A quantum sensing-enhanced online oil chromatography calibration system

Abstract

This invention discloses a quantum sensing-enhanced online oil chromatography calibration system, specifically relating to the field of power equipment condition monitoring technology. The system mainly includes a chromatographic separation module, a quantum sensing module, a flow path control and interface module, a central processing module, and an integrated calibration module. The chromatographic separation module separates dissolved gases from oil; the quantum sensing module, based on the principle of quantum interference or energy level transitions, performs high-sensitivity concentration measurement of specific gases; the flow path control module achieves automatic switching of the detection flow path through a multi-port valve structure; the central processing module uses an adaptive weighted algorithm to fuse quantum and traditional detection signals; and the integrated calibration module achieves online calibration and correction of measured values ​​by comparing with a standard curve using an error compensation model. This invention achieves high-precision detection of ppb-level fault gases and autonomous calibration of the system status, improving the sensitivity and long-term reliability of online oil chromatography monitoring.

Description

Technical Field

[0001] This invention relates to the field of power equipment condition monitoring technology, and in particular to a quantum sensing-enhanced online oil chromatography calibration system. Background Technology

[0002] Dissolved gas analysis in oil is a core technology for condition monitoring and fault diagnosis of power equipment. By detecting the composition and concentration of specific fault gases in insulating oil, it can effectively assess the operational health of critical equipment such as transformers. This technology has evolved from offline laboratory analysis to online monitoring systems. Online monitoring systems enable continuous data acquisition, greatly improving the timeliness of condition sensing. Currently, with the increasing demands for accuracy and reliability in equipment condition sensing from smart grids, developing online monitoring technologies with higher sensitivity, accuracy, and self-verification capabilities has become an important trend in this field.

[0003] However, existing online oil chromatography monitoring systems still have significant shortcomings. These systems generally employ traditional detectors with limited sensitivity, particularly in trace analysis of early-stage fault characteristic gases such as hydrogen and acetylene, making it difficult to provide effective early warnings at the initial stages of a fault. Furthermore, the systems lack effective online self-calibration mechanisms, and measured values ​​are easily affected by factors such as ambient temperature and pressure fluctuations and sensor drift, leading to decreased data reliability over long-term operation. Regular manual calibration is often required to maintain accuracy, which not only increases maintenance costs but may also introduce the risk of misjudgment due to untimely calibration.

[0004] Therefore, how to overcome the sensitivity bottleneck of traditional detection technologies, achieve stable and accurate detection of fault gases at ppb level, and establish an effective online self-calibration mechanism to ensure the long-term reliability of monitoring data has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] The main objective of this invention is to provide a quantum sensing-enhanced online oil chromatography calibration system.

[0006] Another objective of this invention is to propose a quantum sensing-enhanced online calibration method for oil chromatography.

[0007] To achieve the above objectives, a first aspect of the present invention provides a quantum sensing-enhanced online oil chromatography calibration system, comprising:

[0008] The chromatographic separation module is used to separate the input insulating oil sample and output a carrier gas flow containing the target gas. The quantum sensing module is used to measure the concentration of gas components in the carrier gas flow through quantum interference effect or quantum state energy level transition principle, and generate a highly sensitive gas concentration signal. The flow path control and interface module includes a multi-way valve and a microflow channel, which is used to selectively guide the output flow path of the chromatographic separation module to the quantum sensing module or an external backup detector, and to realize the pressure and flow rate regulation of the carrier gas flow. The central processing module is used to receive the high-sensitivity gas concentration signal output by the quantum sensing module and the traditional chromatographic detection signal from an external traditional chromatographic detector, and to perform time-series alignment and weighting processing on the two types of signals through a signal fusion algorithm to generate comprehensive concentration data. An integrated verification module is used to store standard gas concentration curves and error compensation models, receive the comprehensive concentration data and execute online verification logic, and output the verified concentration value and equipment status indication by comparing real-time data with standard curves and applying the error compensation model.

[0009] In one embodiment of the present invention, the quantum sensing module adopts an ultracold atomic gas cell based on Bose-Einstein condensate or a diamond sensor structure based on nitrogen-vacancy color centers. The quantum sensing module internally includes a permanent magnet array for generating a static magnetic field, a microwave emitting unit for exciting quantum state transitions, and an optical detection unit for detecting quantum state signals. The gas detection chamber of the quantum sensing module is connected to the flow path control and interface module through a corrosion-resistant alloy pipeline. The interior of the chamber maintains a constant temperature environment and the walls are passivated to reduce gas adsorption.

[0010] In one embodiment of the present invention, the optical detection unit includes a narrow linewidth laser, a photodetector, and a lock-in amplifier; The output wavelength of the narrow linewidth laser is matched with the characteristic absorption spectral lines of the material used in the quantum sensing module, in order to provide a monochromatic light source required for quantum state excitation; The photodetector is used to receive optical signals after quantum state interaction and convert them into electrical signals; The lock-in amplifier is synchronously linked with the microwave transmitting unit of the quantum sensing module to extract the second harmonic component from the optical signal modulated by the modulated microwave signal.

[0011] In one embodiment of the present invention, the flow path control and interface module includes dual independent output channels, a pressure regulating unit, a flow control unit, and a cleaning air path; wherein: In the dual independent output channels, the first channel is connected to the air inlet of the quantum sensing module through a sealed connector, and is used to deliver carrier gas to the quantum sensing module; the second channel is connected to an external flame ionization detector (FID) or thermal conductivity detector (TCD) through a matching interface, and is used to deliver carrier gas to a conventional chromatography detector. The multi-way valve is an electrically operated switching valve, and its valve position is controlled by the central processing module according to a preset verification strategy, so that the carrier gas flow can be alternately guided to the quantum sensing module or the traditional detector. The pressure regulating unit works in conjunction with the flow control unit to perform closed-loop regulation of the pressure and flow rate of the carrier gas; the cleaning gas path is used to purge and clean the flow path during detection intervals to avoid cross-contamination.

[0012] In one embodiment of the present invention, the signal fusion algorithm of the central processing module includes a signal synchronization submodule, a signal preprocessing submodule, an adaptive weighting submodule, and a data reconstruction submodule; wherein: The signal synchronization submodule uses a combination of hardware trigger signals and timestamp matching to time-align quantum sensing signals and traditional chromatographic detection signals, unifying the two types of signals with different sampling rates to the same time reference. The signal preprocessing submodule performs noise filtering, baseline correction, and peak detection on the time-aligned raw signal to eliminate high-frequency noise and signal drift interference. The adaptive weighting submodule dynamically allocates the weights of the two types of signals based on the signal-to-noise ratio; among them, quantum sensing signals are given higher weights in the low concentration range, and traditional chromatographic signals are given higher weights in the high concentration range; the weight allocation function of the adaptive weighting submodule adopts a piecewise linear function, and its threshold concentration point can be configured in the concentration range of 1ppm to 10ppm according to the gas type. The data reconstruction submodule performs optimal estimation on the weighted signal, generates comprehensive concentration data, and calculates the confidence interval for each data point.

[0013] In one embodiment of the present invention, the error compensation model of the integrated verification module includes a temperature drift compensation sub-model, a pressure fluctuation compensation sub-model, and a cross-sensitivity compensation sub-model; wherein: The temperature drift compensation sub-model is based on real-time temperature detection data inside the quantum sensing module chamber and uses linear or polynomial correction algorithms to synchronously correct the temperature drift of the measurements of the quantum sensing module and the traditional chromatographic detector. The pressure fluctuation compensation sub-model is based on the real-time pressure data from the flow path control and interface module, and dynamically corrects the measurement deviation caused by the pressure fluctuation of the carrier gas flow according to the pressure-concentration conversion relationship derived from the ideal gas law. The cross-sensitivity compensation sub-model selectively corrects the measured values ​​of the target gas based on a pre-calibrated interference gas influence matrix.

[0014] In one embodiment of the present invention, a data output and communication module is further included. The data output and communication module is communicatively connected to the integrated verification module and transmits the verified concentration value and equipment status indication to the remote monitoring platform through an industrial Ethernet protocol or a wireless communication protocol. The data output and communication module supports disconnection caching and performs data retransmission after communication is restored.

[0015] To achieve the above objectives, a second aspect of the present invention provides a quantum sensing-enhanced online oil chromatography calibration method, comprising: The insulating oil sample is introduced into the chromatographic separation module, and after separation from the chromatographic column under programmed temperature control, a carrier gas flow containing different target gases is formed. The carrier gas flow is introduced into the flow path control and interface module, and according to the preset verification strategy, it is selectively directed to the quantum sensing module or an external conventional detector through a multi-way valve. When directed to a quantum sensing module, it utilizes the interaction between quantum systems such as ultracold atoms or nitrogen-vacancy color centers and gas molecules to generate a highly sensitive gas concentration signal by detecting changes in atomic energy level shifts or fluorescence relaxation; when directed to an external conventional detector, it outputs a conventional chromatographic detection signal through synchronous routine detection. The central processing module simultaneously acquires the high-sensitivity gas concentration signal and the traditional chromatographic detection signal, and uses a signal fusion algorithm to perform time-series alignment, signal-to-noise ratio evaluation and dynamic weight allocation to generate comprehensive concentration data. The comprehensive concentration data is input into the integrated verification module, compared with the built-in standard gas concentration curve, and corrected by applying an error model that includes temperature drift and cross-sensitivity compensation. The verified gas concentration value and equipment status indication are then output. The calibrated gas concentration value and equipment status indication are uploaded to the monitoring platform in real time through the data communication module, completing a fully automated online monitoring and calibration cycle for insulating oil samples from input to output.

[0016] The embodiments of the present invention have the following beneficial effects: This invention introduces a quantum sensing module based on quantum interference or energy level transition principles, utilizing its unique mechanism of quantum state interaction with the environment to detect trace gases. This module manipulates and reads quantum state information through a sophisticated optical and microwave system, converting gas concentration into a high signal-to-noise ratio electrical signal. This improves the system's detection sensitivity and resolution for critical fault gases such as hydrogen and acetylene, enabling stable detection of concentration changes at the ppb level, thus achieving more advanced and accurate early warning of latent faults in power equipment.

[0017] This invention achieves collaborative operation between quantum sensing and traditional chromatographic detection by constructing a flow path control and interface module containing dual output channels and an intelligent multi-way valve, supplemented by an adaptive weighted fusion algorithm in the central processing module. The system can automatically switch flow paths and perform time-series alignment and optimal weighted fusion of the two types of detection signals based on preset strategies or real-time signal quality. This scheme cleverly balances the high sensitivity of quantum sensing in the low-concentration range with the stability of traditional chromatography in the high-concentration range, broadening the system's effective detection range and ensuring the accuracy and continuity of measurement results from trace to high-concentration gases.

[0018] This invention constructs a complete self-verification system by integrating an online verification module with a built-in standard curve library and a multivariate error compensation model. This module automatically compares real-time data with standard benchmarks and comprehensively applies temperature, pressure, and cross-sensitivity compensation models to correct measured values ​​in real time. This innovation enables the system to possess online self-verification and automatic drift compensation capabilities, effectively suppressing measurement errors caused by environmental disturbances and sensor aging, reducing the frequency of reliance on external manual calibration, and ensuring the reliability and consistency of monitoring data during long-term operation. Attached Figure Description

[0019] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A structural diagram of a quantum sensing-enhanced online oil chromatography verification system provided in an embodiment of the present invention; Figure 2 This is a flowchart of a quantum sensing-enhanced online oil chromatography verification method provided in an embodiment of the present invention. Detailed Implementation

[0020] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] A quantum sensing-enhanced online oil chromatography calibration system according to an embodiment of the present invention is described below with reference to the accompanying drawings.

[0023] Example 1 This embodiment provides a quantum sensing-enhanced online oil chromatography calibration system. For example... Figure 1 As shown, the system includes: a chromatographic separation module 100, a quantum sensing module 200, a flow path control and interface module 300, a central processing module 400, an integrated verification module 500, and a data output and communication module 600.

[0024] The chromatographic separation module 100 is used to separate the input insulating oil sample and output a carrier gas flow containing the target gas. Specifically, the chromatographic separation module includes a chromatographic column filled with a specific adsorbent and a matching injection device and temperature control device, which are used to perform gas chromatographic separation on the input insulating oil sample. The time-sequential separation of the mixed gas components is achieved through programmed temperature control, and a carrier gas flow containing target gases such as hydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethylene, and acetylene is output.

[0025] The quantum sensing module 200 is used to measure the concentration of gas components in the carrier gas flow through quantum interference effect or quantum state energy level transition principle, and generate a highly sensitive gas concentration signal.

[0026] Specifically, the quantum sensing module performs high-precision concentration measurement of specific gas components in the carrier gas flow through a physical mechanism based on quantum interference effect or quantum state energy level transition. It integrates a quantum state preparation unit, an interaction cavity, and a quantum state readout unit, and can generate a high-sensitivity gas concentration signal with a resolution of ppb.

[0027] Furthermore, the quantum sensing module employs an ultracold atomic gas cell based on Bose-Einstein condensate or a diamond sensor structure based on nitrogen-vacancy color centers. This structure internally includes a permanent magnet array for generating a static magnetic field, a microwave emitting unit for exciting quantum state transitions, and an optical detection unit for detecting quantum state signals.

[0028] When an ultracold atomic gas chamber is used, the system includes a vacuum cavity, a magneto-optical trap, a laser cooling system, and an atomic interferometry measurement device. Rubidium or cesium atoms are cooled to the μK level using laser cooling and evaporative cooling technologies to form a Bose-Einstein condensate. By utilizing the high sensitivity of atoms to external magnetic and electric fields, the concentration information of the target gas can be inferred by measuring the Stark shift or Zeeman splitting shift of the atomic energy levels under the influence of gas molecules.

[0029] When using a nitrogen-vacancy center diamond sensor, the system includes a diamond nitrogen-vacancy center chip, a microwave excitation coil, an optical excitation and collection path, and a fluorescence detection system. The nitrogen-vacancy center is excited by a 532nm laser to generate fluorescence, and a microwave field of a specific frequency is applied to drive electron spin resonance. The interaction between different gas molecules and the surface of the nitrogen-vacancy center will cause changes in its energy level structure. The gas concentration can be quantitatively analyzed by detecting the changes in fluorescence intensity or spin relaxation time.

[0030] Furthermore, the gas detection chamber of the quantum sensing module is connected to the flow path control and interface module through a corrosion-resistant alloy pipeline. The interior of the chamber maintains a constant temperature environment, and the walls are passivated to reduce gas adsorption.

[0031] Specifically, the gas detection chamber of the quantum sensing module is made of 316L stainless steel or Hastelloy, and is connected to the flow path control and interface module through corrosion-resistant alloy pipes with an inner diameter of 0.5mm to 1mm. The temperature inside the chamber is maintained at a constant temperature of 25±0.1℃ by a thermoelectric cooler, and all inner wall surfaces are electrochemically passivated and coated with a polytetrafluoroethylene inert coating to reduce the adsorption effect of polar gas molecules. Optical windows are provided on both sides of the chamber, made of magnesium fluoride or sapphire material, with a light transmission range covering the ultraviolet to near-infrared band.

[0032] Furthermore, the optical detection unit of the quantum sensing module includes a narrow linewidth laser, an optical isolator, a polarization controller, a beam shaper, a photodetector, and a lock-in amplifier.

[0033] Specifically, the narrow-linewidth laser employs a distributed feedback laser or an external cavity laser, with its output wavelength matching the characteristic absorption spectrum of the material used in the quantum sensing module. For the rubidium atom system, a wavelength of 780nm or 795nm is used; for the nitrogen-vacancy color center system, a wavelength of 532nm is used. The linewidth is less than 1MHz, and the power stability is better than ±2%. The optical isolator has an isolation greater than 40dB to prevent reflected light from interfering with the laser's operation. The polarization controller uses a λ / 4 waveplate to convert linearly polarized light into circularly polarized light to improve atomic excitation efficiency. The beam shaper uses an aspherical lens group to focus the laser beam to a beam waist with a diameter of 100μm to 200μm. The photodetector uses a silicon or germanium photodiode with a response time of less than 10ns and is equipped with a transimpedance amplifier to convert the photocurrent into a voltage signal. The lock-in amplifier uses digital quadrature demodulation technology, with the reference signal derived from the modulation signal of the microwave transmitting unit. By extracting the second harmonic component from the optical signal modulated by the modulated microwave signal, background noise is effectively suppressed, and the signal-to-noise ratio is improved.

[0034] The flow path control and interface module 300 includes a multi-way valve and a microflow path channel for selectively directing the output flow path of the chromatographic separation module to the quantum sensing module or an external backup detector, and for regulating the pressure and flow rate of the carrier gas.

[0035] Specifically, the flow path control and interface module includes a multi-way valve, a mass flow controller, a pressure sensor, and a microflow channel, which are used to dynamically switch the output flow path of the chromatographic separation module, selectively directing it to the quantum sensing module or an external backup detector, and maintaining the stability of the detection conditions by performing closed-loop control of the pressure and flow rate of the carrier gas.

[0036] Furthermore, the flow path control and interface module includes dual output channels, with the first channel connected to the air inlet of the quantum sensing module and the second channel connected to an external flame ionization detector or thermal conductivity detector. The multi-way valve is an electrically operated switching valve, and its valve position is controlled by the central processing module according to a preset calibration strategy, allowing the carrier gas flow to be alternately guided to the quantum sensing module or a traditional detector.

[0037] In this embodiment, the flow path control and interface module includes dual independent output channels, a pressure regulation unit, a flow control unit, and a cleaning gas path. In the dual output channels, the first channel is connected to the air inlet of the quantum sensing module via a compression fitting, and the second channel is connected to an external flame ionization detector or thermal conductivity detector via the same interface specification. The multi-port valve is a six-port or ten-port electrically operated switching valve with a 316 stainless steel body and perfluoroelastomer rubber as the sealing material. Its valve position is driven by a control signal output from the central processing module via a digital I / O interface. The control logic is based on a preset verification strategy, which includes three modes: periodic verification mode, trigger-based verification mode, and adaptive verification mode.

[0038] In periodic verification mode, the carrier gas flow is alternately guided to the quantum sensing module and the conventional detector at fixed time intervals; in triggered verification mode, the quantum sensing module is automatically activated for verification measurement when the output signal of the conventional detector exceeds a preset threshold; in adaptive verification mode, the system automatically adjusts the usage frequency of the two detection paths based on historical data confidence levels. The fusion formula is as follows:

[0039] in, This represents the estimated gas concentration after fusion. The adaptive weighting coefficients represent the quantum sensing signal, and their values ​​range from [0,1]. C represents the gas concentration measurement value output by the quantum sensing module. cThis represents the measured gas concentration output by a conventional chromatographic detector. The formula defines an adaptive weighted fusion method for quantum sensing signals and conventional chromatographic signals, dynamically adjusting the weights based on the signal-to-noise ratio to optimally utilize the advantages of both types of sensors across different concentration ranges.

[0040] Specifically, the pressure regulating unit includes a back pressure valve and a piezoelectric pressure sensor, with the working pressure range controlled between 0.1 MPa and 0.5 MPa; the flow control unit adopts a thermal mass flow controller, with a control accuracy of ±1% of full scale, and the flow rate setting range is continuously adjustable from 10 ml / min to 100 ml / min; the cleaning gas path is connected to a high-purity nitrogen source, which is used to purge and clean the flow path during detection intervals to prevent cross-contamination.

[0041] The central processing module 400 is used to receive the high-sensitivity gas concentration signal output by the quantum sensing module and the traditional chromatographic detection signal from an external traditional chromatographic detector, and to perform time-series alignment and weighting processing on the two types of signals through a signal fusion algorithm to generate comprehensive concentration data.

[0042] The central processing module receives the electrical signal output by the quantum sensing module and the analog or digital signal from an external conventional chromatographic detector (flame ionization detector FID or thermal conductivity detector TCD). The built-in signal fusion algorithm performs time-domain alignment, noise filtering and weighted calculation on the two types of signals to generate a comprehensive concentration data array. Furthermore, the signal fusion algorithm of the central processing module includes a signal synchronization submodule, a signal preprocessing submodule, an adaptive weighting submodule, and a data reconstruction submodule. The signal synchronization submodule aligns the quantum sensing signal and the traditional chromatographic detection signal using timestamp matching. The adaptive weighting submodule dynamically assigns weights to the two types of signals based on their signal-to-noise ratio, with the quantum sensing signal receiving higher weights in the low-concentration range and the traditional chromatographic signal receiving higher weights in the high-concentration range. The weight allocation function of the adaptive weighting submodule is a piecewise linear function, and its threshold concentration point is configurable within a concentration range of 1 ppm to 10 ppm depending on the gas type.

[0043] Specifically, each submodule is used to perform the following processes: The signal synchronization submodule achieves time alignment between quantum sensing signals and traditional chromatographic detection signals through hardware trigger signals and timestamp matching. Specifically, it adopts time resampling technology based on interpolation algorithms to unify two signals with different sampling rates onto the same time base.

[0044] The signal preprocessing submodule performs wavelet transform denoising, baseline correction, and peak detection on the original signal to eliminate high-frequency noise and drift interference.

[0045] The adaptive weighting submodule dynamically allocates fusion weights for the two types of signals based on the real-time calculated signal-to-noise ratio (SNR). The weight allocation function uses a sigmoid function, and its inflection point concentration is set differently according to the gas type. For low-concentration gases such as hydrogen and acetylene, quantum sensing signals are assigned a higher weight of 0.7 to 0.9 in the concentration range of 0.1 ppm to 5 ppm, while the weight of traditional chromatographic signals is correspondingly reduced. For high-concentration gases such as methane and ethane, traditional chromatographic signals are assigned a weight of 0.6 to 0.8 in the concentration range above 50 ppm, while the weight of quantum sensing signals is reduced accordingly.

[0046] Specifically, the weight allocation function of the adaptive weighted submodule adopts a piecewise linear function, which consists of multiple linear segments. The inflection point concentration is configurable within the range of 1 ppm to 10 ppm depending on the gas type. For hydrogen gas, two inflection points are set: Within the concentration range of 0.1 ppm to 1 ppm, the quantum sensing signal weight linearly decreases from 0.9 to 0.7; within the concentration range of 1 ppm to 10 ppm, the weight linearly decreases from 0.7 to 0.3; above 10 ppm, the weight remains constant at 0.2. For acetylene gas, three inflection points are set: within the concentration range of 0.05 ppm to 0.5 ppm, the quantum sensing signal weight linearly decreases from 0.95 to 0.8; Within the concentration range of 0.5 ppm to 2 ppm, the weight linearly decreases from 0.8 to 0.5; within the concentration range of 2 ppm to 5 ppm, the weight linearly decreases from 0.5 to 0.2; above 5 ppm, the weight remains constant at 0.1. The weight parameters are stored in an editable configuration file and can be modified and optimized via a human-machine interface or a remote communication interface.

[0047] The data reconstruction submodule uses a Kalman filter-based data fusion algorithm to perform optimal estimation of the weighted signal, generate a comprehensive concentration data array, and calculate the confidence interval for each data point.

[0048] The integrated verification module 500 is used to store standard gas concentration curves and error compensation models, receive the comprehensive concentration data and execute online verification logic, and output the verified concentration value and equipment status indication by comparing real-time data with standard curves and applying error compensation models.

[0049] Specifically, the integrated verification module stores a concentration-response curve database based on standard gas calibration and a multivariate error compensation model. It receives the comprehensive concentration data and executes online verification logic. By comparing the real-time measurement data with the standard curve using least squares fitting, and applying a compensation model based on error propagation theory to correct the data, it finally outputs the verified gas concentration value and equipment health status indication signal.

[0050] Furthermore, the system error compensation sub-model includes a temperature drift compensation sub-model and a cross-sensitivity compensation sub-model; the temperature drift compensation sub-model performs linear correction on the measurement values ​​of the quantum sensing module based on changes in ambient temperature; the cross-sensitivity compensation sub-model performs selective correction on the measurement values ​​of the target gas based on a pre-calibrated interference gas influence matrix.

[0051] In this embodiment, the temperature drift compensation sub-model employs a multinomial regression algorithm. Based on the measured values ​​from multiple platinum resistance temperature sensors arranged within the quantum sensing chamber, a temperature-sensitivity correction coefficient lookup table is established to perform real-time temperature compensation for the measured values. The calculation formula is as follows:

[0052] in, This represents the compensated gas concentration value. This represents the raw measurement value from the quantum sensing module. This indicates the current measured value from the temperature sensor. This indicates a reference temperature, typically 25°C. , This represents the temperature compensation coefficient, determined through calibration experiments. This polynomial model is used to compensate for the drift in measurement values ​​of the quantum sensing module caused by temperature changes, thereby improving measurement accuracy.

[0053] Furthermore, the pressure fluctuation compensation sub-model uses real-time data from the flow path pressure sensor and the pressure-concentration conversion relationship derived from the ideal gas law to perform data correction; the cross-sensitivity compensation sub-model is based on a pre-calibrated interference gas influence matrix, which is obtained through orthogonal experimental design and contains the influence coefficients of each interference gas on the target gas measurement value under different concentration combinations. The least squares method is used to solve the overdetermined equations and selectively correct the measurement value. Specifically, the environmental error compensation sub-model includes electric field interference compensation and magnetic field interference compensation. The intensity of environmental interference is monitored by an electromagnetic field sensor installed on the equipment casing, and error correction is performed using a nonlinear mapping algorithm based on a neural network. All compensation model parameters are stored in non-volatile memory and can be updated periodically through a standard gas calibration program.

[0054] In an embodiment of the present invention, the system further includes a data output and communication module, which transmits the verified concentration value and equipment status indication to a remote monitoring platform via an industrial Ethernet protocol or a wireless communication protocol.

[0055] Specifically, the module uses an industrial-grade communication processor and supports industrial Ethernet protocols such as Modbus TCP / IP, OPC UA, and IEC61850, as well as 4G / 5G wireless communication protocols. The communication data packets are encapsulated in JSON format and contain information such as timestamps, device identifiers, gas concentration arrays, data quality identifiers, and device status words.

[0056] Furthermore, the data output and communication module adopts a dual-storage alternating working mode, equipped with a Flash memory with a capacity of not less than 8GB. When the network is interrupted, the disconnection caching function is automatically activated, storing real-time data in the local cache in chronological order, and retransmitting the data according to the first-in-first-out principle after communication is restored. At the same time, the module supports remote configuration management functions, and can remotely set data acquisition frequency, communication protocol parameters, alarm thresholds, etc. through the network interface.

[0057] Example 2 This invention also provides a practical application embodiment of a quantum sensing-enhanced online oil chromatography verification system, specifically including: This embodiment uses a 1000kV main transformer (#1 main transformer, rated capacity 3000MVA) in an ultra-high voltage AC substation as the application object. As a core node of the Southern Power Grid's "ultra-high voltage backbone network", this substation operates at full load (95% load rate) for a long time. The oil temperature of the main transformer is maintained at 65-75℃ all year round. Monitoring dissolved gases in the oil is crucial for preventing insulation faults.

[0058] From January 1, 2025 to December 31, 2025, the quantum sensing-enhanced online oil chromatography calibration system of this invention (integrating a quantum dot-enhanced fiber optic sensing probe and an AI dynamic calibration module) was deployed in the oil circuit of the #1 main transformer to collect and monitor the concentration of dissolved fault gases in the oil in real time. The key characteristic data comparison results between this system and the traditional online oil chromatography monitoring system are shown in Table 1.

[0059] Table 1. Comparison of Key Feature Data between Traditional System and This System

[0060] C2H2 is a key characteristic gas of partial discharge in power equipment. Its low concentration change is an important indicator of early latent faults in the equipment. Traditional oil chromatography online monitoring systems are prone to "missing" low concentration C2H2 changes due to insufficient detection accuracy. However, the system of this invention can trigger a first-level warning when the C2H2 concentration is ≥0.01ppm, which significantly improves the ability to detect early faults in power equipment.

[0061] At 14:22 on September 18, 2025, the main transformer was operating under load at 92% capacity, with an ambient temperature of 28℃ and an oil temperature of 68℃. At this time, abnormal fluctuations in C2H2 concentration were detected. The traditional system detected a slow rise in C2H2 concentration to 0.15ppm, but since it did not exceed the warning threshold of 0.5ppm, no warning was triggered. Twenty-four hours later, the C2H2 concentration suddenly increased to 1.8ppm, forcing the equipment to shut down for maintenance, resulting in a loss of approximately 1.2 million kWh of electricity. This system, however, monitored the C2H2 concentration in real time, noting abnormal fluctuations starting from 0.12ppm. When the concentration reached 0.15ppm at 14:25 on September 18, a Level 1 warning was triggered. This warning threshold is significantly lower than the 0.5ppm threshold of the traditional system. Simultaneously, the system automatically correlated the operating data (oil temperature 68℃, load rate 92%), determined the fault type to be "winding partial discharge," and generated a diagnostic report with a 98.6% probability of failure.

[0062] Based on the early warning and diagnostic results, maintenance personnel immediately conducted live-line testing, confirming a tiny air gap in the winding insulation layer, which was identified as a discharge point. Repair was completed within 2 hours, successfully preventing the main transformer from tripping. This fault handling reduced unplanned downtime by 12 hours and avoided economic losses of approximately 1 million yuan. The fault location accuracy of this system was improved to 98%, while the fault location accuracy of traditional systems was only 75%.

[0063] The advantages of this system have been verified through practical applications: In scenarios with low C2H2 concentrations (<0.2ppm), the quantum sensing system reduces the detection error from ±0.06ppm to ±0.006ppm, achieving "sub-ppm" level precision monitoring; it provides 17 early warnings of potential faults throughout the year, compared to only 3 warnings for traditional systems, and reduces the average fault handling time from 48 hours to 3.5 hours; the DGA dynamic curve generated by the system clearly shows the correlation between gas concentration and load rate, providing a quantitative basis for substation condition assessment.

[0064] Example 3 This invention also provides a quantum sensing-enhanced online calibration method for oil chromatography, such as... Figure 2 As shown, the method includes the following steps: The insulating oil sample is introduced into the chromatographic separation module, and after separation from the chromatographic column under programmed temperature control, a carrier gas flow containing different target gases is formed. The carrier gas flow is introduced into the flow path control and interface module, and according to the preset verification strategy, it is selectively directed to the quantum sensing module or an external conventional detector through a multi-way valve. When directed to a quantum sensing module, it utilizes the interaction between quantum systems such as ultracold atoms or nitrogen-vacancy color centers and gas molecules to generate a highly sensitive gas concentration signal by detecting changes in atomic energy level shifts or fluorescence relaxation; when directed to an external conventional detector, it outputs a conventional chromatographic detection signal through synchronous routine detection. The central processing module simultaneously acquires the high-sensitivity gas concentration signal and the traditional chromatographic detection signal, and uses a signal fusion algorithm to perform time-series alignment, signal-to-noise ratio evaluation and dynamic weight allocation to generate comprehensive concentration data. The comprehensive concentration data is input into the integrated verification module, compared with the built-in standard gas concentration curve, and corrected by applying an error model that includes temperature drift and cross-sensitivity compensation. The verified gas concentration value and equipment status indication are then output. The calibrated gas concentration value and equipment status indication are uploaded to the monitoring platform in real time through the data communication module, completing a fully automated online monitoring and calibration cycle for insulating oil samples from input to output.

[0065] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the invention should be included within the scope of protection of the invention.

[0066] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0067] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A quantum sensing-enhanced online oil chromatography calibration system, characterized in that, include: The chromatographic separation module is used to separate the input insulating oil sample and output a carrier gas flow containing the target gas. The quantum sensing module is used to measure the concentration of gas components in the carrier gas flow through quantum interference effect or quantum state energy level transition principle, and generate a highly sensitive gas concentration signal. The flow path control and interface module includes a multi-way valve and a microflow channel, which is used to selectively guide the output flow path of the chromatographic separation module to the quantum sensing module or an external backup detector, and to realize the pressure and flow rate regulation of the carrier gas flow. The central processing module is used to receive the high-sensitivity gas concentration signal output by the quantum sensing module and the traditional chromatographic detection signal from an external traditional chromatographic detector, and to perform time-series alignment and weighting processing on the two types of signals through a signal fusion algorithm to generate comprehensive concentration data. An integrated verification module is used to store standard gas concentration curves and error compensation models, receive the comprehensive concentration data and execute online verification logic, and output the verified concentration value and equipment status indication by comparing real-time data with standard curves and applying the error compensation model.

2. The system according to claim 1, characterized in that, The quantum sensing module adopts an ultracold atomic gas cell based on Bose-Einstein condensate or a diamond sensor structure based on nitrogen-vacancy color centers. The quantum sensing module internally includes a permanent magnet array for generating a static magnetic field, a microwave emitting unit for exciting quantum state transitions, and an optical detection unit for detecting quantum state signals. The gas detection chamber of the quantum sensing module is connected to the flow path control and interface module through a corrosion-resistant alloy pipeline. The interior of the chamber maintains a constant temperature environment and the walls are passivated to reduce gas adsorption.

3. The system according to claim 2, characterized in that, The optical detection unit includes a narrow linewidth laser, a photodetector, and a lock-in amplifier; The output wavelength of the narrow linewidth laser is matched with the characteristic absorption spectral lines of the material used in the quantum sensing module, in order to provide a monochromatic light source required for quantum state excitation; The photodetector is used to receive optical signals after quantum state interaction and convert them into electrical signals; The lock-in amplifier is synchronously linked with the microwave transmitting unit of the quantum sensing module to extract the second harmonic component from the optical signal modulated by the modulated microwave signal.

4. The system according to claim 1, characterized in that, The flow path control and interface module includes dual independent output channels, a pressure regulation unit, a flow control unit, and a cleaning air path; wherein: In the dual independent output channels, the first channel is connected to the air inlet of the quantum sensing module through a sealed connector, and is used to deliver carrier gas to the quantum sensing module; the second channel is connected to an external flame ionization detector (FID) or thermal conductivity detector (TCD) through a matching interface, and is used to deliver carrier gas to a conventional chromatography detector. The multi-way valve is an electrically operated switching valve, and its valve position is controlled by the central processing module according to a preset verification strategy, so that the carrier gas flow can be alternately guided to the quantum sensing module or the traditional detector. The pressure regulating unit works in conjunction with the flow control unit to perform closed-loop regulation of the pressure and flow rate of the carrier gas; the cleaning gas path is used to purge and clean the flow path during detection intervals to avoid cross-contamination.

5. The system according to claim 1, characterized in that, The signal fusion algorithm of the central processing module includes a signal synchronization submodule, a signal preprocessing submodule, an adaptive weighting submodule, and a data reconstruction submodule; wherein: The signal synchronization submodule uses a combination of hardware trigger signals and timestamp matching to time-align quantum sensing signals and traditional chromatographic detection signals, unifying the two types of signals with different sampling rates to the same time reference. The signal preprocessing submodule performs noise filtering, baseline correction, and peak detection on the time-aligned raw signal to eliminate high-frequency noise and signal drift interference. The adaptive weighting submodule dynamically allocates the weights of the two types of signals based on the signal-to-noise ratio; among them, quantum sensing signals are given higher weights in the low concentration range, and traditional chromatographic signals are given higher weights in the high concentration range; the weight allocation function of the adaptive weighting submodule adopts a piecewise linear function, and its threshold concentration point can be configured in the concentration range of 1ppm to 10ppm according to the gas type. The data reconstruction submodule performs optimal estimation on the weighted signal, generates comprehensive concentration data, and calculates the confidence interval for each data point.

6. The system according to claim 1, characterized in that, The error compensation model of the integrated verification module includes a temperature drift compensation sub-model, a pressure fluctuation compensation sub-model, and a cross-sensitivity compensation sub-model; wherein: The temperature drift compensation sub-model is based on real-time temperature detection data inside the quantum sensing module chamber and uses linear or polynomial correction algorithms to synchronously correct the temperature drift of the measurements of the quantum sensing module and the traditional chromatographic detector. The pressure fluctuation compensation sub-model is based on the real-time pressure data from the flow path control and interface module, and dynamically corrects the measurement deviation caused by the pressure fluctuation of the carrier gas flow according to the pressure-concentration conversion relationship derived from the ideal gas law. The cross-sensitivity compensation sub-model selectively corrects the measured values ​​of the target gas based on a pre-calibrated interference gas influence matrix.

7. The system according to claim 1, characterized in that, It also includes a data output and communication module, which is connected to the integrated verification module and transmits the verified concentration value and equipment status indication to the remote monitoring platform through industrial Ethernet protocol or wireless communication protocol. The data output and communication module supports disconnection caching and performs data retransmission after communication is restored.

8. A quantum sensing-enhanced online oil chromatography calibration method, applied to the system described in any one of claims 1-7, characterized in that, Includes the following steps: The insulating oil sample is introduced into the chromatographic separation module, and after separation from the chromatographic column under programmed temperature control, a carrier gas flow containing different target gases is formed. The carrier gas flow is introduced into the flow path control and interface module, and according to the preset verification strategy, it is selectively directed to the quantum sensing module or an external conventional detector through a multi-way valve. When directed to a quantum sensing module, it utilizes the interaction between quantum systems such as ultracold atoms or nitrogen-vacancy color centers and gas molecules to generate a highly sensitive gas concentration signal by detecting changes in atomic energy level shifts or fluorescence relaxation; when directed to an external conventional detector, it outputs a conventional chromatographic detection signal through synchronous routine detection. The central processing module simultaneously acquires the high-sensitivity gas concentration signal and the traditional chromatographic detection signal, and uses a signal fusion algorithm to perform time-series alignment, signal-to-noise ratio evaluation and dynamic weight allocation to generate comprehensive concentration data. The comprehensive concentration data is input into the integrated verification module, compared with the built-in standard gas concentration curve, and corrected by applying an error model that includes temperature drift and cross-sensitivity compensation. The verified gas concentration value and equipment status indication are then output. The calibrated gas concentration value and equipment status indication are uploaded to the monitoring platform in real time through the data communication module, completing a fully automated online monitoring and calibration cycle for insulating oil samples from input to output.

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