Testing system and method for hydrogen sulfide sensor

Abstract

The invention provides a testing system and method for a hydrogen sulfide sensor, and belongs to the technical field of measurement and testing. The method comprises a sensor type identification stage: determining the type of a target sensor based on the measurement principle and the material attribute of the target sensor; a test mode determination stage: based on the identified target sensor type, determining a test mode of the target sensor, the test mode at least comprising a reference test mode and a compensation test mode; a test execution stage: executing a performance test on the target sensor based on the determined test mode; a test result analysis stage: analyzing the performance of the target sensor based on the test result; and a man-machine interaction feedback stage: receiving man-machine interaction feedback data, determining whether to switch the test mode based on the feedback data, if so, returning to the test mode determination stage and reselecting the test mode, and otherwise, ending the test. The technical scheme provided by the invention is suitable for the performance test of various types of hydrogen sulfide sensors, and the test error can be reduced.

Description

Technical Field

[0001] This invention belongs to the field of measurement and testing technology, and relates to testing or analyzing materials by means of measuring their chemical or physical properties, and particularly to a testing system and method for a hydrogen sulfide sensor. Background Technology

[0002] Hydrogen sulfide is widely used in chemical production processes such as papermaking, oil refining, and steelmaking, and is also widely present in environments such as biogas, sewers, oil fields, mines, and natural gas fields. However, hydrogen sulfide is a highly volatile and toxic gas with unstable properties. When mixed with air, it can form an explosive mixture, which can ignite and explode upon contact with open flames or high heat. It poses a significant safety hazard during application, and its concentration must be detected and monitored.

[0003] Known hydrogen sulfide gas sensors are mainly classified into conductivity-based gas sensors and electrochemical sensors based on semiconductor oxides. Depending on the type of electrolyte used, hydrogen sulfide sensors are further categorized into high-temperature solid electrolyte electrochemical sensors, solid polymer electrolyte electrochemical sensors, liquid electrolyte electrochemical sensors, and gel electrolyte electrochemical sensors.

[0004] In practical applications, hydrogen sulfide gas sensors often face problems such as poor selectivity and significant influence from operating temperature and ambient humidity. In some environments, the presence of low concentrations of hydrogen sulfide gas over extended periods can cause a gradual decrease in sensor accuracy, resulting in large deviations in detection results and impacting their effectiveness. Therefore, regular performance testing and calibration of hydrogen sulfide sensors are essential. However, since different types of hydrogen sulfide sensors exist with varying operating principles, their performance testing and calibration methods also differ.

[0005] A search revealed no specific performance testing schemes for hydrogen sulfide sensors. Similar technical solutions include the comprehensive testing method for nitrogen and oxygen sensors proposed in Chinese invention patent application CN202411216483.9, and the comprehensive gas sensor tester proposed in CN201410634410.1. However, none of these methods are directly applicable to hydrogen sulfide sensors, let alone for the performance testing of various types of hydrogen sulfide sensors. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention proposes a testing system and method for a hydrogen sulfide sensor.

[0007] In a first aspect of the invention, a method for testing a hydrogen sulfide sensor is provided, the method comprising:

[0008] Sensor type identification stage: Determine the type of the target sensor based on its measurement principle and material properties;

[0009] Test mode determination stage: Based on the target sensor type identified in the previous stage, the test mode of the target sensor is determined, and the test mode includes at least a benchmark test mode and a compensation test mode.

[0010] Test execution phase: Based on the determined test mode, performance tests are performed on the target sensor;

[0011] Test result analysis phase: Analyze the performance of the target sensor based on the test results;

[0012] Human-computer interaction feedback phase: Receive human-computer interaction feedback data, determine whether to switch test modes based on the feedback data, if yes, return to the test mode determination phase to reselect the test mode, otherwise end the test;

[0013] In the test mode determination stage, each type of target sensor corresponds to at least two different test modes, and the different test modes include different benchmark test modes or compensation test modes.

[0014] In the technical solution of the present invention, the target sensor types to be tested include at least: fuel cell type based on micro fuel cell principle and using true solid electrolyte; impedance type based on semiconductor resistance sensing principle and using metal oxide sensitive membrane; electrochemical type based on constant potential electrolysis principle and using bimetallic catalyst; and photoelectrochemical type based on photoelectric conversion principle and using organic-inorganic composite heterojunction.

[0015] The test modes include a reference test mode selected from one or any combination of factory calibration information retrieval, standard gas verification, catalyst sensitivity calibration, limiting current calibration, identification probe calibration, or photocurrent reference calibration; the test modes include a compensation test mode selected from one or any combination of temperature and humidity correlation compensation, sensitive membrane adsorption characteristic compensation, linear fitting compensation, and signal quenching compensation.

[0016] The standard gas used for calibration is hydrogen sulfide standard gas, and the identification probe calibration uses a metal ion probe.

[0017] The test results include the performance curves and key indicators of the target sensor before and after the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability.

[0018] The test result analysis stage also includes a result visualization sub-stage, which visualizes at least two performance curves corresponding to the test results.

[0019] The human-computer interaction feedback data received during the human-computer interaction feedback phase includes: receiving comparison operations from testers on the at least two performance curves, the comparison operations including translation, zooming in, zooming out, and rotation;

[0020] If at least two performance curves after performing the comparison operation do not meet the preset conditions, the test mode is switched.

[0021] During the test execution phase, core performance data of the target sensor are collected, including zero-point signal, response signal at target concentration, and output signal under environmental influence.

[0022] In a second aspect of the invention, to implement the method described in the first aspect, a testing system for a hydrogen sulfide sensor is proposed. The target sensor types to be tested include at least: fuel cell type based on a micro fuel cell principle and using a true solid electrolyte; impedance type based on a semiconductor resistance sensing principle and using a metal oxide sensitive membrane; electrochemical type based on a constant potential electrolysis principle and using a bimetallic catalyst; and photoelectrochemical type based on a photoelectric conversion principle and using an organic-inorganic composite heterojunction.

[0023] Specifically, the system includes:

[0024] Sensor type identification unit: Determines the type of the target sensor based on its measurement principle and material properties;

[0025] Test mode determination unit: Based on the target sensor type identified by the sensor type identification unit, determines the test mode of the target sensor, wherein the test mode includes at least a benchmark test mode and a compensation test mode;

[0026] Test execution unit: Performs performance tests on the target sensor based on a defined test mode;

[0027] Test Result Analysis Unit: Analyzes the performance of the target sensor based on the test results output by the visualization interface; the test results include the performance curves and key indicators of the target sensor before and after performing the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability;

[0028] Human-computer interaction feedback unit: Receives human-computer interaction feedback data based on the visual interface, determines whether to switch test modes based on the feedback data, if so, returns to the test mode determination unit to reselect the test mode, otherwise ends the test;

[0029] In the test mode determination stage, each type of target sensor corresponds to at least two different test modes, and the different test modes include different benchmark test modes or compensation test modes.

[0030] The human-computer interaction feedback unit receives human-computer interaction feedback data including: receiving comparison operations from testers on at least two performance curves, the comparison operations including translation, zooming in, zooming out, and rotation;

[0031] When at least two performance curves after the comparison operation meet the preset conditions, the target sensor is determined to have passed the performance test.

[0032] The test results output based on the visualization interface include the performance curves and key indicators of the target sensor before and after performing the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability.

[0033] The hydrogen sulfide sensor testing method and system proposed in this invention are highly adaptable to different types of hydrogen sulfide sensors. Based on testing principles and material properties, it can identify multiple types of hydrogen sulfide sensors, including fuel cell type and impedance type sensors. Each type corresponds to at least two testing modes, including reference and compensation modes, solving the problem that existing technologies cannot adapt to multiple types of hydrogen sulfide sensors. Simultaneously, it offers high testing accuracy: combining reference testing (such as standard gas calibration) and compensation testing (such as temperature and humidity compensation) corrects accuracy deviations caused by environmental and material characteristics, improving the problem of sensor accuracy degradation in low-concentration environments. Finally, the entire testing process is interactive and intuitive: supporting visual comparison of test results and interactive operations such as panning and zooming, it allows for flexible switching of test modes based on feedback, ensuring the accuracy of cross-validation of test results.

[0034] Further advantages of the present invention will be further detailed in the Specific Embodiments section in conjunction with the accompanying drawings. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic diagram illustrating different execution stages of a testing method for a hydrogen sulfide sensor according to an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram illustrating the specific execution steps of a testing method for a hydrogen sulfide sensor according to one embodiment;

[0038] Figure 3 This is a schematic diagram of the human-computer interaction and visualization interface operation for implementing the testing method of a hydrogen sulfide sensor described in this invention;

[0039] Figure 4This is a schematic diagram of some functional units of a hydrogen sulfide sensor testing system according to an embodiment of the present invention. Detailed Implementation

[0040] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments identical to those described in this application. Rather, they are merely examples of apparatuses and methods identical to some aspects of this application as detailed in the appended claims.

[0041] In specific embodiments of this application, if user-related data is involved, user permission or consent must be obtained when the embodiments of this application are applied to specific products or technologies, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0042] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0043] First see Figure 1 , Figure 1 This is a schematic diagram illustrating different execution stages of a testing method for a hydrogen sulfide sensor according to an embodiment of the present invention.

[0044] exist Figure 1 The present invention illustrates a testing method for a hydrogen sulfide sensor comprising five stages: sensor type identification stage, test mode determination stage, test execution stage, test result analysis stage, and human-computer interaction feedback stage.

[0045] exist Figure 1 On this basis, Figure 2 Further show Figure 1 A schematic diagram illustrating the specific execution steps of the five stages of the testing method.

[0046] Specifically, in combination Figure 1 and Figure 2 As can be seen, a testing method for a hydrogen sulfide sensor according to an embodiment of the present invention includes:

[0047] Sensor type identification stage: Determine the type of the target sensor based on its measurement principle and material properties;

[0048] Test mode determination stage: Based on the target sensor type identified in the previous stage, the test mode of the target sensor is determined, and the test mode includes at least a benchmark test mode and a compensation test mode.

[0049] Test execution phase: Based on the determined test mode, performance tests are performed on the target sensor;

[0050] Test result analysis phase: Analyze the performance of the target sensor based on the test results;

[0051] Human-computer interaction feedback phase: Receive human-computer interaction feedback data, determine whether to switch test modes based on the feedback data, if yes, return to the test mode determination phase to reselect the test mode, otherwise end the test;

[0052] In the test mode determination stage, each type of target sensor corresponds to at least two different test modes, and the different test modes include different benchmark test modes or compensation test modes.

[0053] Next, we will elaborate on the five stages included in the above method.

[0054] The specific implementation process for each stage will be described with examples of specific parameters (states), sensor principles, and types. However, it is understood that these examples are merely illustrative and not exhaustive, and do not constitute a limitation on the scope of protection of this invention.

[0055] At the same time, it's important to understand that while the various steps and stages are interconnected in practice (i.e., essentially targeting the same scenario / example / type), to enrich the examples and avoid using the same example for every step, the introductory sections will provide an example for each step as much as possible. This means that the example (scenario) for each step may differ (from the example in the preceding / following step), but those skilled in the art will understand that this will not lead to comprehension difficulties or contradictions in the description. In actual implementation, it is only necessary to unify and adjust the relevant examples for all stages and steps.

[0056] I. Sensor Type Identification Stage

[0057] In this identification stage, the classification logic is mainly based on the two dimensions of sensor "measurement principle - material properties": the measurement principle determines the core working mechanism of the sensor, and the material properties determine its performance characteristics (such as anti-interference and temperature and humidity sensitivity). The combination of the two can accurately distinguish different types of sensors and avoid confusion from single-dimensional classification (such as sensors with different sensitive materials based on the same principle cannot be distinguished by the principle alone).

[0058] In this invention, 'material properties' refer to the key material characteristics that determine the core performance of the sensor, specifically including three categories: ① the chemical composition and microstructure of the sensitive membrane (e.g., metal oxide nanostructures, organic-inorganic composite heterojunctions); ② the type of electrolyte (e.g., true solid electrolytes, liquid electrolytes, gel electrolytes); ③ the composition and morphology of the electrodes / catalysts (e.g., bimetallic alloys, nanoparticle catalysts). The identification of material properties requires corresponding characterization methods to ensure that the criteria for distinguishing different types of sensors are quantifiable and verifiable.

[0059] Preferred illustrative examples of sensor type identification include:

[0060] Fuel cell type sensor: Confirm its measurement principle as "micro fuel cell" through the instruction manual or product label, and confirm that the electrolyte is "true solid electrolyte" by disassembly and observation (or manufacturer parameters), and determine it to be a fuel cell type (such as FCO-H2S-100).

[0061] Impedance type sensor: By testing its resistance response characteristics without an external power supply, the principle is confirmed to be "semiconductor resistance sensing". X-ray diffraction (XRD) is used to analyze the sensitive film. If CuO nanocrystal characteristic peaks (2θ=32.4°, 35.5°) are detected, it is determined to be impedance type.

[0062] Electrochemical sensor: Circuit analysis confirms the existence of a constant potential electrolysis circuit (including working electrode and reference electrode). X-ray photoelectron spectroscopy (XPS) is used to detect the electrode material. If it contains Pt-Co bimetallic characteristic peaks (Pt4f7 / 2=71.2eV, Co2p3 / 2=780.5eV), it is determined to be electrochemical.

[0063] Photoelectrochemical sensor: The principle of "photoelectric conversion" was confirmed by photocurrent response test under illumination. The porous structure of poly(5-aldehyde indole) / TiO2 heterojunction was observed by scanning electron microscopy (SEM), and it was determined to be photoelectrochemical.

[0064] Therefore, preferably, the target sensor types to be tested include at least: fuel cell type based on micro fuel cells and using true solid electrolytes; impedance type based on semiconductor resistance sensing and using metal oxide sensitive membranes; electrochemical type based on constant potential electrolysis and using bimetallic catalysts; and photoelectrochemical type based on photoelectric conversion and using organic-inorganic composite heterojunctions.

[0065] This stage lays the foundation for subsequent targeted testing mode matching by accurately distinguishing multiple types of hydrogen sulfide sensors, ensuring that the testing plan matches the core characteristics of the sensor.

[0066] II. Test Mode Determination Phase

[0067] This phase is based on the "type-mode" mapping rule. Each sensor type corresponds to at least two test modes. Each mode consists of "benchmark test (to ensure the test benchmark is consistent) + compensation test (to correct interference factors)". Through the combination of differentiated benchmarks and compensation, it covers the needs of different application scenarios (such as precise laboratory testing and rapid field testing).

[0068] The test modes include a reference test mode selected from one or any combination of factory calibration information retrieval, standard gas verification, catalyst sensitivity calibration, limiting current calibration, identification probe calibration, or photocurrent reference calibration; the test modes include a compensation test mode selected from one or any combination of temperature and humidity correlation compensation, sensitive membrane adsorption characteristic compensation, linear fitting compensation, and signal quenching compensation.

[0069] Preferably, for fuel cell-type tests, the test reference can be factory calibration information retrieval or standard gas calibration, and the test compensation can be temperature and humidity correlation compensation; for impedance-type tests, the test reference can be low-concentration standard gas calibration or baseline calibration, and the test compensation can be sensitive membrane adsorption characteristic compensation; for electrochemical-type tests, the test reference can be catalyst sensitivity calibration or limiting current calibration, and the test compensation can be linear fitting compensation; for photoelectrochemical-type tests, the test reference can be identification probe calibration or photocurrent reference calibration, and the test compensation can be signal quenching compensation.

[0070] Preferably, the standard gas used for standard gas verification is hydrogen sulfide standard gas, and the identification probe calibration uses a metal ion probe.

[0071] Continuing with the previous example, the test mode determination examples for different types of partial hydrogen sulfide sensors are as follows:

[0072] (1) Fuel cell type sensor:

[0073] Mode 1: The benchmark test is "factory QR code recall" (scan the sensor QR code to read zero-point current and sensitivity calibration data), and the compensation test is "temperature and humidity correlation compensation" (correct output based on the temperature and humidity curve from -40℃ to 125℃).

[0074] Mode 2: The benchmark test is "50ppm hydrogen sulfide standard gas calibration" (sensitivity is calibrated by introducing standard gas), and the compensation test is "temperature and humidity correlation compensation".

[0075] (2) Impedance type sensor:

[0076] Mode 1: The benchmark test is "0.1ppm low concentration standard gas calibration" (measuring the resistance response baseline), and the compensation test is "sensitive membrane adsorption characteristic compensation" (based on RH 30%~90% adsorption curve correction).

[0077] Mode 2: The benchmark test is "clean air baseline calibration" (measuring the resistance value under clean air), and the compensation test is "sensitive membrane adsorption characteristic compensation".

[0078] During the test mode determination phase, each type of target sensor corresponds to at least two different test modes. The different test modes include different benchmark test modes or compensation test modes, thereby avoiding the limitations of a single test mode (such as QR code calibration being convenient but easily affected by factory deviations, and standard gas calibration being accurate but complex to operate). Users can select the mode according to the scenario (select mode 1 for quick testing on site, and select mode 2 for accurate calibration in the laboratory), thereby improving the testing flexibility.

[0079] Of course, in practical applications, the choice of test mode needs to be combined with the application scenario. The following are examples of basic scenario selection principles:

[0080] ① Rapid on-site testing (e.g., mines, sewers): Prioritize 'factory calibration information retrieval + basic compensation' (e.g., temperature and humidity related compensation), operation time ≤ 10 min; ② Precise laboratory testing (e.g., sensor factory quality inspection): Prioritize 'standard gas calibration + precise compensation' (e.g., linear fitting + temperature and humidity dual compensation), operation time ≤ 30 min; ③ Low concentration / trace detection: Select 'low concentration standard gas calibration + dedicated compensation' (e.g., photoelectrochemical type 'identification probe calibration + signal quenching compensation').

[0081] III. Test Execution Phase

[0082] The execution test phase follows the process of "benchmark calibration → interference correction → data acquisition": first, a unified performance benchmark is established through benchmark testing, then the deviations caused by the environment (temperature and humidity) and materials (adsorption of sensitive membrane) are corrected through compensation testing, and finally, core performance data is collected to ensure that the data truly reflects the sensor performance.

[0083] Taking an electrochemical sensor (using a Pt-Co / C catalyst with a specific surface area of ​​approximately 1000 m² / g) as an example:

[0084] 1. Benchmark test: Introduce 50ppm hydrogen sulfide standard gas, control the temperature at 25℃ and RH at 50%, record the response current (e.g., 443.08nA / ppm), and calibrate the sensitivity benchmark;

[0085] The units are explained as follows:

[0086] pM: Pimoles per liter (10 -12 mol / L);

[0087] nA / ppm: Nanoampere concentration per million parts per volume.

[0088] 2. Compensation test: "Linear fitting compensation" is adopted (for example, the current deviation at low concentration (1ppm) can be corrected based on polynomial fitting algorithm).

[0089] 3. Data Acquisition: Acquire zero-point current (e.g., 3nA) under clean air, response current under 1~20ppm hydrogen sulfide, and output signal under temperature change from -20℃ to 50℃, and store it as structured data.

[0090] In this example, the accuracy reduction caused by low-concentration environment and temperature and humidity fluctuations is corrected through the dual protection of "benchmark + compensation" (e.g., the low-concentration deviation reaches 15% without compensation, and is reduced to ±5% after compensation). At the same time, multi-dimensional data is collected to provide a comprehensive basis for subsequent analysis.

[0091] IV. Test Result Analysis Phase

[0092] The analysis phase is based on the analysis logic of "visual comparison + key indicator quantification": the performance data before and after compensation are transformed into intuitive curves, and quantitative evaluation is carried out in combination with industry standards (such as response time <30s, linearity R²≥0.99) to achieve dual verification of "qualitative observation + quantitative judgment".

[0093] The test results include the performance curves and key indicators of the target sensor before and after the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability.

[0094] Taking photoelectrochemical sensors as an example:

[0095] 1. Result Visualization: The interface displays the "Photocurrent-Concentration Curve Before Compensation" (R²=0.985) and the "Curve After Compensation" (R²=0.999), with Cu labeled. x The difference between S-signal quenching compensation and its aftermath;

[0096] 2. Key indicator analysis: Calculate response time (28s before compensation → 22s after compensation), sensitivity (detection limit of 333.3pM before compensation → 300pM after compensation), and anti-interference (deviation from 10% to 3% under VOC interference) to determine whether it meets industrial testing requirements (e.g., detection limit ≤ 500pM).

[0097] The visualization analysis method at this stage avoids the obscurity of pure data listing, presents the compensation effect intuitively through curve comparison, and accurately judges performance by combining quantitative indicators, thus solving the problem of "too much subjective judgment and too few objective standards" in existing analysis.

[0098] V. Human-Computer Interaction Feedback Stage

[0099] Based on the closed-loop logic of "visual interaction - feedback decision - mode switching", testers are allowed to conduct in-depth verification through the performance curve (such as magnifying the deviation area), and then decide whether to switch modes based on the feedback results (meeting the standard / not meeting the standard), ensuring that the testing process is adjustable and the results are reliable.

[0100] Taking impedance-type sensors as an example:

[0101] 1. Interactive operation: The testers found that in the "low concentration standard gas + adsorption compensation" mode, the curve deviated by more than 8% at RH 90%. By zooming in on the curve in this humidity range through the interface, it was confirmed that the deviation was due to insufficient adsorption compensation.

[0102] 2. Feedback Decision: If it is determined that a mode switch is needed, return to the "Test Mode Determination Stage" and select the "0.1ppm Standard Gas + Temperature and Humidity Dual Compensation" mode to retest;

[0103] 3. Result verification: After switching, the deviation decreased to 3%, which meets the requirements, and the test ended.

[0104] As a more preferred embodiment, see further details. Figure 3 , Figure 3 This is a schematic diagram of the human-computer interaction and visualization interface operation for implementing the testing method of a hydrogen sulfide sensor described in this invention.

[0105] As an example, in Figure 3 In the process, the performance curves use "concentration-response signal" as the core dimension (e.g., current / resistance / photocurrent-hydrogen sulfide concentration). Comparing the curves before and after compensation can intuitively present the interference correction effect (it should be understood that...). Figure 3 The two performance curves shown are merely illustrative and do not represent actual results.

[0106] Key metrics include:

[0107] - Response time (t) 90 Due to the highly toxic nature of hydrogen sulfide, rapid early warning is required (industry default <30s).

[0108] - Linearity (R²): Ensures detection accuracy over a wide concentration range (e.g., 0-100ppm) and avoids deviation at low concentrations (1-5ppm);

[0109] - Sensitivity: Quantified by sensor type (e.g., electrochemical type is measured in nA / ppm, photoelectrochemical type is measured in pM detection limit);

[0110] - Anti-interference capability: For common interfering gases (VOC, CO, ammonia) in application scenarios, the standard is the deviation rate (≤±5%).

[0111] The combination of the two achieves "trend observation (curve) + quantitative judgment (indicator)", avoiding misjudgment from a single dimension (such as a curve that appears linear but R² does not meet the standard).

[0112] For result visualization, a design of "hyperbolic overlay + key node annotation" is adopted:

[0113] The horizontal axis is uniformly represented by "hydrogen sulfide concentration" (ppm / nM), and the vertical axis is the sensor response signal (nA / Ω / μA) to ensure consistency of the comparison benchmark.

[0114] The curves before and after compensation are distinguished by different colors (e.g., red before compensation, blue after compensation), and the signal difference at key concentration points (e.g., 0ppm zero point, 50ppm standard gas point) is marked.

[0115] It supports dynamically loading indicator data (mouse hovering over curve nodes displays response time and sensitivity values), solving the problem of "intuitive curves but vague indicators".

[0116] The comparison operations (translation, zoom in, zoom out, rotation) are designed for "detail verification needs":

[0117] Magnify / Zoom Out: Focus on areas prone to deviation, such as low concentration (1-10ppm) or high humidity (RH80%-90%), to observe subtle signal fluctuations;

[0118] Translation: Compare the parallelism of the curves at different concentration ranges to determine linear consistency;

[0119] Rotation: Adapts to different display scenarios (such as landscape / vertical reports).

[0120] Of course, it is understandable that, compared to translation, zooming in and out, rotation is only used to adapt to horizontal / vertical report display, without changing the essence of the curve data, only optimizing the viewing perspective.

[0121] The above comparison operation logic conforms to the testers' analytical habits of "observing the overall picture first and then verifying the details", avoiding deviations and omissions caused by curve compression.

[0122] The preset conditions are customized according to "sensor type + application scenario", with the core being "key indicator threshold + curve overlap".

[0123] Threshold determination: For example, fuel cell type requires t 90 <30s, R²≥0.99; for photoelectrochemical type, the detection limit is required to be ≤500pM and the anti-interference deviation is required to be ≤±3%;

[0124] Curve coincidence: The deviation rate between the compensated curve and the "ideal performance curve" (the theoretical curve based on standard gas calibration) is ≤ ±5%, which is considered to meet the condition;

[0125] If any indicator fails to meet the standard or the curve deviation exceeds the threshold, it is determined that "the preset conditions are not met" and the mode switch is triggered.

[0126] Taking an impedance-type hydrogen sulfide sensor (CuO nanofilm) as an example, the test scenario is "low concentration (1-20ppm) detection in an industrial workshop", and the preset conditions are: t 90 <25s, R²≥0.995, VOC interference deviation≤±4%, curve coincidence≥95%.

[0127] 1. Test Result Generation

[0128] Performance curves: Curve before compensation (can be marked in red during actual implementation): Response resistance deviation of 12% at low concentration (1ppm) (theoretical value 10kΩ → measured 11.2kΩ), curve slope fluctuation at RH90%;

[0129] Compensated curve (can be marked in blue): Using "sensitive membrane adsorption characteristic compensation" (correcting the resistance deviation caused by excessive adsorption in high humidity), the deviation of 1ppm is reduced to 3%, and the slope is stable;

[0130] Key metrics:

[0131] Before compensation: t 90 =28s, R²=0.988, VOC interference deviation 8%;

[0132] After compensation: t 90 =22s, R²=0.998, VOC interference deviation 3%.

[0133] 2. Results visualization

[0134] In the test system interface:

[0135] - The horizontal axis represents "hydrogen sulfide concentration (ppm)" (0-20ppm), and the vertical axis represents "sensor resistance (kΩ)".

[0136] - Display two curves overlaid, with t values ​​labeled before and after compensation. 90 Resistance difference at the node (28s→22s) and the 1ppm concentration point (1.2kΩ→0.3kΩ);

[0137] - A pop-up indicator panel on the right displays in real time whether key indicators have met the standards (green "√" or red "×").

[0138] 3. Human-computer interaction comparison operation

[0139] Testers found that "the curve before compensation appeared linear in the 1-5 ppm range, but fluctuated after scaling up," and performed the following operations:

[0140] Magnification operation: Select the 1-5ppm concentration range, click "Magnify", the interface focuses on this range, and displays the curve before compensation where the resistance jumps abruptly at 3ppm (10.8kΩ→11.5kΩ), and the curve after compensation is smooth (10.8kΩ→10.9kΩ).

[0141] Translation operation: Translate the two curves along the vertical axis to align with the 0ppm zero point (zero point resistance was 1.2kΩ before compensation and 1.1kΩ after compensation), and observe the consistency of the slope;

[0142] Rotation Operation: Rotate the interface 90° (vertical display) to adapt to the workshop report format, ensuring that curve data is not distorted.

[0143] 4. Preset condition determination

[0144] - Meeting the following conditions: The deviation rate between the amplified compensation curve and the ideal curve (based on 50ppm standard gas calibration) is 2.3%, and all key indicators meet the standards (t). 90 =22s, R²=0.998, interference deviation 3%), determined as "performance test passed";

[0145] -Scenario where conditions are not met: If compensation is not performed, the deviation rate in the 1-5ppm range after amplification reaches 12%, t 90 =28s exceeded the threshold, determined "test mode needs to be switched", returned to "test mode determination stage", selected "low concentration standard gas calibration + temperature and humidity dual compensation" mode to retest and correct the deviation.

[0146] Compared to the "one test for life" approach of existing single-mode testing technologies, this embodiment solves the problem of sudden deviations (such as insufficient compensation caused by a sudden increase in environmental humidity) by flexibly switching modes, ensuring that the final test results meet the actual application requirements and improving test reliability.

[0147] Based on the method implementation examples, see [link to relevant documentation]. Figure 4 , Figure 4 This diagram illustrates a partial functional unit composition of a test system for a hydrogen sulfide sensor according to an embodiment of the present invention.

[0148] Figure 4 The present invention provides a test system for a hydrogen sulfide sensor. The target sensor types to be tested include at least the following: fuel cell type based on micro fuel cells and using a true solid electrolyte; impedance type based on semiconductor resistance sensing and using a metal oxide sensitive membrane; electrochemical type based on constant potential electrolysis and using a bimetallic catalyst; and photoelectrochemical type based on photoelectric conversion and using an organic-inorganic composite heterojunction.

[0149] Specifically, the system includes:

[0150] Sensor type identification unit: Determines the type of the target sensor based on its measurement principle and material properties;

[0151] Test mode determination unit: Based on the target sensor type identified by the sensor type identification unit, determines the test mode of the target sensor, wherein the test mode includes at least a benchmark test mode and a compensation test mode;

[0152] Test execution unit: Performs performance tests on the target sensor based on a defined test mode;

[0153] Test Result Analysis Unit: Analyzes the performance of the target sensor based on the test results output by the visualization interface; the test results include the performance curves and key indicators of the target sensor before and after performing the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability;

[0154] Human-computer interaction feedback unit: Receives human-computer interaction feedback data based on the visual interface, determines whether to switch test modes based on the feedback data, if so, returns to the test mode determination unit to reselect the test mode, otherwise ends the test;

[0155] In the test mode determination stage, each type of target sensor corresponds to at least two different test modes, and the different test modes include different benchmark test modes or compensation test modes.

[0156] For illustration purposes, a test mode = a baseline test mode + a compensation test mode; different test modes are constituted as long as either the baseline test mode or the compensation test mode is different.

[0157] For example, if test mode M1 = baseline test mode M10 + compensation test mode M20; and test mode M2 ​​= baseline test mode M20 + compensation test mode M20, then test mode M1 and test mode M2 ​​belong to different test modes. Each time the test mode is changed, either the baseline test mode or the compensation test mode can be changed, or both can be changed simultaneously.

[0158] The human-computer interaction feedback unit receives human-computer interaction feedback data including: receiving comparison operations from testers on at least two performance curves, the comparison operations including translation, zooming in, zooming out, and rotation;

[0159] When at least two performance curves after the comparison operation meet the preset conditions, the target sensor is determined to have passed the performance test.

[0160] The test results output based on the visualization interface include the performance curves and key indicators of the target sensor before and after performing the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability.

[0161] Although not shown in the accompanying drawings, further embodiments also include a computer-readable storage medium for storing computer instructions that, when executed on an electronic device, enable the implementation of a testing method for a hydrogen sulfide sensor according to an embodiment of the present invention.

[0162] Although not shown in the accompanying drawings, further embodiments include an electronic device comprising a processor and a memory for storing instructions, the processor for calling the instructions in the memory to cause the electronic device to perform a testing method for a hydrogen sulfide sensor according to an embodiment of the present invention.

[0163] Although not shown in the accompanying drawings, further embodiments also include a computer program product comprising a computer program that, when executed, implements a testing method for a hydrogen sulfide sensor according to an embodiment of the present invention.

[0164] Those skilled in the art will understand that the implementation principles of the system (product, medium, device) embodiments and the steps of the method embodiments can correspond to and reference each other. Therefore, given that the method embodiments have already been described in detail, the implementation principles of the system (product, medium, device) embodiments need not be repeated. Furthermore, the technical problems that the method embodiments can solve and their advantages over existing technologies will necessarily be reflected in the relevant system (product, medium, device) embodiments as well.

[0165] In summary, the advantages of the technical solution proposed in this invention include at least the following:

[0166] (1) Strong adaptability to multiple types of sensors

[0167] In the technical solution of this invention, sensor types are identified through a two-dimensional approach: "measurement principle - material properties." For example, fuel cell sensors are identified based on "micro fuel cell principle + true solid electrolyte," while impedance sensors are identified based on "semiconductor resistance principle + CuO nano-sensitive membrane." At least two testing modes are matched for each type, such as "QR code access + temperature and humidity compensation" and "standard gas calibration + temperature and humidity compensation" for fuel cell sensors. This invention avoids the problem of general testing methods ignoring the characteristics of hydrogen sulfide sensors; it also covers both precise laboratory testing and rapid on-site testing scenarios, overcoming the limitations of single-application technology and achieving standardized testing for multiple sensor types.

[0168] (2) High testing accuracy

[0169] In the technical solution of this invention, a unified performance benchmark is established through benchmark testing, such as using 50ppm hydrogen sulfide standard gas to calibrate the sensitivity of the electrochemical type; a type-specific compensation algorithm is used to correct the deviation, such as using sensitive membrane adsorption compensation for the impedance type and temperature and humidity correlation compensation for the fuel cell type; zero-point signal, target concentration response signal and environmental influence signal are collected simultaneously to provide data support for correction; the deviation caused by low concentration and temperature and humidity fluctuations is reduced from 15% to ±5%, solving the problem of sensor accuracy degradation and meeting industrial testing requirements.

[0170] (3) Flexible human-computer interaction and mode switching

[0171] In the technical solution of this invention, the performance curves before and after compensation are visualized and supported for comparison operations such as translation and magnification. For example, after magnifying the low concentration range to observe the deviation, interactive feedback is received to judge whether the curve meets the preset conditions. It can avoid the rigid limitation of traditional one-way testing that is "one test for life". When the conditions are not met, the mode can be switched. For example, the impedance type can be switched from "single adsorption compensation" to "temperature and humidity dual compensation", dynamically optimizing the test strategy and improving reliability.

[0172] (4) The test results analysis is comprehensive and intuitive.

[0173] The improvements in this area are mainly reflected in the following aspects: First, performance curves are overlaid and key differences are marked, such as the comparison of R² before and after photoelectrochemical compensation; second, indicators such as response time and linearity are quantified and compared with preset thresholds (such as R²≥0.99) for judgment; third, data listing and subjective misjudgment are avoided; finally, the compliance status and problem points are clearly marked, such as "anti-interference deviation 3% (√)", realizing "qualitative observation + quantitative judgment" to ensure that the analysis is objective and traceable.

[0174] Nevertheless, it is particularly important to note that although the present invention provides multiple embodiments, each embodiment can constitute an independent technical solution and may contribute to the prior art and solve corresponding technical problems. That is, each embodiment can solve at least one technical problem, but it is not required that each individual embodiment solve multiple or all technical problems.

[0175] Other technologies, principles, algorithms, or models not elaborated in detail in this application can be found in the prior art.

[0176] The foregoing has shown and described the method embodiments and systems of the present invention, but it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A testing method for a hydrogen sulfide sensor, characterized in that, The method includes: Sensor type identification stage: Determine the type of the target sensor based on its measurement principle and material properties; Test mode determination stage: Based on the target sensor type identified in the previous stage, the test mode of the target sensor is determined, and the test mode includes at least a benchmark test mode and a compensation test mode. Test execution phase: Based on the determined test mode, performance tests are performed on the target sensor; Test result analysis phase: Analyze the performance of the target sensor based on the test results; Human-computer interaction feedback phase: Receive human-computer interaction feedback data, determine whether to switch test modes based on the feedback data, if yes, return to the test mode determination phase to reselect the test mode, otherwise end the test; In the test mode determination stage, each type of target sensor corresponds to at least two different test modes, and the different test modes include different benchmark test modes or compensation test modes.

2. The testing method for a hydrogen sulfide sensor as described in claim 1, characterized in that, The test modes include a reference test mode selected from one or a combination of factory calibration information retrieval, standard gas verification, catalyst sensitivity calibration, limiting current calibration, identification probe calibration, or photocurrent reference calibration; the test modes include a compensation test mode selected from one or a combination of temperature and humidity correlation compensation, sensitive membrane adsorption characteristic compensation, linear fitting compensation, and signal quenching compensation.

3. The testing method for a hydrogen sulfide sensor as described in claim 2, characterized in that, The standard gas used for calibration is hydrogen sulfide standard gas, and the identification probe calibration uses a metal ion probe.

4. The testing method for a hydrogen sulfide sensor as described in claim 1, characterized in that, The test results include the performance curves and key indicators of the target sensor before and after the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability.

5. The testing method for a hydrogen sulfide sensor as described in claim 1, characterized in that, The test result analysis stage also includes a result visualization sub-stage, which visualizes at least two performance curves corresponding to the test results. The human-computer interaction feedback data received during the human-computer interaction feedback phase includes: receiving comparison operations from testers on the at least two performance curves, the comparison operations including translation, zooming in, zooming out, and rotation; If at least two performance curves after performing the comparison operation do not meet the preset conditions, the test mode is switched.

6. The testing method for a hydrogen sulfide sensor as described in claim 1, characterized in that, During the test execution phase, core performance data of the target sensor are collected, including zero-point signal, response signal at target concentration, and output signal under environmental influence.

7. A testing system for a hydrogen sulfide sensor, characterized in that, The system includes: Sensor type identification unit: Determines the type of the target sensor based on its measurement principle and material properties; Test mode determination unit: Based on the target sensor type identified by the sensor type identification unit, determines the test mode of the target sensor, wherein the test mode includes at least a benchmark test mode and a compensation test mode; Test execution unit: Performs performance tests on the target sensor based on a defined test mode; Test Result Analysis Unit: Analyzes the performance of the target sensor based on the test results output by the visualization interface; the test results include the performance curves and key indicators of the target sensor before and after performing the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability; Human-computer interaction feedback unit: Receives human-computer interaction feedback data based on the visual interface, determines whether to switch test modes based on the feedback data, if so, returns to the test mode determination unit to reselect the test mode, otherwise ends the test; In the test mode determination stage, each type of target sensor corresponds to at least two different test modes, and the different test modes include different benchmark test modes or compensation test modes.

8. The testing system for a hydrogen sulfide sensor as described in claim 7, characterized in that, The human-computer interaction feedback unit receives human-computer interaction feedback data including: receiving comparison operations from testers on at least two performance curves, the comparison operations including translation, zooming in, zooming out, and rotation; When at least two performance curves after the comparison operation meet the preset conditions, the target sensor is determined to have passed the performance test.

9. The testing system for a hydrogen sulfide sensor as described in claim 7, characterized in that, The test results output based on the visualization interface include the performance curves and key indicators of the target sensor before and after performing the compensation test; the key indicators include response time, linearity, sensitivity, and anti-interference capability.

10. The testing system for a hydrogen sulfide sensor as described in claim 7, characterized in that, The target sensor types to be tested include at least: fuel cell type based on micro fuel cells and using true solid electrolytes; impedance type based on semiconductor resistance sensing and using metal oxide sensitive membranes; electrochemical type based on constant potential electrolysis and using bimetallic catalysts; and photoelectrochemical type based on photoelectric conversion and using organic-inorganic composite heterojunctions.

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