Dual-configuration ISFET intelligent pH sensor and rapid calibration method thereof

Abstract

The invention discloses a double-configuration ISFET intelligent pH sensor and a rapid calibration method thereof, and belongs to the technical field of ocean sensors. The sensor adopts a modular double-configuration shell design, comprises a self-contained integrated structure and a miniature probe type structure, and is provided with components such as multiple watertight packaging, an integrated sensing unit, a low-noise signal processing system, a multi-protocol data interface and the like. The sensor supports dry storage, the pre-operation stabilization time is less than 5 min, the response time is less than or equal to 7 s, and the measurement uncertainty is less than 0.01 pH. According to the calibration method, through a dynamic temperature gradient experiment and a real-time comparison system, rapid calibration of the temperature coefficient and the reference potential is achieved, initial parameters are predicted in combination with a self-learning model, the calibration time is shortened to be 1 / 10 or below of that of a traditional method, and the precision reaches + / -0.002 pH. The problems that an existing sensor is long in pre-balance time, low in response speed, difficult to calibrate, high in maintenance cost and the like are solved, and the sensor is suitable for high-frequency and high-precision pH measurement of the marine environment.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of marine sensors, and particularly relates to a double-configuration ISFET intelligent pH sensor and a rapid calibration method thereof, which is suitable for high-frequency and high-precision determination of pH in surface water in estuary, near sea, ocean and the like. BACKGROUND

[0002] Seawater pH describes the acidity and alkalinity of seawater and is one of the four core parameters of seawater carbonate. As a direct indicator parameter of ocean acidification, pH value occupies a key position in the global ocean observation system and is included in multiple international observation plans such as BGC-Argo, GOA-ON, GOOS and the like. Meanwhile, pH value is one of the core parameters of the domestic marine monitoring specification (GB 17378.4) and the marine investigation specification (GB / T 12763.4).

[0003] Current seawater pH determination methods mainly include a glass electrode method, a spectrophotometry and an electrochemistry method based on an ion-sensitive field effect transistor (ISFET). The glass electrode method is simple in equipment and low in cost, but is prone to drift, low in precision, and needs to be frequently calibrated; the spectrophotometry is high in precision and small in environmental influence, has been widely applied in researches on ocean acidification and conventional marine investigation, is the only method that can be used for calibration of a high-precision seawater pH sensor at present, but needs to use a pump, a valve and the like, is large in power consumption, is not suitable for long-time in-situ observation, and is slow in analysis speed and low in spatio-temporal resolution of data; the electrochemistry method based on ISFET is free of reagents, high in sensitivity, fast in response speed, low in power consumption, can realize a full-solid structure, is large in mechanical strength, and is wide in application range, and is suitable for in-situ determination of seawater pH. However, current pH sensors based on ISFET mostly have long pre-equilibrium time (need weeks), harsh storage conditions (need to be soaked in liquid), long time-consuming and complicated steps in calibration method, high requirements in maintenance and calibration, and poor multi-platform adaptability, and therefore, it is urgent to develop a pH sensor with stable performance, fast response and suitable for multiple observation platforms and a matching calibration method to meet the demand of high-frequency and high-precision pH monitoring of marine environment. SUMMARY

[0004] The application aims to provide a pH sensor with stable performance, fast response, no need for long-time pre-equilibrium and suitable for multiple observation platforms, and develop a matching intelligent calibration method to realize rapid calibration. The scheme is suitable for determination of pH in surface water in complex environments such as estuary, near sea and ocean, can realize continuous measurement with high frequency (maximum 1 Hz) and high precision (uncertainty < 0.01 pH), and provides a reliable technical means for ocean acidification research and water quality monitoring.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions.

[0006] The present invention provides a dual-configuration ISFET intelligent pH sensor, which adopts a self-contained integrated structure or a micro-probe structure. It includes:

[0007] Multiple watertight packaging, including housing, flange and fluororubber radial sealing structure;

[0008] Integrated sensing unit, including ISFET electrode, reference electrode covered with KCl crystal slow-release layer and high-precision temperature probe;

[0009] A low-noise signal processing system, including a FET drive circuit with voltage isolation and an ADC module with integrated digital filter;

[0010] Multi-protocol data interface, six-core watertight plug-in supports RS232 / USB dual-mode communication;

[0011] Self-contained power supply system, equipped with 8 to 24 replaceable lithium battery compartments.

[0012] The microprocessor unit, integrated into the low-noise signal processing system, has a built-in long-term drift calibration module and a dual-scale coupling calculation model for data processing, dynamic compensation, and calibration algorithm execution.

[0013] Furthermore, the ISFET electrode's sensitive film is Ta2O5, and the surface is plasma activated, resulting in a response time of ≤7 s and a measurement uncertainty of <0.01 pH. The surface plasma activation treatment can be performed at a power of 50-200 W in an Ar / O2 atmosphere.

[0014] The sensor supports dry storage and the pre-run stabilization time is less than 5 minutes.

[0015] The microprocessor unit has a built-in long-term drift calibration module, which realizes dynamic compensation adjustment of the long-term drift of the pH sensor according to a preset drift compensation algorithm through real-time analysis of characteristic parameters such as electrode potential drift rate and temperature response consistency; the preset drift compensation algorithm includes a linear or nonlinear regression model based on historical drift data.

[0016] The present invention provides a rapid calibration method for a dual-configuration ISFET intelligent pH sensor, which aims to construct a multi-parameter coupling calibration system under a dynamic environment, including:

[0017] 1) On-site calibration of temperature coefficient k2: Perform a dynamic temperature gradient experiment, use the least squares method to fit the temperature and gate potential curve, and automatically calculate the k2 value;

[0018] 2) Intelligent calibration of the reference potential k0: A real-time comparison system between the calibrator and the pH sensor is established (LabVIEW software can be used). The microprocessor runs an iterative algorithm (such as gradient descent or Newton iteration) to automatically optimize the k0 value until the deviation between the two is less than 0.002 pH.

[0019] 3) Multi-scale automatic conversion and temperature compensation: The microprocessor unit has a built-in dual-scale coupling calculation model to realize the dynamic mutual calculation of the free hydrogen ion scale and the total hydrogen ion scale; the integrated temperature adaptive compensation algorithm realizes the accurate conversion of pH values ​​within the full range of 0-50℃.

[0020] The structure of the dual-scale coupling calculation model is: based on the free hydrogen ion scale pH F pH scale with total hydrogen ions T The conversion formula is combined with the on-site seawater salinity (S) and temperature (T) parameters to achieve mutual calculation through the following formula:

[0021] pH T = pH F +ΔpH (S,T)

[0022] Among them, ΔpH (S,T) is the salinity-temperature correction term, which is derived based on the carbonate system parameter model commonly used in international oceanography (such as the CO2SYS model). The correction term coefficient is optimized by fitting historical observation data with laboratory calibration data.

[0023] The calibrator is based on spectrophotometry, adopts flow sequencing technology, and combines high-purity pH indicators to achieve a calibration accuracy of 0.001 pH.

[0024] The calibration method introduces a self-learning calibration model. A database model is constructed using historical calibration data, and initial calibration parameters are predicted based on historical k0 values ​​and real-time temperature and salinity data for the same sea area.

[0025] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0026] 1. This invention innovatively adopts a dual-configuration design to achieve "one device for multiple uses". The self-contained integrated configuration has a battery life of over one month, and the micro-probe configuration is more than 90% smaller and 80% lighter. It is suitable for different platforms such as buoys, floating vessels, and water quality multi-parameter platforms to meet different monitoring needs.

[0027] 2. The present invention adopts an innovative combination of plasma-activated Ta2O5 sensitive film and KCl slow-release electrode, which can achieve dry storage, facilitate the storage and transportation of the sensor; shorten the pre-equilibrium time and response time, and greatly improve the measurement efficiency;

[0028] 3. The pH sensor of the present invention has a built-in long-term drift calibration module to achieve dynamic compensation adjustment of the long-term drift of the pH sensor, extend the calibration cycle and service life of the sensor, and reduce maintenance costs;

[0029] 4. The present invention develops a rapid calibration method that uses a multi-parameter coupled calibration system combined with a self-learning calibration model to shorten the calibration time from more than 10 hours of traditional methods to within 1 hour, with a calibration accuracy of ±0.002 pH. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a schematic structural diagram of a dual-configuration ISFET intelligent pH sensor according to Example 1 of the present invention;

[0031] Figure 2 Schematic diagram of the process of the rapid calibration method according to embodiment 2 of the present invention;

[0032] Figure 3 The pH cruise test results of the present invention are shown in Example 3.

[0033] Figure 4 The pH fixed-point test results of the present invention are shown in Example 4.

[0034] In the figure, the following are marked: a. Self-contained integrated structure; b. Miniature probe structure; 1. Housing; 2. Flange; 3. O-ring; 4. ISFET electrode; 5. Reference electrode; 6. High-precision temperature probe; 7. FET drive circuit; 8. ADC module; 9. Six-core watertight plug-in; 10. Lithium battery compartment. DETAILED DESCRIPTION

[0035] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer and more understandable, the present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0036] Example 1: Structural implementation of a dual-configuration ISFET intelligent pH sensor

[0037] Figure 1 This is a schematic diagram of the dual-configuration ISFET intelligent pH sensor of the present invention, which adopts a self-contained integrated structure (a) or a micro-probe structure (b). It includes the following components:

[0038] 1. Sensor housing

[0039] Self-contained integrated structure a: Shell 1 is made of polyoxymethylene (POM). Flanges 2 secure the upper and lower ends of shell 1. O-rings 3 are embedded between the flanges to form a radial watertight seal. O-rings 3 seal the gap between shell 1 and flange 2. Shell 1 measures Φ15 cm × 45 cm. Flange 2 is made of 316 stainless steel. O-rings 3 are made of fluoropolymer.

[0040] In a preferred embodiment, the flange 2 and the housing 1 are fastened by threads, and the O-ring 3 is compressed and sealed to ensure watertightness in an underwater environment.

[0041] Miniature probe structure b: Housing 1 is made of 316 stainless steel. An O-ring 3 is used between housing 1 and flange 2. The dimensions are Φ6.4 cm × 21 cm. Flange 2 is made of 316 stainless steel. O-ring 3 is made of fluoropolymer.

[0042] 2. Integrated sensing unit

[0043] ISFET electrode 4: The sensitive film is Ta2O5, and the surface is treated by plasma activation;

[0044] Reference electrode 5: Silver / silver chloride reference electrode covered with a KCl crystal slow-release layer;

[0045] High-precision temperature probe 6: integrated on the ISFET chip, with a measurement accuracy of ±0.1°C.

[0046] The integrated sensing unit (ISFET electrode 4, reference electrode 5, high-precision temperature probe 6) is integrated into the bottom of the housing 1 and directly contacts the seawater.

[0047] 3. Low-noise signal processing system

[0048] FET drive circuit 7: with voltage isolation function to reduce common ground interference;

[0049] ADC module 8: integrated digital filter, sampling frequency 1 Hz, signal-to-noise ratio > 80 dB.

[0050] Microprocessor unit: integrated into the low-noise signal processing system, with built-in long-term drift calibration module, dual-scale coupling calculation model and self-learning calibration model algorithm.

[0051] The low-noise signal processing system (FET drive circuit 7, ADC module 8) is located below the lithium battery compartment 10 and is connected to the top six-core watertight plug-in 9 and the integrated sensor unit below through wiring.

[0052] 4. Multi-protocol data interface

[0053] Six-core watertight plug-in 9: The six-core watertight plug-in 9 is located above the top flange 2, supports RS232 / USB dual-mode communication, and is suitable for various observation platforms.

[0054] 5. Power system

[0055] The middle cavity of the self-contained integrated structure a houses 16 3300 mAh replaceable lithium battery compartments 10, which power the low-noise signal processing system and integrated sensor unit through internal circuits, with a battery life of over one month.

[0056] The micro structure supports external power supply (4.2~18 V) with an average power consumption of 0.72 W.

[0057] 1. Self-contained integrated structure a ( Figure 1 (left image in the figure)

[0058] 1. Sensor housing

[0059] Self-contained integrated structure a: Shell 1 is made of polyoxymethylene (POM). Flanges 2 secure the upper and lower ends of shell 1. O-rings 3 are embedded between the flanges to form a radial watertight seal. O-rings 3 seal the gap between shell 1 and flange 2. Shell 1 measures Φ15 cm × 45 cm. Flange 2 is made of 316 stainless steel. O-rings 3 are made of fluoropolymer.

[0060] In a preferred embodiment, the flange 2 and the housing 1 are fastened by threads, and the O-ring 3 is compressed and sealed to ensure watertightness in an underwater environment.

[0061] 2. Integrated sensing unit

[0062] ISFET electrode 4: The sensitive film is Ta2O5, and the surface is treated by plasma activation;

[0063] Reference electrode 5: Silver / silver chloride reference electrode covered with a KCl crystal slow-release layer;

[0064] High-precision temperature probe 6: integrated on the ISFET chip, with a measurement accuracy of ±0.1°C.

[0065] The integrated sensing unit (ISFET electrode 4, reference electrode 5, high-precision temperature probe 6) is integrated into the bottom of the housing 1 and directly contacts the seawater.

[0066] 3. Low-noise signal processing system

[0067] FET drive circuit 7: with voltage isolation function to reduce common ground interference;

[0068] ADC module 8: integrated digital filter, sampling frequency 1 Hz, signal-to-noise ratio > 80 dB.

[0069] The low-noise signal processing system (FET drive circuit 7, ADC module 8) is located below the lithium battery compartment 10 and is connected to the top six-core watertight plug-in 9 and the integrated sensor unit below through wiring.

[0070] 4. Multi-protocol data interface

[0071] Six-core watertight plug-in 9: Located above the top flange 2, it supports RS232 / USB dual-mode communication and is suitable for various observation platforms. It connects to external devices.

[0072] 5. Power system

[0073] The middle cavity of the self-contained integrated structure a houses 16 3300 mAh replaceable lithium battery compartments 10, which power the low-noise signal processing system and integrated sensor unit through internal circuits, with a battery life of over one month.

[0074] The signal processed by the sensing unit is output through the communication plug-in (six-core watertight plug-in 9).

[0075] Each module is fixed inside the shell by slots or bolts to ensure structural stability.

[0076] 2. Micro probe structure b ( Figure 1 (right image in the figure)

[0077] 1. Sensor housing

[0078] Material: Shell 1 is made of 316 stainless steel, which is resistant to seawater corrosion; flange 2 is made of 316 stainless steel and is fastened to the shell by threads.

[0079] Sealing structure: An O-ring 3 is embedded between the housing 1 and the flange 2 to form a radial watertight seal, meeting the pressure and waterproof requirements for long-term underwater operation. The O-ring 3 is made of fluoropolymer.

[0080] Size: The overall size is Φ6.4 cm × 21 cm, which is more than 90% smaller in volume and about 80% lighter in weight than the self-contained integrated structure.

[0081] 2. Integrated sensing unit

[0082] ISFET electrode 4: The sensitive film is Ta2O5, the surface is treated with plasma activation, the response time is ≤7 s, and the measurement uncertainty is <0.01 pH.

[0083] Reference electrode 5: A silver / silver chloride reference electrode covered with a KCl crystal slow-release layer is used, which supports dry storage (no need to immerse in liquid).

[0084] High-precision temperature probe 6: Integrated on the ISFET chip, with a measurement accuracy of ±0.1°C, providing real-time data for temperature compensation.

[0085] 3. Low-noise signal processing system

[0086] FET drive circuit 7: With voltage isolation function, it effectively reduces common ground interference and ensures signal stability.

[0087] ADC module 8: Integrated digital filter, sampling frequency 1Hz, signal-to-noise ratio >80dB, ensuring data quality under high-frequency measurement.

[0088] 4. Multi-protocol data interface

[0089] Six-core watertight plug-in 9: Located on the top of the micro-probe structure b, it supports RS232 / USB dual-mode communication and is compatible with an external power supply interface, adapting to the communication and power supply needs of small carriers such as buoys and underwater robots.

[0090] 5. Power supply system

[0091] It adopts external power supply mode, supports 4.2~18V wide voltage input, has an average power consumption of 0.72W, and does not require a built-in battery compartment, further reducing the size.

[0092] Example 2: Implementation of the rapid calibration method

[0093] Figure 2 The flowchart of the rapid calibration method of the present invention is as follows:

[0094] 1. Prediction of initial calibration value: Input the longitude and latitude of the monitored sea area, current seawater temperature and salinity in the parameter input interface of the sensor calibration control software based on LabVIEW, match the historical database, and obtain the initial k0 value based on the model prediction.

[0095] 2. On-site calibration of the temperature coefficient k²: The pH sensor is placed in a custom bottle for temperature calibration. This custom bottle is shielded from light and filled with 0.01 mol / L HCl solution. It is then placed in a constant-temperature water bath, controlled between 0 and 50°C. The sensor includes a high-precision temperature probe, which automatically reads the temperature and electrical signal using LabVIEW-based sensor calibration control software. During the experiment, the temperature is continuously increased, and the real-time temperature and potential values ​​are recorded. The temperature and potential curves are fitted using the least-squares method to automatically calculate the k² value.

[0096] 3. Intelligent calibration of the reference potential k0: A real-time comparison system was established between a calibrator (based on spectrophotometry, using flow sequencing technology, combined with high-purity pH indicators, with a calibration accuracy of 0.001 pH) and a pH sensor (implemented using LabVIEW-based sensor calibration control software). The sensor and calibrator sample tubes were simultaneously inserted into a custom-made water bucket (Φ25×40 cm), which was sealed and shielded from light. The bucket was filled with aged seawater from the surface of the South China Sea. The calibrator measured the sample three times at a frequency of 5 minutes per time, and the pH sensor measured the sample at a frequency of 1 Hz for 15 minutes. Based on the initial predicted k0 value, the pH value measured by the sensor was obtained. u The pH value of the sample under the total hydrogen ion scale is obtained according to the measurement results of the calibrator. T The pH value of the sample calibrated with free hydrogen ions at ambient temperature is obtained through the dual-scale calculation model and temperature compensation algorithm. F , compared with the pH measured by the sensor u , the k0 value was optimized by iterative algorithm until the deviation between the two was less than 0.002 pH.

[0097] like Figure 2 As shown, the programming logic of the sensor calibration control software based on LabVIEW described in this embodiment can be referred to as follows:

[0098] 1. Initialization and system configuration

[0099] Hardware detection: Use LabVIEW's VISA module to automatically scan and identify sensors, calibrators, constant temperature water baths, and other devices to establish communication connections.

[0100] Parameter loading: Read historical calibration data (such as sea area location, historical calibration parameters) from the local database and initialize the calibration model.

[0101] Interface generation: Create a user interaction interface, including data input area, control buttons, real-time data display area and status indication area.

[0102] 2. Data Collection and Preprocessing

[0103] User input processing: Obtain and validate environmental parameters (such as temperature and salinity) entered by the user.

[0104] Sensor data acquisition: Synchronously collect sensor potential, temperature and other data at a set frequency (such as 1 Hz).

[0105] Data preprocessing: Filter and denoise the collected data to improve data quality.

[0106] 3. Calibration algorithm implementation

[0107] Initial parameter prediction: Predict initial calibration parameters based on historical data and current environmental conditions.

[0108] Temperature coefficient calibration: Control the water bath to perform a temperature gradient experiment, collect sensor responses at different temperatures, and calculate the temperature coefficient.

[0109] Reference potential optimization: By comparing with the standard value, the reference potential parameters are iteratively optimized until the accuracy requirements are met.

[0110] 4. Control logic and exception handling

[0111] Hardware control: Automatically control water bath temperature, sensor start and stop, and other operations according to the calibration process.

[0112] Scheduled tasks: implement a timed loop for data acquisition, processing, and storage.

[0113] Exception handling: Detect and handle abnormal situations such as communication interruption and data deviation to ensure stable system operation.

[0114] 5. Data storage and report generation

[0115] Database operation: Store the calibration results in the local database for subsequent analysis and traceability.

[0116] Report generation: Automatically generate calibration reports including timestamp, key parameters, calibration curves and result evaluation.

[0117] In this example, LabVIEW was used to implement a real-time comparison system between a calibrator and a pH sensor. Because the calibrator uses spectrophotometry and the pH sensor is an ISFET, data acquisition and comparison between the two must be synchronized. The pH sensor is connected to the computer via RS232 / USB. The calibrator is connected to the computer via its communication interface (such as RS232, USB, or Modbus). The real-time comparison system between the calibrator and the pH sensor consists of two parallel data acquisition threads: one for the pH sensor and one for the calibrator. The pH sensor interprets the data according to its communication protocol (e.g., sending a specific command, the sensor returns a data frame). The calibrator interprets the data according to its communication protocol (e.g., sending a start measurement command, then reading the returned pH value). Because the calibrator's measurement speed is slow (5 minutes / time) and the pH sensor's measurement speed is fast (1 Hz), the average of the pH sensor's measurements near that moment (e.g., the average of the sensor data for the 10 seconds before and after the calibrator's measurement) is simultaneously acquired for comparison.

[0118] Example 3: pH cruise test using the present invention

[0119] On April 29, 2024, the self-contained integrated pH sensor was used to measure the pH value of seawater in Dongshan Bay. According to the rapid calibration method ( Figure 2 The sensor's k0 and k2 values ​​were -292.001 mV and -2.949 mV / °C, respectively. The sensor was then deployed in a 25 cm × 35 cm overflow bucket. During navigation, the surface seawater was pumped by a submersible pump to a distribution pipe on the deck. The seawater in the distribution pipe was then introduced to the bottom of the overflow bucket. When powered on, the sensor automatically measured and stored the pH value of the seawater during navigation. The measurement frequency was 1 Hz. The results are shown in the figure below. Figure 3 As shown in the figure, the pH value shows a significant increasing trend from the inner to the outer bay. The pH sensor captures the pH change trend and degree, which is consistent with previous research (Hangqian Li, Shu Wang, Shulu Zheng, Tengyue Fang, Huilin Shu, Yi Xu, Xianghui Guo, Eric P. Achterberg, Liyang Zhan, Jian Ma*, Underway mapping of coastal seawater pH using an automated shipboard analyzer with spectrophotometric detection, Talanta, 2024, 278, 126532).

[0120] Example 4: pH fixed-point testing using the present invention

[0121] From January 20, 2025, to January 27, 2025, a micro-probe pH sensor according to the present invention was deployed on a buoy in Xiamen Bay. Before deployment, the sensor was calibrated using a rapid calibration method, obtaining k0 and k2 values ​​of -261.942 mV and -2.602 mV / °C, respectively. The sensor was deployed approximately 1 m underwater to avoid interference from surface fluctuations. It was powered by the buoy and measured at a frequency of 1 minute. The results are as follows: Figure 4 As shown in the figure, a total of 10,593 data points were collected. During the long-term fixed-point test, the sensor's built-in long-term drift calibration module continued to operate. When it detected a reference electrode potential drift rate of 1 mV / d and a temperature response deviation, it initiated self-calibration and dynamically compensated the reference electrode potential based on a preset algorithm, calibrating its measured value to at least 98% of the actual pH value, ensuring measurement accuracy.

[0122] The preset algorithm can be as follows:

[0123] E 校准 =E 测定-ΔE(t)

[0124] Among them E 校准 is the voltage after sensor calibration; E 测定 is the voltage actually measured by the sensor; ΔE(t) is the reference electrode potential drift that changes with time t, which can be obtained by fitting historical data with the preset drift rate.

[0125] from Figure 4 It can be seen that the average pH amplitude of the semidiurnal tide in Xiamen Bay is 0.386, and the pH fluctuates, and the changes are related to the tide.

[0126] This invention innovatively utilizes a dual-configuration housing, combining a self-contained integrated design with a micro-probe. The self-contained design offers an endurance of over one month, enabling long-term independent monitoring. The micro-probe is 90% smaller and 80% lighter, making it suitable for small platforms such as buoys and underwater robots. Its modular structure addresses the poor compatibility of traditional sensor platforms, enabling a single device for multiple uses. It utilizes a plasma-activated Ta2O5 sensitive membrane and a KCl crystal slow-release reference electrode, supporting dry storage (without liquid immersion) and simplifying storage and transportation. The pre-run stabilization time is less than 5 minutes (compared to several weeks traditionally required), the response time is ≤7 seconds, and the measurement uncertainty is less than 0.01 pH, significantly improving measurement efficiency and accuracy. This invention integrates a long-term drift calibration module that analyzes parameters such as electrode potential drift and temperature response deviation in real time. Dynamic compensation and adjustment through an algorithm reduces the need for frequent calibration, extends service life, and reduces maintenance costs. An innovative multi-parameter coupled calibration system automatically calculates temperature coefficients during dynamic temperature gradient experiments, uses a real-time comparison system to iteratively optimize reference potentials, and combines this with a self-learning model to predict initial parameters. This reduces calibration time from over 10 hours to under an hour, achieving an accuracy of ±0.002 pH. This eliminates the time-consuming and complex steps of traditional calibration. The low-noise signal system, including voltage isolation circuitry and digital filters, achieves a signal-to-noise ratio of >80 dB. The six-core, waterproof plug-in supports RS232 / USB dual-mode communication, compatible with power and transmission requirements across multiple platforms, ensuring stable and reliable high-frequency measurement data.

[0127] The above is a typical embodiment of the present invention, but the present invention should not be limited to the contents disclosed in this embodiment. Therefore, any equivalent or modification completed without departing from the spirit disclosed in the present invention shall fall within the scope of protection of the present invention.

Claims

1. A dual-configuration ISFET intelligent pH sensor, characterized in that: Modular dual-configuration housing design, adopting self-contained integrated structure or micro-probe structure; including: Multiple watertight packaging, including housing, flange and fluororubber radial sealing structure; Integrated sensing unit, including ISFET electrode, reference electrode covered with KCl crystal slow-release layer and high-precision temperature probe; A low-noise signal processing system, including a FET drive circuit with voltage isolation and an ADC module with integrated digital filter; Multi-protocol data interface, six-core watertight plug-in supports RS232 / USB dual-mode communication; Self-contained power supply system with replaceable lithium battery compartment.

2. A dual-configuration ISFET intelligent pH sensor as claimed in claim 1, characterized in that: The sensitive film of the ISFET electrode is Ta2O5, the surface of which is treated with plasma activation, the response time is ≤7 s, and the measurement uncertainty is <0.01 pH.

3. A dual-configuration ISFET intelligent pH sensor as claimed in claim 1, characterized in that: The sensor supports dry storage and the pre-run stabilization time is less than 5 minutes.

4. A dual-configuration ISFET intelligent pH sensor as claimed in claim 1, characterized in that: The sensor has a built-in long-term drift calibration module, which realizes dynamic compensation adjustment of the long-term drift of the pH sensor through real-time analysis of characteristic parameters such as electrode potential drift rate and temperature response consistency.

5. A rapid calibration method for a dual-configuration ISFET intelligent pH sensor according to any one of claims 1 to 4, characterized in that: Construct a multi-parameter coupling calibration system in a dynamic environment, including: 1) On-site calibration of temperature coefficient k2: Perform a dynamic temperature gradient experiment, use the least squares method to fit the temperature and gate potential curve, and automatically calculate the k2 value; 2) Intelligent calibration of the reference potential k0: A real-time comparison system between the calibrator and the pH sensor is established, and an iterative algorithm is run through the microprocessor to automatically optimize the k0 value until the deviation between the two is less than 0.002 pH. 3) Multi-scale automatic conversion and temperature compensation: The microprocessor unit has a built-in dual-scale coupling calculation model to realize the dynamic mutual calculation of the free hydrogen ion scale and the total hydrogen ion scale; the integrated temperature adaptive compensation algorithm realizes the accurate conversion of pH values ​​within the full range of 0-50℃.

6. A rapid calibration method for a dual-configuration ISFET intelligent pH sensor as claimed in claim 5, characterized in that: The calibrator is based on spectrophotometry, adopts flow sequencing technology, and combines high-purity pH indicators to achieve a calibration accuracy of 0.001 pH.

7. A rapid calibration method for a dual-configuration ISFET intelligent pH sensor as claimed in claim 5, characterized in that: A self-learning calibration model is introduced; a database model is constructed through historical calibration data, and the initial calibration parameters are predicted based on the historical k0 values ​​and real-time temperature and salinity data of the same sea area.

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