Multi-parameter measuring instrument for underwater mobile platform and adaptive data processing method

Abstract

The invention discloses a multi-parameter measuring instrument for an underwater mobile platform and a self-adaptive data processing method, and relates to the field of underwater observation. The measuring instrument comprises a temperature-salinity-depth measuring instrument, a dissolved oxygen sensor and a water pump; the temperature-salinity-depth measuring instrument is fixedly connected with the dissolved oxygen sensor; a fixing piece is arranged on the dissolved oxygen sensor and is fixedly connected with the water pump; a controller is arranged in the temperature-salinity-depth measuring instrument and is used for setting a working mode of the multi-parameter measuring instrument for the underwater mobile platform, sending a control instruction to the temperature-salinity-depth measuring instrument, the dissolved oxygen sensor and the water pump according to the working mode, and receiving sensor data of the temperature-salinity-depth measuring instrument and the dissolved oxygen sensor; and processing the sensor data by adopting a self-adaptive data processing algorithm, directly outputting high-quality observation data, and sending the high-quality observation data to the underwater mobile platform. The method is not limited by the installation position of the sensor and the time constant, and high-quality observation data are directly output.

Description

Technical Field

[0001] The present application relates to the field of underwater observation, and in particular to a multi-parameter measuring instrument for an underwater mobile platform and an adaptive data processing method. Background Art

[0002] Temperature, salinity, and dissolved oxygen content are key environmental parameters in marine ecosystems. Their changes directly or indirectly affect the survival, growth, and reproduction of marine organisms, as well as the structure and function of ecosystems. Therefore, long-term, large-scale observations of changes in ocean temperature, salinity, and dissolved oxygen content can provide a solid scientific basis for marine ecological protection, helping to safeguard the health and stability of marine ecosystems and achieve the sustainable use of marine resources.

[0003] Small mobile observation platforms, such as underwater gliders, offer long flight times, wide cruising ranges, low costs, ease of operation, and a high degree of intelligence. Equipped with diverse sensors, they can efficiently complete a variety of marine environmental detection and information collection tasks. They are widely used in fields such as marine field observation, scientific research, and environmental protection, playing a vital role in global ocean observation and exploration systems. However, existing multi-parameter instruments for measuring temperature, salinity, depth, and dissolved oxygen are bulky, heavy, and lack a streamlined design. Their structural layout makes them difficult to integrate directly into the cabin of an underwater glider, failing to meet the requirements for compactness, lightness, and low flow resistance.

[0004] Existing temperature, salinity, depth, and dissolved oxygen multi-parameter measuring instruments are restricted by various factors, and the quality of the directly output observation data is poor, which is specifically reflected in the following points: (1) The sensor itself has different response times. Especially in rapidly changing environments such as thermohaline cline, the temperature and conductivity responses are not synchronized, resulting in deviations in salinity calculations. The dissolved oxygen sensor responds even more slowly and is difficult to accurately reflect instantaneous changes.

[0005] (2) Real-time observation data is usually not filtered and anomalies are not eliminated. It is easily affected by electrical noise, communication interference, bubbles or biological attachment, resulting in jumps, drift or distortion. In particular, the accuracy of dissolved oxygen data depends on temperature and salinity parameters. If there are errors in temperature and salinity data, the deviation of oxygen concentration calculation will be further amplified.

[0006] (3) The movement, attitude change or hydrodynamic disturbance of the underwater mobile platform itself will affect the flow conditions of the sensor, especially on mobile platforms such as AUV, which is more likely to cause unstable readings.

[0007] In summary, even if existing sensors have good performance, the real-time output data is still difficult to directly meet the quality standards of ocean observation and monitoring.

[0008] Currently, the quality of observation data is mainly improved through data post-processing. However, with the increasing complexity of observation tasks and the increasing demand for real-time performance, its drawbacks are becoming increasingly prominent, as shown in the following points: (1) Observational data usually need to be uniformly extracted and analyzed after the completion of a stage mission. This makes it impossible to immediately identify and track rapidly changing ocean phenomena (such as frontal movement, red tide outbreaks, and internal wave propagation), and often misses the recording and research windows of key processes.

[0009] (2) Data quality issues are difficult to detect in time during the observation process, such as sensor drift, abnormal readings, equipment failure, etc., which are often exposed in the post-processing stage of the data and cannot be corrected. In serious cases, the entire data segment may be scrapped or the observation target may not be achieved, resulting in a waste of resources.

[0010] (3) The data post-processing model makes it difficult to dynamically adjust the sampling path, frequency, or area of interest based on the observed data, which can easily lead to problems such as target offset and insufficient data coverage. In the application of underwater mobile platforms such as AUVs and gliders, the data post-processing model cannot support the platform's autonomous judgment and intelligent decision-making, limiting the task adaptability of "observing and adjusting" and hindering the development of underwater observation systems towards efficient and intelligent development.

[0011] (4) Faced with massive amounts of observation data, the workload of manual quality control, format conversion, data screening and analysis is huge. The labor cost of data analysis is high, the cycle is long and the efficiency is low, which is not conducive to the rapid sharing and application of data.

[0012] In summary, traditional data post-processing methods face many limitations in modern ocean observations and are unable to meet the requirements for real-time, high reliability, and intelligence. They are being replaced by a new generation of intelligent observation systems with real-time processing capabilities and adaptive decision-making capabilities. Summary of the Invention

[0013] The purpose of this application is to provide a multi-parameter measuring instrument and adaptive data processing method for underwater mobile platforms, which has the characteristics of compact structure, light weight, and low flow resistance, can output high-quality observation data in real time, and is convenient for integration and mounting on underwater mobile platforms.

[0014] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a multi-parameter measuring instrument for an underwater mobile platform, comprising: Temperature, salinity and depth measuring instruments, dissolved oxygen sensors and water pumps; The temperature, salinity and depth measuring instrument is fixedly connected to the dissolved oxygen sensor; The dissolved oxygen sensor is provided with a fixing piece, and the fixing piece is fixedly connected to the water pump; The temperature, salinity, and depth measuring instrument is internally provided with a controller for setting the working mode of the multi-parameter measuring instrument for the underwater mobile platform and sending control instructions to the temperature, salinity, and depth measuring instrument, the dissolved oxygen sensor, and the water pump according to the working mode. The controller is also used to receive sensor data from the temperature, salinity, and depth measuring instrument and the dissolved oxygen sensor, and process the sensor data using an adaptive data processing algorithm, directly output high-quality observation data, and send it to the underwater mobile platform; the sensor data includes temperature data, conductivity data, pressure data, dissolved oxygen data, and user-defined salinity and density.

[0015] Optionally, the temperature-salinity-depth measuring instrument specifically comprises: an end cover, a sealing shell, a fixing seat, a front guide cover, a support frame, a rear guide cover, a temperature sensor, a conductivity sensor and a pressure sensor; The end cover and the sealing housing are radially sealed; The end surface between the fixing seat and the end cover is sealed; the fixing seat and the front air guide cover are fixed by two screws; The fixing seat and the support frame are connected by screws; the rear air duct is fixed to the support frame by a fixing clamp; The sealed housing and the watertight connector are sealed with a conical surface; a rear column is provided on the sealed housing; the rear column is radially sealed with a plurality of water pipe interfaces, and the water pipe interfaces are used to connect to the water inlet of the dissolved oxygen sensor and the water outlet of the water pump; A radial seal is used between the probe of the temperature sensor and the fixing seat; two radial seals are used between the conductivity sensor and the fixing seat, and both ends of the conductivity sensor are limited by front and rear guide columns; The end faces between the probe of the pressure sensor and the end cover are sealed, and a pressure interface is provided on the surface of the end cover, and the pressure interface is communicated with the mounting hole of the pressure sensor.

[0016] In a second aspect, the present application provides an adaptive data processing method, which is applied to the above-mentioned multi-parameter measuring instrument for underwater mobile platforms, and the adaptive data processing method includes: Setting the working mode of the multi-parameter measuring instrument for the underwater mobile platform and sending control instructions to the temperature, salinity and depth measuring instrument, dissolved oxygen sensor and water pump according to the working mode; Based on the working mode, sensor data is collected according to the control instruction, and the collected sensor data is filtered to determine the processed sensor data; the sensor data includes temperature data, conductivity data, pressure data and dissolved oxygen data; Based on the processed sensor data, and taking the pressure data collected by the pressure sensor as a benchmark, position correction is performed on the installation position of each sensor in the underwater mobile platform multi-parameter measuring instrument and the measurement lag caused by the time required for water to propagate in the measuring pipeline, thereby synchronizing all sensor data in time; the sensors include a dissolved oxygen sensor, a temperature sensor, and a conductivity sensor; Performing time offset correction on the synchronized sensor data according to the response time of each sensor to determine the corrected sensor data; Based on the corrected sensor data, performing a conductivity cell thermal mass correction on the conductivity data to determine a conductivity correction value; A derivative of the sensor data is calculated based on the conductivity correction value and the corrected sensor data; the derivative includes salinity and density.

[0017] Optionally, based on the working mode, collecting sensor data according to the control instruction specifically includes: The working modes specifically include: automatic measurement mode, fast measurement mode and slow measurement mode; When entering the automatic measurement mode, controlling the underwater mobile platform to perform measurement using a multi-parameter measuring instrument according to a preset sampling frequency, and transmitting sensor data to the underwater mobile platform; When entering the fast measurement mode, controlling the underwater mobile platform to keep the multi-parameter measuring instrument in an activated state, controlling the underwater mobile platform to perform a sampling action using the multi-parameter measuring instrument based on a sampling command in the control instruction, and transmitting sensor data to the underwater mobile platform; When entering the slow measurement mode, the multi-parameter measuring instrument for the underwater mobile platform is controlled to remain in a dormant state. Based on the sampling command in the control instruction, the multi-parameter measuring instrument for the underwater mobile platform is started, a sampling action is performed, and after the sensor data is transmitted to the underwater mobile platform, the multi-parameter measuring instrument for the underwater mobile platform automatically enters a dormant state.

[0018] Optionally, performing time offset correction on the synchronized sensor data according to the response time of each sensor to determine the corrected sensor data, the method further includes: Measuring the time constants of the temperature sensor and the conductivity sensor in a laboratory; determining a time constant of a dissolved oxygen sensor at a current temperature and pressure based on the temperature measured by the temperature sensor and the pressure measured by the pressure sensor; The response time required for the water pump to run before the dissolved oxygen sensor takes measurements is determined based on the time constant of the dissolved oxygen sensor at the current temperature and pressure.

[0019] Optionally, determining a time constant of a dissolved oxygen sensor at a current temperature and pressure based on the temperature measured by the temperature sensor and the pressure measured by the pressure sensor specifically includes: determining a temperature coefficient according to the temperature measured by the temperature sensor; determining a pressure coefficient based on the pressure measured by the pressure sensor; The time constant of the dissolved oxygen sensor at the current temperature and pressure is determined according to the temperature coefficient and the pressure coefficient.

[0020] Optionally, determining the temperature coefficient according to the temperature measured by the temperature sensor specifically includes: use , determine the temperature coefficient; where, ft is the temperature coefficient, A 、 B 、 C are the calibration coefficients of dissolved oxygen sensors. T The real-time temperature measured by the temperature sensor.

[0021] Optionally, determining the pressure coefficient according to the pressure measured by the pressure sensor specifically includes: use , determine the pressure coefficient; where, fp is the pressure coefficient; pcor is the calibration coefficient of the conductivity sensor; P is the real-time pressure measured by the pressure sensor.

[0022] Optionally, determining a time constant of a dissolved oxygen sensor at a current temperature and pressure according to the temperature coefficient and the pressure coefficient specifically includes: use , determine the time constant of the dissolved oxygen sensor at the current temperature and pressure; where, tau is the time constant of the dissolved oxygen sensor at the current temperature and pressure; OxTau 20 is the time constant of the dissolved oxygen sensor at 20℃ and in air, ft is the temperature coefficient, fp is the pressure coefficient.

[0023] Optionally, based on the corrected sensor data, performing a conductivity cell thermal mass correction on the conductivity data to determine a conductivity correction value, specifically comprising: use Conduct the conductivity data with conductivity cell thermal mass correction to determine the conductivity correction value; The sampling number is n Conductivity correction value at ; The sampling number is n Conductivity correction value at -1; ris the relationship between conductivity and temperature; T ( n ) is the corrected temperature data when the sampling number is n; T ( n -1) is the sampling number n Corrected temperature data at -1 o'clock; M is the calculated value related to the thermal mass correction parameter; N is a calculated value related to the sampling frequency.

[0024] According to the specific embodiments provided in this application, this application has the following technical effects: The multi-parameter measuring instrument for underwater mobile platforms provided by this application can integrate multiple different types of sensors, with a reasonable and compact structural layout, making it easy to directly install inside the wet cabin of underwater mobile platforms such as underwater gliders, meeting the requirements of compact structure, light weight, and low flow resistance. In addition, this application sets a controller in the multi-parameter measuring instrument for underwater mobile platforms, which is recorded with an adaptive data processing algorithm to filter the sensor data collected by the temperature sensor, conductivity sensor, dissolved oxygen sensor, and pressure sensor, and correct the position of each sensor based on the pressure data to eliminate the position lag caused by the sensor installation position and the time required for water to propagate in the measurement pipeline. It also matches the time constant of each sensor data to eliminate spikes caused by data misalignment in areas with steep temperature gradients. Finally, the conductivity data quality is improved through thermal mass correction of the conductivity cell, and derivative calculations are performed. Through the above series of data processing, this application makes the data no longer restricted by the sensor installation position and time constant, so that high-quality observation data can be directly output to meet the application requirements of real-time monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0026] Figure 1 A schematic diagram of a multi-parameter measuring instrument for an underwater mobile platform provided in one embodiment of the present application; Figure 2 A schematic diagram of an integrated model of a temperature, salinity and depth measuring instrument provided in one embodiment of the present application; Figure 3 A schematic diagram of a circuit board installation provided in one embodiment of the present application; Figure 4 This is a left view of a temperature, salinity and depth measuring instrument provided in one embodiment of the present application; Figure 5 This is a right view of the temperature, salinity and depth measuring instrument provided in one embodiment of the present application; Figure 6 A schematic diagram of measurement intervals in automatic measurement mode provided in an embodiment of the present application; Figure 7 A schematic diagram of a measurement interval in a fast measurement mode according to an embodiment of the present application; Figure 8 A schematic diagram of a measurement interval in a slow measurement mode according to an embodiment of the present application; Figure 9 A schematic diagram of a salinity measurement peak provided in one embodiment of the present application; Figure 10 Another salinity measurement peak diagram provided in one embodiment of the present application; Figure 11 A flow chart of an adaptive data processing method provided in one embodiment of the present application; Figure 12 A schematic diagram of position correction provided in one embodiment of the present application.

[0027] Figure numerals: temperature, salinity and depth measuring instrument 1, dissolved oxygen sensor 2, water pump 3, fixing part 4, watertight connector 5, first gasket 6, first throat hoop 7, second gasket 8, second throat hoop 9, power supply and communication watertight connector 10, first water pump water-tight connector 11, second water pump water-tight connector 12, first dissolved oxygen water-tight connector 13, second dissolved oxygen water-tight connector 14, end cover 1-1, sealing shell 1-2, fixing base 1-3, front air deflector 1-4, supporting frame 1-5, rear air deflector 1-6, temperature sensor 1-7, conductivity sensor 1-8, pressure sensor 1-9, fixing clamp 1-10, first water pipe interface 1-11, second water pipe interface 1-12, protective column 1-13, anti-fouling plug 1-14, circuit board 1-15, acquisition circuit board 1-16, conductivity circuit board 1-17, control circuit board 1-18, first circuit board bracket 1-19, second circuit board bracket 1-20. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0029] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0030] The embodiment of the present application provides a multi-parameter measuring instrument for an underwater mobile platform, such as Figure 1 As shown, it includes: a temperature-salinity-depth measuring instrument 1, a dissolved oxygen sensor 2 and a water pump 3; The temperature-salinity-depth measuring instrument 1 is fixedly connected to the dissolved oxygen sensor 2; a fixing member 4 is provided on the dissolved oxygen sensor 2, and the fixing member 4 is fixedly connected to the water pump 3; A controller is provided inside the temperature, salinity and depth measuring instrument 1 for setting the working mode of the multi-parameter measuring instrument for the underwater mobile platform and sending control instructions to the temperature, salinity and depth measuring instrument 1, the dissolved oxygen sensor 2 and the water pump 3 according to the working mode. The controller is also used to receive sensor data from the temperature, salinity and depth measuring instrument 1 and the dissolved oxygen sensor 2, and process the sensor data using an adaptive data processing algorithm, directly output high-quality observation data, and send it to the underwater mobile platform; the sensor data includes temperature data, conductivity data, pressure data, dissolved oxygen data and user-defined derivative data.

[0031] In an exemplary embodiment, Figure 2 As shown, the temperature-salinity-depth measuring instrument specifically includes: an end cover 1-1, a sealing shell 1-2, a fixing seat 1-3, a front air guide 1-4, a support frame 1-5, a rear air guide 1-6, a temperature sensor 1-7, a conductivity sensor 1-8 and a pressure sensor 1-9; Among them, a radial seal is selected between the end cover 1-1 and the sealing housing 1-2, and is fixed by two M4 screws.

[0032] The end faces of the fixing base 1-3 and the end cover 1-1 are sealed and fixed by four screws; the fixing base 1-3 and the front air guide cover 1-4 are fixed by two M3 screws; The fixing seat 1-3 is connected to the support frame 1-5 by screws; the rear air duct 1-6 is fixed to the support frame 1-5 by a fixing clamp 1-10; The sealed housing 1-2 and the watertight connector 5 utilize a conical seal. A rear column is provided on the sealed housing 1-2. The rear column is radially sealed against multiple water pipe connections. These connections are used to connect to the water inlet of the dissolved oxygen sensor 2 and the water outlet of the water pump 3, and to discharge water through the rear column. In this embodiment, the water pipe connections include two: a first water pipe connection 1-11 and a second water pipe connection 1-12. A radial seal is employed between the rear column and the two water pipe connections.

[0033] A radial seal is used between the temperature sensor 1-7 and the fixing seat 1-3; two radial seals are used between the conductivity sensor 1-8 and the fixing seat 1-3, and both ends of the conductivity sensor 1-8 are limited by the front and rear guide columns; the protective column 1-13 is fixed to the front and rear guide columns with two M3 screws to reduce collisions with the conductivity cell.

[0034] The probe of pressure sensor 1-9 is sealed against the end cap 1-1. A pressure port is provided on the surface of end cap 1-1. This port communicates with the mounting hole of pressure sensor 1-9 and is used to connect to a pressure connector for calibration and testing of pressure sensor 1-9. The pressure port is sealed against the end face, and the mounting thread pitch is M10. The threads have been verified to meet technical specifications.

[0035] More specifically, in order to reduce the resistance and bubbles of the measuring water mass in the pipeline and improve the quality of the measurement data, it is necessary to rationally design the layout of the temperature-salinity-depth measuring instrument 1, the dissolved oxygen sensor 2, and the water pump 3 so that the measuring pipeline length is the shortest and the resistance is the smallest. Figure 1 A first spacer 6 is placed between the temperature-salinity-depth measuring instrument 1 and the dissolved oxygen sensor 2, and the two are fixed together by a first hose clamp 7. The fixing member 4 is fixed to the dissolved oxygen sensor 2 with four jackscrews. A second spacer 8 is placed between the water pump 3 and the fixing member 4, and the two are fixed together by a second hose clamp 9. The pipe joints of the temperature-salinity-depth measuring instrument 1, the dissolved oxygen sensor 2, and the water pump 3 are all connected by PVC transparent hoses.

[0036] In actual application, the water first passes through the temperature sensors 1-7, flows through the conductivity sensors 1-8 and the dissolved oxygen sensor 2, and is then discharged through the water pump 3.

[0037] The multi-parameter measuring instrument for underwater mobile platforms has a low flow resistance shape and an independent watertight cabin. The maximum pressure resistance can cover the entire sea depth and can be directly installed in the non-watertight cabin of the underwater glider, making it easy to integrate and carry on the underwater mobile platform.

[0038] The material of the above-mentioned sealing shell 1-2, end cover 1-1, fixing base 1-3, temperature sensor 1-7 and protective column 1-13 are all TC4, and the other parts are made of high-quality polyoxymethylene.

[0039] Specifically, the front fairing 1-4 is further provided with an anti-fouling plug 1-14. The anti-fouling plug 1-14 is a slow-release anti-fouling plug that can inhibit the approach and attachment of marine organisms by slowly releasing certain substances, thereby reducing the frequency of instrument cleaning and maintenance and increasing the service life of the equipment.

[0040] In an exemplary embodiment, the temperature-salinity-depth measuring instrument further includes: a circuit board 1-15; the circuit board 1-15 is arranged inside the sealed housing 1-2, and the circuit board 1-15 is fixed by a circuit board bracket.

[0041] In an exemplary embodiment, Figure 3 As shown, the circuit board 1-15 specifically includes an acquisition circuit board 1-16, a conductivity circuit board 1-17 and a control circuit board 1-18; the acquisition circuit board 1-16 is fixed to the control circuit board 1-18 by means of a spacer and screws and nuts; the circuit board bracket includes a first circuit board bracket 1-19 and a second circuit board bracket 1-20 that are relatively arranged; the conductivity circuit board 1-17 and the control circuit board 1-18 are connected by a connector and are fixed to the first circuit board bracket 1-19 and the second circuit board bracket 1-20 by screws.

[0042] In an exemplary embodiment, the first circuit board bracket 1 - 19 is fixed to the end cover 1 - 1 by screws.

[0043] In actual application, in order to facilitate the installation of the circuit board 1-15, a special circuit board bracket is designed to fix and support the circuit board 1-15, such as Figure 3 As shown, the acquisition circuit board 1-16 is fixed to the control circuit board 1-18 by four circuit board spacers and four M2 screws and nuts. The control circuit board 1-18 is connected to the conductivity circuit board 1-17 through a connector and is fixed by the first circuit board bracket 1-19 and the second circuit board bracket 1-20 with 8 M3 screws. The first circuit board bracket 1-19 is fixed to the end cover 1-1 by two M3 screws.

[0044] In an exemplary embodiment, Figure 4 and Figure 5 As shown, the sealed housing 1-2 is provided with a plurality of watertight connectors.

[0045] The watertight connector includes a power supply and communication watertight connector 10, a water pump water-tight connector and a dissolved oxygen water-tight connector; the water pump water-tight connector includes a first water pump water-tight connector 11 and a second water pump water-tight connector 12, and the dissolved oxygen water-tight connector includes a first dissolved oxygen water-tight connector 13 and a second dissolved oxygen water-tight connector 14.

[0046] The power supply and communication watertight connector 10 is connected to the underwater mobile platform through a watertight cable, and is used to power the temperature, salinity and depth measuring instrument 1, send control instructions and transmit measured sensor data; the water pump water-tight connector is used to adjust the power supply voltage of the water pump 3 through a watertight cable to control the flow of the water pump 3; the dissolved oxygen water-tight connector is used to power the dissolved oxygen sensor 2 through a watertight cable and transmit measured sensor data.

[0047] In practice, the second water pump watertight connector 13 is connected to the first water pump watertight connector 12 via a watertight cable, controlling the flow of water pump 3 by varying the motor supply voltage. The second dissolved oxygen watertight connector 15 is connected to the first dissolved oxygen watertight connector 14 via a watertight cable, providing power and enabling the transmission of control commands and measurement data via RS-232. The power supply and communication watertight connector 10 is connected to the underwater mobile platform via a watertight cable, which supplies power to the temperature, salinity, and depth measurement instrument 1 and enables the transmission of control commands and measurement data via RS-232.

[0048] In an exemplary embodiment, the working modes specifically include: automatic measurement mode, fast measurement mode and slow measurement mode; when entering the automatic measurement mode, the underwater mobile platform uses a multi-parameter measuring instrument to measure according to a preset sampling frequency and transmits the sensor data to the underwater mobile platform.

[0049] When entering the fast measurement mode, the underwater mobile platform uses the multi-parameter measuring instrument to keep the startup state. Based on the sampling command in the control instruction, the underwater mobile platform uses the multi-parameter measuring instrument to perform a sampling action and transmit the sensor data to the underwater mobile platform.

[0050] When entering the slow measurement mode, the multi-parameter measuring instrument for the underwater mobile platform remains in a dormant state. Based on the sampling command in the control instruction, the multi-parameter measuring instrument for the underwater mobile platform is started, a sampling action is performed, and after the sensor data is transmitted to the underwater mobile platform, the multi-parameter measuring instrument for the underwater mobile platform automatically enters a dormant state.

[0051] In practical applications, the dissolved oxygen sensor 2 can be selected based on actual observation needs. If the dissolved oxygen sensor 2 is not included, the measurement pipeline length will be shortened. Therefore, the motor power supply voltage of the water pump 3 can be set to 5V to further reduce the power consumption of the measuring instrument. If the dissolved oxygen sensor 2 is required, or the measurement pipeline is long due to installation space limitations on the underwater mobile platform, the motor power supply voltage of the water pump 3 can be set to 6V to ensure the flow rate of the measured water mass and the quality of the instrument's observation data.

[0052] Automatic measurement mode: According to the preset sampling interval, the instrument automatically performs the measurement action and sends out the real-time data.

[0053] After setting to automatic measurement mode, the instrument automatically performs measurement and data transmission according to the preset sampling frequency (0.2~4Hz adjustable). Figure 6 shown.

[0054] To set the instrument to work in automatic sampling mode, follow the steps below to set it up.

[0055] Set the instrument sampling frequency ($setfre).

[0056] Set the instrument to automatic measurement mode ($setmode 1).

[0057] Fast measurement mode: Keep the measurement circuit, water pump 3, etc. turned on. According to the sampling command, the instrument performs a sampling action and sends out the data.

[0058] After setting to fast measurement mode, the instrument can receive measurement instructions ($takesample) in a short time interval (up to 250ms) to complete a measurement and data transmission. Figure 7 shown.

[0059] Set the instrument to fast measurement mode ($setmode 2).

[0060] Slow measurement mode: With low power consumption capability, the instrument wakes up according to the sampling command, turns on the measurement circuit, water pump 3, etc., performs a sampling action, sends the data, and then automatically enters the sleep state.

[0061] After setting to slow measurement mode, the instrument is in standby state for a long time, which can significantly save power consumption. It receives measurement instructions ($takesample) at a longer time interval (the fastest is 4s) to complete a measurement and data transmission. Figure 8 shown.

[0062] Set the instrument to slow measurement mode ($setmode 3).

[0063] The underwater mobile platform's multi-parameter measuring instrument has three operating modes to meet diverse observation needs. Users can adjust the power supply voltage of the water pump 3 according to their needs and set the low-power operating mode to maximize the underwater mobile platform's endurance.

[0064] To achieve rapid data processing and provide high-quality observation data in real time, the multi-parameter measuring instrument for an underwater mobile platform provided in this application integrates an adaptive data processing algorithm. It can perform position correction and time constant matching for temperature sensors 1-7, conductivity sensors 1-8, and dissolved oxygen sensor 2, perform thermal mass correction for the conductivity cell, perform filtering processing, calculate derivative quantities, and directly output high-quality observation data to meet the application requirements of real-time monitoring.

[0065] During the high-speed sampling measurement of the multi-parameter measuring instrument, due to the different installation positions, time constants and sampling times of the temperature and conductivity probes, the inconsistent changes in temperature and conductivity during salinity calculation will cause spikes in salinity data, such as Figure 9 and Figure 10 As shown, where T represents temperature, C represents conductivity, and S represents salinity.

[0066] During data processing, the measurement time differences between sensors can be calculated based on the constant pump speed, pipeline structure, and sensor time constant. These differences are primarily caused by the installation position and sensor response time. This application eliminates measurement asynchrony caused by sensor installation position through position correction and eliminates measurement asynchrony caused by different sensor response times through time constant matching.

[0067] Based on the pressure data, the measurement time of each sensor is advanced accordingly to synchronize it with the correct pressure data, thus completing the "lag calibration" and significantly improving the quality of the observation data.

[0068] Based on the above mentioned multi-parameter measuring instrument for underwater mobile platform, such as Figure 11 As shown, the present application provides an adaptive data processing method, comprising: S101: Setting the working mode of the multi-parameter measuring instrument for the underwater mobile platform, and sending control instructions to the temperature-salinity-depth measuring instrument, the dissolved oxygen sensor, and the water pump according to the working mode.

[0069] S102: Based on the working mode, sensor data is collected according to the control instruction, and the collected sensor data is filtered to determine processed sensor data; the sensor data includes temperature data, conductivity data, pressure data and dissolved oxygen data.

[0070] S103: Based on the processed sensor data and taking the pressure data collected by the pressure sensor as a benchmark, position correction is performed on the installation position of each sensor in the multi-parameter measuring instrument for the underwater mobile platform and the measurement lag caused by the time required for water to propagate in the measuring pipeline, and all sensor data are synchronized in time; each sensor includes a dissolved oxygen sensor, a temperature sensor, and a conductivity sensor.

[0071] S104: Performing time offset correction on the synchronized sensor data according to the response time of each sensor to determine corrected sensor data.

[0072] S105: Based on the corrected sensor data, perform conductivity cell thermal mass correction on the conductivity data to determine a conductivity correction value.

[0073] S106: Calculating derived quantities of the sensor data according to the conductivity correction value and the corrected sensor data; the derived quantities include salinity, density, etc.

[0074] The above steps 101 to 106 can be divided into five stages of the adaptive data processing method provided by the present application: low-pass filtering, position correction, time constant matching, conductivity cell thermal mass correction, and derivative quantity calculation.

[0075] Low-pass filtering specifically applies low-pass filtering to temperature, conductivity, pressure, and dissolved oxygen data. Low-pass filtering suppresses high-frequency noise, making subtle, low-frequency variations in the pressure signal (such as slow changes in water depth) clearer, thereby improving the effective resolution of the data. Temperature, conductivity, and dissolved oxygen sensors are susceptible to turbulence, bubbles, or instrument vibration, generating high-frequency noise. Low-pass filtering removes these unrealistic, rapid fluctuations, smoothing out high-frequency fluctuations and preserving true physical changes.

[0076] Position correction specifically includes: Position correction eliminates measurement lag caused by the sensor's mounting position and the time required for water to travel through the measurement line. When the data is aligned, the derived parameters are calculated from measurements taken from the same water body. This eliminates spikes caused by misaligned data in areas with steep temperature gradients.

[0077] like Figure 12 As shown, time 1 is when water begins to flow into the temperature-salinity-depth meter, i.e., time t1 when the pressure sensor and temperature sensor begin measuring. Time 2 is when water begins to enter the conductivity sensor, i.e., time t2. Time 3 is when water flows out of the conductivity sensor, i.e., time t3 when the conductivity sensor begins measuring. Time 4 is when water flows into the dissolved oxygen sensor, i.e., time t4. Time 5 is when water flows out of the dissolved oxygen sensor, i.e., time t5 when the dissolved oxygen sensor begins measuring. The time intervals for time 1 and time 2 are calculated by dividing the length of the pipe from the temperature-salinity-depth meter inlet to the conductivity sensor inlet, L1, by the pump speed, Vb. The remaining calculations are similar.

[0078] Based on the pressure data, time offset correction is performed. Since the temperature sensor is installed at the water inlet, the time offset is 0, the conductivity time offset is t3-t1, and the dissolved oxygen time offset is t5-t1. The measured data are appropriately shifted on the time axis to make them as synchronized as possible with the pressure data in time.

[0079] The time constant matching specifically includes: performing time offset correction on the conductivity, temperature, and dissolved oxygen data according to the response time of the conductivity sensor, temperature sensor, and dissolved oxygen sensor.

[0080] 1) Determine the sensor response time: The time constants of temperature and conductivity are obtained through laboratory measurements. The response time of the temperature sensor used in underwater mobile platforms is generally 200ms, and the response time of the conductivity sensor is 60ms to 70ms.

[0081] The response time of the dissolved oxygen sensor, and the length of time the pump needs to run before taking a measurement, depends on temperature and pressure. The response time of the dissolved oxygen sensor increases with increasing pressure and decreasing temperature. Therefore, the underwater mobile platform uses a multi-parameter measuring instrument to perform preliminary temperature and pressure measurements (but does not store the preliminary values in memory). These values are used to calculate the required pump run time, the pump is operated, and then new measurements of all parameters are taken. This allows for adaptive pump control and time constant calculation and matching.

[0082] The specific process of adaptive water pump control and time constant calculation is as follows: ; Among them, A, B, and C are the calibration coefficients of the dissolved oxygen sensor. pcor is the conductivity sensor calibration coefficient, OxTau 20 is the time constant of the dissolved oxygen sensor at 20°C and air (1 atmosphere), both obtained through laboratory testing; T 、 P The real-time temperature and pressure values measured by the temperature-salinity-depth instrument. tau is the time constant of the dissolved oxygen sensor at the current temperature and pressure values, pt The dissolved oxygen sensor requires the pump to run before taking a measurement. ft To calculate the temperature coefficient required for tau, fp is the pressure coefficient required to calculate tau.

[0083] 2) Time Offset Correction: Conductivity, temperature, and dissolved oxygen data are time-offset corrected based on the sensor's time constant. Using the pressure sensor as a benchmark, the data from other sensors are appropriately shifted on the time axis to align them as closely as possible with the pressure data. For example, if the temperature sensor has a response time of 200ms, the temperature data is shifted forward by 200ms to align more closely with the corresponding pressure data.

[0084] Thermal mass correction for conductivity cells involves the following: Due to the thermal inertia of the conductivity cell material, when the ambient temperature changes, the conductivity cell undergoes a heat exchange process. This can cause the measured conductivity value to differ from the actual value, affecting the accuracy of the measurement results. Therefore, in rapidly changing ocean profile environments, thermal mass correction of the conductivity cell is necessary to improve the quality of the observation data.

[0085] ; in, The sampling number is n Conductivity correction value at ; The sampling number is n Conductivity correction value at -1; r is the relationship between conductivity and temperature; T ( n ) is the sampling number n Corrected temperature data at 1000 ℃; T ( n -1) is the sampling number n Corrected temperature data at -1 o'clock; M is the calculated value related to the thermal mass correction parameter; N is the calculated value related to the sampling frequency; f is the sampling frequency; α and τ are thermal mass correction parameters, representing the error amplitude and time constant caused by thermal mass effects, and are usually measured in the laboratory.

[0086] The calculation of derived quantities specifically includes: using the above data to calculate derived quantities such as salinity and density based on the 1978 International Practical Salt Standard Formula and the 1980 International Standard Seawater State Equation.

[0087] This application integrates an adaptive pump control program and a data processing algorithm, namely an adaptive data processing method, which can perform position correction and time constant matching of temperature, conductivity, and dissolved oxygen sensors, thermal mass correction of conductivity cells, filtering processing, derivative quantity calculation, etc., and directly output high-quality observation data to meet the application needs of real-time monitoring.

[0088] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0089] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A multi-parameter measuring instrument for an underwater mobile platform, characterized in that: The multi-parameter measuring instrument for the underwater mobile platform includes: a temperature, salinity and depth measuring instrument, a dissolved oxygen sensor and a water pump; The temperature, salinity and depth measuring instrument is fixedly connected to the dissolved oxygen sensor; The dissolved oxygen sensor is provided with a fixing piece, and the fixing piece is fixedly connected to the water pump; The temperature, salinity, and depth measuring instrument is internally provided with a controller for setting the operating mode of the multi-parameter measuring instrument for the underwater mobile platform and sending control instructions to the temperature, salinity, and depth measuring instrument, the dissolved oxygen sensor, and the water pump according to the operating mode. The controller is also used to receive sensor data from the temperature, salinity, and depth measuring instrument and the dissolved oxygen sensor, and process the sensor data using an adaptive data processing algorithm, directly output high-quality observation data, and send it to the underwater mobile platform; the sensor data includes temperature data, conductivity data, pressure data, dissolved oxygen data, and user-defined salinity and density.

2. The multi-parameter measuring instrument for underwater mobile platform according to claim 1, characterized in that: The temperature-salinity-depth measuring instrument specifically includes: an end cover, a sealed housing, a fixing seat, a front guide cover, a support frame, a rear guide cover, a temperature sensor, a conductivity sensor, and a pressure sensor; The end cover and the sealing housing are radially sealed; The end surface between the fixing seat and the end cover is sealed; the fixing seat and the front air guide cover are fixed by two screws; The fixing seat and the support frame are connected by screws; the rear air duct is fixed to the support frame by a fixing clamp; The sealed housing and the watertight connector are sealed with a conical surface; a rear column is provided on the sealed housing; the rear column is radially sealed with a plurality of water pipe interfaces, and the water pipe interfaces are used to connect to the water inlet of the dissolved oxygen sensor and the water outlet of the water pump; A radial seal is used between the probe of the temperature sensor and the fixing seat; two radial seals are used between the conductivity sensor and the fixing seat, and both ends of the conductivity sensor are limited by front and rear guide columns; The end faces between the probe of the pressure sensor and the end cover are sealed, and a pressure interface is provided on the surface of the end cover, and the pressure interface is communicated with the mounting hole of the pressure sensor.

3. An adaptive data processing method, characterized in that: The adaptive data processing method is applied to the multi-parameter measuring instrument for an underwater mobile platform according to any one of claims 1 to 2, and the adaptive data processing method includes: Setting the working mode of the multi-parameter measuring instrument for the underwater mobile platform and sending control instructions to the temperature, salinity and depth measuring instrument, dissolved oxygen sensor and water pump according to the working mode; Based on the working mode, sensor data is collected according to the control instruction, and the collected sensor data is filtered to determine the processed sensor data; the sensor data includes temperature data, conductivity data, pressure data and dissolved oxygen data; Based on the processed sensor data, and taking the pressure data collected by the pressure sensor as a benchmark, position correction is performed on the installation position of each sensor in the underwater mobile platform multi-parameter measuring instrument and the measurement lag caused by the time required for water to propagate in the measuring pipeline, thereby synchronizing all sensor data in time; the sensors include a dissolved oxygen sensor, a temperature sensor, and a conductivity sensor; Performing time offset correction on the synchronized sensor data according to the response time of each sensor to determine the corrected sensor data; Based on the corrected sensor data, performing a conductivity cell thermal mass correction on the conductivity data to determine a conductivity correction value; A derivative of the sensor data is calculated based on the conductivity correction value and the corrected sensor data; the derivative includes salinity and density.

4. The adaptive data processing method according to claim 3, characterized in that: Based on the working mode, collecting sensor data according to the control instruction specifically includes: The working modes specifically include: automatic measurement mode, fast measurement mode and slow measurement mode; When entering the automatic measurement mode, controlling the underwater mobile platform to perform measurement using a multi-parameter measuring instrument according to a preset sampling frequency, and transmitting sensor data to the underwater mobile platform; When entering the fast measurement mode, controlling the underwater mobile platform to keep the multi-parameter measuring instrument in an activated state, controlling the underwater mobile platform to perform a sampling action using the multi-parameter measuring instrument based on a sampling command in the control instruction, and transmitting sensor data to the underwater mobile platform; When entering the slow measurement mode, the multi-parameter measuring instrument for the underwater mobile platform is controlled to remain in a dormant state. Based on the sampling command in the control instruction, the multi-parameter measuring instrument for the underwater mobile platform is started, a sampling action is performed, and after the sensor data is transmitted to the underwater mobile platform, the multi-parameter measuring instrument for the underwater mobile platform automatically enters a dormant state.

5. The adaptive data processing method according to claim 3, characterized in that: According to the response time of each sensor, the synchronized sensor data is time-offset corrected to determine the corrected sensor data, which also includes: Measuring the time constants of the temperature sensor and the conductivity sensor in a laboratory; determining a time constant of a dissolved oxygen sensor at a current temperature and pressure based on the temperature measured by the temperature sensor and the pressure measured by the pressure sensor; The response time required for the water pump to run before the dissolved oxygen sensor takes measurements is determined based on the time constant of the dissolved oxygen sensor at the current temperature and pressure.

6. The adaptive data processing method according to claim 5, characterized in that: Determining a time constant of a dissolved oxygen sensor at a current temperature and pressure based on the temperature measured by the temperature sensor and the pressure measured by the pressure sensor specifically includes: determining a temperature coefficient according to the temperature measured by the temperature sensor; determining a pressure coefficient based on the pressure measured by the pressure sensor; The time constant of the dissolved oxygen sensor at the current temperature and pressure is determined according to the temperature coefficient and the pressure coefficient.

7. The adaptive data processing method according to claim 6, characterized in that: Determining a temperature coefficient according to the temperature measured by the temperature sensor specifically includes: use , determine the temperature coefficient; where, ft is the temperature coefficient, A 、 B 、 C are the calibration coefficients of dissolved oxygen sensors. T The real-time temperature measured by the temperature sensor.

8. The adaptive data processing method according to claim 6, characterized in that: Determining a pressure coefficient according to the pressure measured by the pressure sensor specifically includes: use , determine the pressure coefficient; where, fp is the pressure coefficient; pcor is the calibration coefficient of the conductivity sensor; P is the real-time pressure measured by the pressure sensor.

9. The adaptive data processing method according to claim 6, wherein: Determining the time constant of the dissolved oxygen sensor at the current temperature and pressure based on the temperature coefficient and the pressure coefficient includes: use , determine the time constant of the dissolved oxygen sensor at the current temperature and pressure; where, tau is the time constant of the dissolved oxygen sensor at the current temperature and pressure; OxTau 20 is the time constant of the dissolved oxygen sensor at 20℃ and in air, ft is the temperature coefficient, fp is the pressure coefficient.

10. The adaptive data processing method according to claim 3, characterized in that: Based on the corrected sensor data, the conductivity data is corrected for thermal mass of the conductivity cell to determine a conductivity correction value, specifically including: use Conduct the conductivity data with conductivity cell thermal mass correction to determine the conductivity correction value; The sampling number is n Conductivity correction value at ; The sampling number is n Conductivity correction value at -1; r is the relationship between conductivity and temperature; T ( n ) is the sampling number n Corrected temperature data at 1000 ℃; T ( n -1) is the sampling number n Corrected temperature data at -1 o'clock; M is the calculated value related to the thermal mass correction parameter; N is a calculated value related to the sampling frequency.

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