Fire-resistant oil resistivity on-line monitoring sensor and control method thereof

Abstract

The invention discloses a fire-resistant oil resistivity on-line monitoring sensor and a control method thereof, and belongs to the technical field of fire-resistant oil on-line monitoring. According to the method, the problem that in an existing method, an electrode is prone to being polluted by oil pollutants, and consequently the measurement precision is reduced is solved, by setting the warning threshold value and the danger threshold value, abnormal changes of the resistivity can be found in time, and abnormal conditions of different degrees can be distinguished; more detailed abnormal information is provided for operators, and targeted measures can be taken; by analyzing impedance characteristics of different frequency regions, the state of the fire-resistant oil can be known more deeply, and the reason of resistivity change can be accurately judged; the electrochemical behavior of the fire-resistant oil is obtained based on the analysis result of the EIS data and the resistivity change, and the remaining service life of the fire-resistant oil can be predicted, so that the oil change period is optimized, unnecessary maintenance work is reduced, and an equipment maintenance strategy can be formulated more scientifically.

Description

Technical Field

[0001] The present invention relates to the technical field of on-line monitoring of fire-resistant oil, and specifically to an on-line monitoring sensor for the resistivity of fire-resistant oil and its control method. Background Technique

[0002] Fire-resistant oil (EH oil) is a synthetic hydraulic oil composed of phosphate esters, with a transparent and uniform appearance. It is mainly applied to the electro-hydraulic control system of power plants for hydraulic transmission and control systems. The main characteristics of fire-resistant oil include: fire resistance: it is not easily ignited even at extremely high temperatures, and if it catches fire under extreme conditions, the flame will not spread and will quickly self-extinguish; thermal oxidation stability: it can remain stable in high-temperature environments; physical properties: fire-resistant oil has a high density, a high auto-ignition point, a high resistivity, and good lubricity and anti-wear properties. The resistivity of fire-resistant oil refers to the resistance per unit volume, which is an important indicator characterizing the electrical properties of insulating materials. The larger the resistivity, the better the insulation performance.

[0003] The industry requires the resistivity of fire-resistant oil to be monitored during use. The traditional method for measuring the resistivity of fire-resistant oil is to monitor it using an insulating oil resistivity tester; however, when the insulating oil resistivity tester is used for long-term on-line monitoring, the electrodes are easily contaminated by oil pollutants such as particulate matter and water adhesion, resulting in a decrease in measurement accuracy and the need for frequent cleaning or replacement.

[0004] Therefore, it does not meet the existing requirements, and for this reason, we propose an on-line monitoring sensor for the resistivity of fire-resistant oil and its control method. Summary of the Invention

[0005] The purpose of the present invention is to provide an on-line monitoring sensor for the resistivity of fire-resistant oil and its control method. By setting warning thresholds and danger thresholds, it can timely detect abnormal changes in resistivity and distinguish different degrees of abnormal situations; it provides more detailed abnormal information for operators, which helps to take targeted countermeasures; by analyzing the impedance characteristics in different frequency regions, it can more deeply understand the state of fire-resistant oil and accurately judge the cause of resistivity changes; based on the analysis results of EIS data and resistivity changes, the electrochemical behavior of fire-resistant oil can be obtained, and the remaining service life of fire-resistant oil can be predicted, thereby optimizing the oil change cycle, reducing unnecessary maintenance work, and formulating a more scientific equipment maintenance strategy, solving the problems raised in the above background technique.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: An on-line monitoring sensor for the resistivity of fire-resistant oil, the sensor includes: a signal acquisition unit and a signal analysis unit, and the signal analysis unit includes: a signal calculation module and a characteristic analysis module; The signal acquisition unit is configured to preset a periodic acquisition frequency and regularly acquire the current flowing through the test electrode of the fire-resistant oil, the voltage across the test electrode, and the test temperature. The signal calculation module is configured to determine the distance between the test electrodes and the effective facing area based on the current, voltage, and temperature signals of the fire-resistant oil, and calculate the resistivity of the fire-resistant oil. The characteristic analysis module is configured to analyze the current, voltage, and temperature signals and resistivity of the fire-resistant oil based on the EIS (Electrochemical Impedance Spectroscopy) technology to obtain EIS data; and generate an impedance spectrum diagram for judging the relationship between the change in the resistivity of the fire-resistant oil and the impedance characteristics of the fire-resistant oil, and analyzing the electrochemical behavior of the fire-resistant oil.

[0007] Further, the signal calculation module includes: The abnormal threshold module is configured to set an abnormal threshold according to the normal resistivity range of the fire-resistant oil; and compare the real-time resistivity of the fire-resistant oil with the abnormal threshold to judge whether the real-time resistivity of the fire-resistant oil is abnormal. The abnormal feedback module is configured to trigger an abnormal feedback mechanism if the resistivity exceeds the abnormal threshold range.

[0008] Further, the abnormal feedback module includes: The abnormal level module is configured to set multiple abnormal feedback levels based on the abnormal threshold, corresponding to different degrees of abnormal situations respectively. The warning response module is configured to set different response strategies based on different abnormal feedback levels.

[0009] Further, the characteristic analysis module includes: The current application module is configured to input an AC current signal with adjustable frequency to the test electrode through a galvanostat, analyze the current, voltage, and temperature signals and resistivity of the fire-resistant oil based on the EIS technology to obtain EIS data, and generate an impedance spectrum diagram; for judging the relationship between the change in the resistivity of the fire-resistant oil and the impedance characteristics of the fire-resistant oil, and analyzing the electrochemical behavior of the fire-resistant oil. The impedance analysis module is configured to divide the impedance spectrum diagram into a high-frequency part, a middle-frequency part, and a low-frequency part, and analyze the impedance characteristics of the high-frequency part and the low-frequency part respectively to obtain the analysis results of each part.

[0010] Further, the characteristic analysis module further includes: The relationship analysis module is configured to analyze the corresponding phenomena in the high-frequency part, middle-frequency part, and low-frequency part respectively based on the resistivity decrease phenomenon and resistivity increase phenomenon to obtain the relationship between the resistivity change and the impedance characteristics. An electrochemical analysis module, configured to obtain electrochemical behavior results based on the performance of the high-frequency part, intermediate-frequency part, and low-frequency part of the impedance spectrogram, in combination with the relationship between resistivity change and impedance characteristics.

[0011] Further, the signal analysis unit further includes: A temperature threshold module, configured to analyze EIS data at different temperatures, evaluate the influence of the electrochemical impedance spectrum of the fire-resistant oil at different temperatures, and preset an ambient temperature threshold; A temperature compensation module, configured to monitor the temperature of the test environment in real time, compare the real-time ambient temperature with the ambient temperature threshold, and if the real-time ambient temperature is lower than the ambient temperature threshold, timely perform temperature compensation on the on-line monitoring sensor.

[0012] Further, the signal acquisition unit includes: A timing acquisition module, configured to set a periodic acquisition mechanism based on a timer, and control the on-line monitoring sensor to perform signal acquisition tasks each time the timer is triggered; A data reading module, configured to read the outputs of the voltage measurement, current measurement, and temperature sensor based on an analog-to-digital converter, and obtain the voltage across the test electrode, the current flowing through the test electrode, and the temperature of the fire-resistant oil.

[0013] Further, the sensor further includes: A human-machine interaction terminal, configured to visually display the voltage, current, temperature of the fire-resistant oil, and resistivity data based on a mobile terminal; A data transmission module, configured to transmit the voltage, current, temperature of the fire-resistant oil, and resistivity data to the human-machine interaction terminal through a communication interface.

[0014] Further, the sensor further includes: A data storage module, configured to store the collected voltage, current, temperature of the fire-resistant oil, and resistivity data in the human-machine interaction terminal in a time series to form a database; A data encryption module, configured to encrypt the data in the database based on a hash function.

[0015] A control method for an on-line monitoring sensor of the resistivity of fire-resistant oil includes the following steps: Control the sensor to collect data regularly according to a preset periodic acquisition frequency, and calculate the resistivity of the fire-resistant oil; Set multiple abnormal feedback levels based on an abnormal threshold, including: setting a warning threshold and a danger threshold, comparing the real-time resistivity of the fire-resistant oil with the set warning threshold and danger threshold respectively, judging whether there is an abnormality and the degree of the abnormality, and triggering a corresponding abnormal feedback mechanism; Analyze the current, voltage, temperature signals and resistivity of the fire-resistant oil based on the EIS (Electrochemical Impedance Spectroscopy) technology to obtain EIS data and create an impedance spectrogram. Based on the change phenomenon of resistivity, analyze the impedance characteristics of the high-frequency, medium-frequency and low-frequency parts, and judge the relationship between the resistivity change and the impedance characteristics. Combined with the performance of the impedance spectrogram, analyze the electrochemical behavior of the fire-resistant oil. Visually display the voltage, current, temperature and resistivity data, as well as the relationship between the resistivity change and impedance characteristics and the electrochemical behavior of the fire-resistant oil on the human-computer interaction terminal.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. In the present invention, by setting warning thresholds and danger thresholds, the resistivity of the real-time fire-resistant oil is compared with the preset normal range in real time, the abnormal change of resistivity is detected in time, and different degrees of abnormal situations are distinguished; more detailed abnormal information is provided for the operator, which helps to take targeted measures.

[0017] 2. In the present invention, by analyzing the impedance characteristics of different frequency regions, the state of the fire-resistant oil can be understood more deeply, and the reason for the resistivity change can be accurately judged; based on the analysis results of EIS data and resistivity change, the electrochemical behavior of the fire-resistant oil can be obtained, and the remaining service life of the fire-resistant oil can be predicted, so as to optimize the oil change cycle, reduce unnecessary maintenance work and formulate a more scientific equipment maintenance strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a logic schematic diagram of the on-line monitoring sensor for the resistivity of the fire-resistant oil of the present invention; Figure 2 It is a flow chart of the control method of the on-line monitoring sensor for the resistivity of the fire-resistant oil of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0020] To solve the technical problem in the prior art that in the traditional method for measuring the resistivity of fire-resistant oil, it is monitored by using an insulating oil resistivity tester; however, when the insulating oil resistivity tester is monitored online for a long time, the electrodes are easily contaminated by oil contaminants such as particulate matter and water adhesion, resulting in a decrease in measurement accuracy and the need for frequent cleaning or replacement, please refer to Figure 1 - Figure 2, this embodiment provides the following technical solutions: An on-line monitoring sensor for the resistivity of fire-resistant oil, the on-line monitoring sensor comprising: a signal acquisition unit and a signal analysis unit, the signal analysis unit comprising: a signal calculation module and a characteristic analysis module.

[0021] The signal acquisition unit is configured to preset a periodic acquisition frequency and regularly acquire the current flowing through the test electrode of the fire-resistant oil, the voltage across the test electrode, and the test temperature; the signal acquisition unit comprises: A timing acquisition module configured to set a periodic acquisition mechanism based on a timer and, upon each trigger of the timer, control the on-line monitoring sensor to perform a signal acquisition task.

[0022] In one embodiment, assuming that the acquisition period is once per minute, the trigger interval of the timer should be set to 60 seconds; when the timer is triggered, the timing acquisition module sends a control signal to start the signal acquisition task of the on-line monitoring sensor, including activating the voltage measurement module, the current measurement module, and the temperature sensor to obtain relevant data of the fire-resistant oil; thereby ensuring the regularity and continuity of data acquisition and enabling real-time monitoring of the state of the fire-resistant oil.

[0023] A data reading module configured to read the outputs of the voltage measurement, current measurement, and temperature sensor based on an analog-to-digital converter to obtain the voltage across the test electrode, the current flowing through the test electrode, and the temperature of the fire-resistant oil; the analog-to-digital converter can accurately convert the analog signal into a digital signal to obtain relevant data of the fire-resistant oil, providing timely data support for subsequent analysis and processing and improving the accuracy of data acquisition.

[0024] The signal calculation module is configured to determine the distance between the test electrodes and the effective facing area based on the current, voltage, and temperature signals of the fire-resistant oil and calculate the resistivity of the fire-resistant oil; the signal calculation module comprises: An abnormal threshold module configured to set an abnormal threshold according to the normal resistivity range of the fire-resistant oil; and compare the resistivity of the real-time fire-resistant oil with the abnormal threshold to determine whether there is an abnormality in the resistivity of the real-time fire-resistant oil.

[0025] An abnormal feedback module configured to trigger an abnormal feedback mechanism if the resistivity exceeds the abnormal threshold range.

[0026] In one embodiment, assuming that the normal resistivity range of the fire-resistant oil is above 6.0×109Ω•cm, the abnormal thresholds are divided into: a warning threshold and a danger threshold. A lower threshold is set as the warning threshold. For example, the warning threshold is 5.0×109Ω•cm; when the resistivity is lower than this value, a warning is triggered. A lower threshold is set as the danger threshold. For example, the danger threshold is 3.0×109Ω•cm; when the resistivity is lower than this value, a danger alarm is triggered. The feedback methods include: local alarm, such as: an audible and visual alarm; remote notification, such as: text message, email, APP push, etc. to feedback the abnormal information to the human-machine interaction terminal. By setting multiple threshold levels, different degrees of abnormal situations can be distinguished, providing more detailed information for the operator, facilitating the adoption of targeted measures, and avoiding equipment failures or safety accidents.

[0027] The abnormal feedback module includes: an abnormal level module configured to set multiple abnormal feedback levels based on the abnormal thresholds. For example, the warning threshold and the danger threshold, corresponding to different degrees of abnormal situations respectively; different levels of abnormal feedback can correspond to different processing measures. For example, the warning level can remind the user to conduct a routine inspection, and the danger level can trigger measures such as an emergency shutdown. Through hierarchical early warning, the state of the fire-resistant oil can be reflected more accurately, reducing false alarms and missed alarms, and improving the reliability of the system.

[0028] The early warning response module is configured to set different response strategies based on different abnormal feedback levels; for example, the warning level can trigger a routine inspection reminder, and the danger level can trigger measures such as an emergency shutdown or automatic switching to a standby system; enabling it to automatically take corresponding measures when an abnormality is detected, reducing manual intervention, and improving the automation level of the system.

[0029] The beneficial effects achieved by the above content: By setting the warning threshold and the danger threshold, the system can compare the resistivity of the real-time fire-resistant oil with the preset normal range in real time, timely detect abnormal changes in the resistivity, and distinguish different degrees of abnormal situations; providing more detailed abnormal information for the operator, which helps to take targeted measures, such as timely oil replacement or equipment maintenance; and setting different response strategies according to different abnormal levels, not only improving the safety of equipment operation, but also optimizing the equipment maintenance strategy, reducing unnecessary maintenance work, and improving the operation efficiency of the equipment.

[0030] The characteristic analysis module is configured to analyze the current, voltage, temperature signals and resistivity of the fire-resistant oil based on the EIS electrochemical impedance spectroscopy technology, thereby obtaining EIS data; and making an impedance spectrogram to judge the relationship between the resistivity change of the fire-resistant oil and the impedance characteristics of the fire-resistant oil, and analyzing the electrochemical behavior of the fire-resistant oil; for example: the decrease in resistivity may be related to the conductive or polar substances generated by the deterioration of the fire-resistant oil; the characteristic analysis module includes: A current application module, configured to input an alternating current signal with adjustable frequency to a test electrode through a galvanostat, analyze the current, voltage, temperature signals and resistivity of the fire-resistant oil based on the EIS (Electrochemical Impedance Spectroscopy) technology, obtain EIS data, and generate an impedance spectrogram for judging the relationship between the resistivity change of the fire-resistant oil and the impedance characteristics of the fire-resistant oil, and analyzing the electrochemical behavior of the fire-resistant oil; specifically, by analyzing the shape and position of the curve, the control mechanism of the electrochemical process can be judged; for example, the charge transfer control process usually presents as a semicircle, while the mass transfer control process presents as an inclined line segment; by analyzing the variation of the impedance modulus and phase angle with frequency, the control mechanism of the electrochemical process can be clarified; also by analyzing the variation of the phase angle with frequency, the control mechanism of the electrochemical process can be judged, so as to infer the relationship between the resistivity change and the impedance characteristics of the fire-resistant oil, and further deeply analyze the electrochemical behavior of the fire-resistant oil. Usually, a small-amplitude sine wave current signal is adopted, and its amplitude generally does not exceed 10 mA to ensure the linear response of the system. The impedance spectrogram reflects the variation relationship of the impedance of the electrochemical system with frequency.

[0031] An impedance analysis module, configured to divide the impedance spectrogram into a high-frequency part > 1 kHz, a medium-frequency part 10 Hz - 1 kHz, and a low-frequency part < 10 Hz, and analyze the impedance characteristics of the high-frequency part and the low-frequency part respectively to obtain the analysis results of each part; for example: the high-frequency part in the impedance spectrogram mainly reflects the double-layer characteristics, the medium-frequency region mainly reflects the charge transfer impedance, and the low-frequency part is related to the charge transfer and diffusion processes; if there is an obvious relaxation process in the low-frequency region of the impedance spectrogram, it may indicate the existence of electrochemically active substances in the fire-resistant oil.

[0032] A relationship analysis module, configured to respectively analyze the corresponding phenomena in the high-frequency part, the medium-frequency part and the low-frequency part based on the resistivity decrease phenomenon and the resistivity increase phenomenon, and obtain the relationship between the resistivity change and the impedance characteristics; for example: the deterioration of the fire-resistant oil leads to a decrease in resistivity, and at the same time, it is manifested as an increase in the charge transfer impedance in the medium-frequency region of the impedance spectrogram; high water content will cause the hydrolysis of phosphate ester to produce acidic substances, resulting in a decrease in resistivity.

[0033] The electrochemical analysis module is configured to obtain the electrochemical behavior results based on the performance of the high-frequency part, the medium-frequency part and the low-frequency part in the impedance spectrum, combined with the relationship between the resistivity change and the impedance characteristics; for example: Regarding deterioration: Deterioration of fire-resistant oil will lead to a decrease in resistivity, and at the same time, it is manifested in the impedance spectrum as an increase in the charge transfer impedance in the medium-frequency region. Regarding moisture content: High moisture content will cause the hydrolysis of phosphate esters to produce acidic substances, resulting in a decrease in resistivity. Regarding temperature effects: Increased temperature will accelerate the deterioration of fire-resistant oil, resulting in a decrease in resistivity. Regarding polar substances and pollutants: The presence of polar substances and pollutants in the oil, such as chloride ions, acidic degradation products, etc., will affect the resistivity. The impedance spectrum drawn by EIS electrochemical impedance spectroscopy technology can intuitively display the electrochemical behavior of fire-resistant oil, and determine the cause of the change in resistivity by analyzing the impedance characteristics of different frequency zones.

[0034] The beneficial effects achieved by the above content are as follows: by analyzing the impedance characteristics in different frequency zones, we can have a deeper understanding of the state of the fire-resistant oil, sensitively detect tiny changes in the fire-resistant oil, and accurately determine the cause of the resistivity change; based on the EIS data and the analysis results of the resistivity change, the electrochemical behavior of the fire-resistant oil is obtained, and the remaining service life of the fire-resistant oil can be predicted, thereby optimizing the oil change cycle, reducing unnecessary maintenance work, and formulating equipment maintenance strategies more scientifically.

[0035] The signal analysis unit further comprises: The temperature threshold module is configured to collect the temperature of the test environment in real time through a temperature sensor, analyze the EIS data at different temperatures, evaluate the impact of the electrochemical impedance spectrum of the fire-resistant oil at different temperatures, and preset the ambient temperature threshold based on the analysis results for subsequent temperature compensation and abnormality judgment.

[0036] The temperature compensation module is configured to monitor the temperature of the test environment in real time and compare the real-time ambient temperature with the ambient temperature threshold. If the real-time ambient temperature is lower than the ambient temperature threshold, the online monitoring sensor is timely temperature compensated.

[0037] Temperature compensation can be done by: Hardware temperature compensation method: For example, a temperature sensor for testing the ambient temperature is placed near the online monitoring sensor. When the real-time ambient temperature change is detected, the working parameters of the online monitoring sensor are adjusted through the circuit to offset the error caused by the ambient temperature change.

[0038] Software temperature compensation strategy: By writing an algorithm to correct the errors caused by the ambient temperature, the output of the on-line monitoring sensor can be adjusted in real time according to the readings of the temperature sensor used to measure the ambient temperature and the pre-calibrated data. For example, by analyzing the readings of the hardware temperature sensor through a software algorithm, the calibration parameters of the on-line monitoring sensor can be dynamically adjusted to compensate for the errors caused by temperature changes in real time.

[0039] In summary, temperature compensation is achieved by monitoring the ambient temperature and comparing it with a preset ambient temperature threshold, and then using hardware or software methods, or a combination of both, to dynamically adjust the output of the on-line monitoring sensor to eliminate or reduce the impact of temperature changes on the resistivity measurement results.

[0040] The on-line monitoring sensor further includes: A human-computer interaction terminal, configured to visually display voltage, current, the temperature of the fire-resistant oil, and resistivity data based on a mobile terminal; by drawing an impedance spectrogram for display, the electrochemical behavior of the fire-resistant oil can be intuitively understood; and by analyzing the impedance characteristics in different frequency regions, the accuracy and reliability of the monitoring sensor can be improved.

[0041] A data transmission module, configured to transmit voltage, current, the temperature of the fire-resistant oil, and resistivity data to the human-computer interaction terminal through a communication interface, such as RS485, Modbus RTU, Wi-Fi, etc.

[0042] A data storage module, configured to store the collected voltage, current, the temperature of the fire-resistant oil, and resistivity data in the human-computer interaction terminal in a time series to form a database; each data record includes a timestamp, a voltage value, a current value, a temperature value, and a resistivity value, which is convenient for subsequent data analysis and traceability; for example: the data stored in a time series is convenient for users to trace historical data and analyze the state change trend of the fire-resistant oil; through the timestamp, users can quickly locate the data at a specific time point, which is convenient for fault diagnosis and maintenance.

[0043] A data encryption module, configured to encrypt the data in the database based on a hash function, and convert the data into a hash value with a fixed length through the hash function to ensure the integrity and security of the data.

[0044] To better demonstrate the usage process of an on-line monitoring sensor for the resistivity of fire-resistant oil, this embodiment provides a control method for an on-line monitoring sensor for the resistivity of fire-resistant oil, including the following steps: Control the sensor to collect data regularly according to a preset periodic sampling frequency, and calculate the resistivity of the fire-resistant oil; Set multiple abnormal feedback levels based on abnormal thresholds, including: setting warning thresholds and danger thresholds, comparing the resistivity of the real-time fire-resistant oil with the set warning threshold and danger threshold respectively to determine whether there is an abnormality and the degree of abnormality, and triggering the corresponding abnormal feedback mechanism; Analyze the current, voltage, temperature signals and resistivity of the fire-resistant oil based on the EIS electrochemical impedance spectroscopy technology, obtain EIS data, and create an impedance spectrogram; Based on the change phenomenon of resistivity, analyze the impedance characteristics of the high-frequency, medium-frequency and low-frequency parts, and judge the relationship between resistivity change and impedance characteristics; Combine the performance of the impedance spectrogram to analyze the electrochemical behavior of the fire-resistant oil; Visually display the voltage, current, temperature and resistivity data, as well as the relationship between the resistivity change and impedance characteristics and the electrochemical behavior of the fire-resistant oil on the human-computer interaction terminal.

[0045] Working principle: Periodically collect the current, voltage and temperature data of the fire-resistant oil at regular intervals of the acquisition frequency and calculate the resistivity; Based on the set warning threshold and danger threshold, compare the resistivity of the real-time fire-resistant oil in real time to determine whether there is an abnormality and trigger the corresponding feedback mechanism. At the same time, based on the EIS electrochemical impedance spectroscopy technology, plot the measured data into an impedance spectrogram, analyze the impedance characteristics of the high-frequency, medium-frequency and low-frequency parts, judge the relationship between resistivity change and impedance characteristics, and combine the impedance spectrogram to analyze the electrochemical behavior of the fire-resistant oil; Visualize the results on the human-computer interaction terminal to provide comprehensive monitoring information for users.

[0046] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0047] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An on-line monitoring sensor for the resistivity of fire-resistant oil, characterized in that The on-line monitoring sensor includes: a signal acquisition unit and a signal analysis unit, and the signal analysis unit includes: a signal calculation module and a characteristic analysis module; The signal acquisition unit is configured to preset a periodic acquisition frequency and regularly acquire the current flowing through the test electrode of the fire-resistant oil, the voltage across the test electrode, and the test temperature; The signal calculation module is configured to determine the distance between the test electrodes and the effective facing area based on the current, voltage, and temperature signals of the fire-resistant oil, and calculate the resistivity of the fire-resistant oil; The characteristic analysis module is configured to analyze the current, voltage, and temperature signals and resistivity of the fire-resistant oil based on the EIS electrochemical impedance spectroscopy technology to obtain EIS data; and generate an impedance spectrogram for judging the relationship between the resistivity change of the fire-resistant oil and the impedance characteristics of the fire-resistant oil, and analyzing the electrochemical behavior of the fire-resistant oil.

2. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 1, characterized in that: The signal calculation module includes: An abnormal threshold module configured to set an abnormal threshold according to the normal resistivity range of the fire-resistant oil; and compare the real-time resistivity of the fire-resistant oil with the abnormal threshold to judge whether the real-time resistivity of the fire-resistant oil is abnormal; An abnormal feedback module configured to trigger an abnormal feedback mechanism if the real-time resistivity of the fire-resistant oil exceeds the abnormal threshold range.

3. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 2, characterized in that: The abnormal feedback module includes: An abnormal level module configured to set multiple abnormal feedback levels based on the abnormal threshold, corresponding to different degrees of abnormal situations respectively; A warning response module configured to set different response strategies based on different abnormal feedback levels.

4. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 1, characterized in that: The characteristic analysis module includes: A current application module configured to input an alternating current signal with adjustable frequency to the test electrode through a galvanostat, analyze the current, voltage, and temperature signals and resistivity of the fire-resistant oil based on the EIS electrochemical impedance spectroscopy technology to obtain EIS data, and generate an impedance spectrogram; for judging the relationship between the resistivity change of the fire-resistant oil and the impedance characteristics of the fire-resistant oil, and analyzing the electrochemical behavior of the fire-resistant oil; An impedance analysis module configured to divide the impedance spectrogram into a high-frequency part, a middle-frequency part, and a low-frequency part, and analyze the impedance characteristics of the high-frequency part and the low-frequency part respectively to obtain the analysis results of each part.

5. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 4, characterized in that: The characteristic analysis module further includes: A relationship analysis module configured to analyze the corresponding phenomena in the high-frequency part, middle-frequency part, and low-frequency part respectively based on the resistivity decrease phenomenon and the resistivity increase phenomenon to obtain the relationship between the resistivity change and the impedance characteristics; An electrochemical analysis module configured to obtain the electrochemical behavior result based on the performance of the high-frequency part, middle-frequency part, and low-frequency part of the impedance spectrogram, combined with the relationship between the resistivity change and the impedance characteristics.

6. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 1, characterized in that: The signal analysis unit further includes: A temperature threshold module configured to analyze the EIS data at different temperatures, evaluate the influence of the electrochemical impedance spectrum of the fire-resistant oil at different temperatures, and preset an ambient temperature threshold; A temperature compensation module configured to monitor the temperature of the test environment in real time, and compare the real-time ambient temperature with the ambient temperature threshold. If the real-time ambient temperature is lower than the ambient temperature threshold, the on-line monitoring sensor is timely temperature-compensated.

7. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 1, characterized in that: The signal acquisition unit includes: A timing acquisition module, configured to set a periodic acquisition mechanism based on a timer, and control an on-line monitoring sensor to perform a signal acquisition task each time the timer is triggered; A data reading module, configured to read the outputs of a voltage measurement, a current measurement, and a temperature sensor based on an analog-to-digital converter, and obtain the voltage across the test electrode, the current flowing through the test electrode, and the temperature of the fire-resistant oil.

8. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 1, characterized in that: The on-line monitoring sensor further includes: A human-computer interaction terminal, configured to visually display the voltage, current, temperature of the fire-resistant oil, and resistivity data based on a mobile terminal; A data transmission module, configured to transmit the voltage, current, temperature of the fire-resistant oil, and resistivity data to the human-computer interaction terminal through a communication interface.

9. The on-line monitoring sensor for the resistivity of fire-resistant oil according to claim 8, characterized in that: The on-line monitoring sensor further includes: A data storage module, configured to store the collected voltage, current, temperature of the fire-resistant oil, and resistivity data in a time series in the human-computer interaction terminal to form a database; A data encryption module, configured to perform encryption processing on the data in the database based on a hash function.

10. A control method for an on-line monitoring sensor of the resistivity of fire-resistant oil, which is implemented based on the on-line monitoring sensor of the resistivity of fire-resistant oil according to any one of claims 1-9, and is characterized in that: Including the following steps: Controlling the on-line monitoring sensor to periodically collect data according to a preset periodic acquisition frequency, and calculating the resistivity of the fire-resistant oil; Setting multiple abnormal feedback levels based on an abnormal threshold, including: setting a warning threshold and a danger threshold, comparing the real-time resistivity of the fire-resistant oil with the set warning threshold and danger threshold respectively to determine whether there is an abnormality and the degree of the abnormality, and triggering a corresponding abnormal feedback mechanism; Analyzing the current, voltage, temperature signal, and resistivity of the fire-resistant oil based on the EIS electrochemical impedance spectroscopy technology to obtain EIS data, and making an impedance spectrogram; Based on the change phenomenon of the resistivity, analyzing the impedance characteristics of the high-frequency, medium-frequency, and low-frequency parts, and judging the relationship between the resistivity change and the impedance characteristics; Combining the performance of the impedance spectrogram to analyze the electrochemical behavior of the fire-resistant oil; Visually displaying the voltage, current, temperature, and resistivity data on the human-computer interaction terminal, as well as the relationship between the resistivity change and the impedance characteristics and the electrochemical behavior of the fire-resistant oil.

Images