis unit analyzes fluctuation data groups of physical parameters according to the conductance data set, the temperature data set and the water depth data set The measurement analysis unit analyzes the credibility index of each measurement result according to the conductance data set, the temperature data set and the water depth data set The error management unit is provided with fixed range time difference threshold value Conductance threshold value Temperature threshold value Depth threshold value And credibility threshold value Re-evaluate the influencing factors causing the CTD inclination error and the authenticity of the measurement result, and output the corresponding management suggestion; The time difference data set Any one of the values exceeds the time difference threshold When, indicating that the response delay causes a CTD bias, it is recommended to correct the delay time difference in time; The fluctuation data set When the fluctuation range of the conductivity exceeds the conductivity threshold , the fluctuation range of the temperature value exceeds the temperature threshold , or the fluctuation range of the depth value exceeds the depth threshold , it indicates that the attached matter causes the CTD inclination error, and it is suggested to clean the underwater probe in time. the trust index exceeding the trust threshold in this case, the authenticity of the measurement result is abnormal, and it is recommended to optimize the measurement scheme; The expression of the electrical conductivity data set is , to denotes the electrical conductivity measured for the first time to the time, denotes the point in time at which the electrical conductivity was acquired; The expression of the temperature data set is , to denotes the temperature value measured for the first time to the time, denotes the time point at which the temperature value is acquired; The expression of the water depth dataset is , to represents the depth value measured for the first time to the time, represents the time point of obtaining the depth value; The time difference data set The calculation flow is as follows: According to the conductivity data set, the temperature data set and the water depth data set, the conductivity, the temperature value and the depth value measured at the first time are extracted, and the time point at which the conductivity is acquired at the first time is marked as , the time point at which the temperature value is acquired at the first time is marked as , and the time point at which the depth value is acquired at the first time is marked as . ;​​​ ； In the formula, denotes the time difference at which the conductivity and temperature values are acquired during each measurement process, calculated sequentially, denotes the time difference at which the conductivity and depth values are acquired during each measurement process, calculated sequentially, denotes the time difference at which the depth and temperature values are acquired during each measurement process, calculated sequentially.

2. A system for analyzing bias errors of an environmental monitoring instrument according to claim 1, characterized in that: The fluctuation data set The calculation proceeds as follows: ； ； ； ； in the formula, represents the average conductivity of the water body measured, represents the average temperature value of the water body measured, represents the average depth value of the water body measured, represents the conductivity measured at the time, represents the temperature value measured at the time, represents the depth value measured at the time, represents the fluctuation range of the conductivity calculated according to the standard deviation formula, represents the fluctuation range of the temperature value calculated according to the standard deviation formula, represents the fluctuation range of the depth value calculated according to the standard deviation formula.

3. A system for analyzing the bias of an environmental monitoring instrument according to claim 2, wherein: The trust index The calculation flow is as follows: ； In the formula, This represents the standard value used to measure electrical conductivity. This indicates the weighting of the ratio of the standard value to the conductivity. This represents the standard value used to measure temperature. This indicates the weighting of the ratio of the standard value to the temperature value. This represents the standard value used to measure depth. This indicates the weighting of the ratio of the standard value to the depth value. , and All are constants, and , Indicates according to , and Weights, calculated to obtain the first Reliability index of the measurement results .

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