A method and system for VOCs quality control

Abstract

The application provides a VOCs quality control method and system, relating to the technical field of environmental monitoring and analysis testing. The method integrates a full-link quality control framework of sampling quality control-pre-treatment quality control-analysis quality control-data quality control. Through real-time monitoring of sampling end flow / pressure / leakage, dynamic blank baseline establishment, humidity-adjustable multi-point calibration, memory effect index (MBI) evaluation, enrichment efficiency online estimation, retention time-separation degree linkage control, state machine out-of-limit disposal, and data rule library review, an unalterable QC label is generated. The method significantly reduces quantitative deviation under humidity and load fluctuation, realizes quantitative evaluation and automatic disposal of memory effect, improves online diagnosis capability of enrichment efficiency, and reduces dependence on manual maintenance. The system includes a sampling quality control module, a humidity-adjustable standard source, a dynamic blank and enrichment unit, a penetration monitoring and a controller, supports vehicle / carried mobile monitoring scenes, and meets vibration and salt spray environment requirements.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring and analysis testing technology, specifically to a VOCs quality control method and system, which is compatible with monitoring platforms such as thermal desorption-gas chromatography-mass spectrometry / flame ionization (TD-GC-MS / FID), canister sampling-GC-MS, and portable PID / IMS, and is applicable to both fixed-station and mobile monitoring scenarios. Background Technology

[0002] Existing online and offline VOCs monitoring often encounters the following problems in actual operation: (1) response factor drift due to changes in ambient humidity; (2) memory effect and blank residue of sampling / enrichment units; (3) unstable enrichment efficiency caused by adsorption-desorption and pipeline cold spots; (4) quantitative errors caused by retention time drift and improper integral window settings; (5) routine quality control (continuous calibration verification, blank, full procedure blank, flow, leakage) relies on manual verification, making it difficult to achieve 24 / 7 operation; (6) data audit lacks a machine-readable "intrinsic rule base" and audit trail. Existing methods are mostly oriented towards single problems and lack a systematic quality control scheme that can be linked in a closed loop. In particular, there is a lack of a full-link method that integrates sampling quality control, pre-processing quality control, analysis quality control and data quality control into a unified architecture, and there is also a lack of joint monitoring strategies and state machine response mechanisms that can be used in dynamic environments (vehicle-mounted / ship-mounted). Summary of the Invention

[0003] To address the technical problems described in the background art, the present invention aims to provide a VOCs quality control method and system. This system achieves continuous traceability, low maintenance, and high robustness of monitoring data through real-time monitoring and volume correction of the sampling process, adjustable humidity calibration and compensation model, dynamic blank and memory effect index (MBI), online estimation of enrichment efficiency (η_online), retention time drift-integral window-separation linkage control, event-state machine-based SOP, data rule base audit and tamper-proof QC tags.

[0004] The technical solution of the present invention is as follows:

[0005] A VOCs quality control method, comprising:

[0006] S0, Sampling quality control;

[0007] S1. Establish a dynamic blank baseline;

[0008] S2. Perform multi-point calibration under at least three relative humidity conditions to construct a response-concentration-humidity model R=α·C·f(RH), where f(RH)=1+β1·ΔRH+β2·(ΔRH) 2Where R is the instrument response value, α is the response factor, C is the concentration of the target VOCs component, f(RH) is the relative humidity correction function, β1 is the coefficient of the first term of humidity correction, β2 is the coefficient of the second term of humidity correction, and ΔRH is the relative humidity deviation.

[0009] S3. Calculate the limit of detection (MDL) and lower limit of quantitation (LOQ) using the low-concentration standard repeated determination method, and verify that the lowest point of the calibration line is ≥LOQ;

[0010] S4. Based on the retention time locked by the internal standard, shift the integral window when the retention time drift |Δt_R|≤ the first threshold, and adjust the chromatographic conditions when the resolution Rs is lower than the second threshold.

[0011] S5. Assess blank residual and calculate the memory effect index (MBI), and determine if MBI ≤ the third threshold;

[0012] S6. Estimate the enrichment efficiency η_total and correct the response factor by using penetration monitoring and dual internal standards;

[0013] S7. Perform continuous calibration and verification periodically and calculate operational precision;

[0014] S8. Trigger actions for out-of-limit events based on state machines;

[0015] S9. Perform consistency checks on the observation data based on the rule base and output the anomaly category;

[0016] S10. Generate tamper-proof QC tags and write them into metadata for audit trails and quality assessment.

[0017] In the above technical solution, the modules used for sampling quality control include at least an integrated flow controller, pressure sensor, temperature sensor and leak detection unit; when the flow deviation exceeds ±5% or a pipeline leak is detected, an alarm is triggered and the sampling volume correction factor V_corr is recorded and written to the QC metadata.

[0018] In the above technical solution, the relative humidity conditions are 20%, 50%, and 80%, and a weighted least squares fitting is used to output the β coefficient; when the β coefficient drifts beyond the fourth threshold, recalibration is triggered.

[0019] In the above technical solution, the memory effect index MBI = A0 / A_high, where A0 is the value of the blank decay model A_blank(t) = A0·e^{-kt} at t=0, and the qualified threshold is MBI≤1%. When the threshold is exceeded, the desorption / baking / adsorption tube replacement sequence is performed according to the state machine. Here, A_high is the signal amplitude of the high concentration standard point, t is the decay time, and k is the decay rate constant.

[0020] In the above technical solution, the enrichment efficiency η_total = η_enrich × η_desorb, where η_total is the total enrichment efficiency, η_enrich is the adsorption enrichment efficiency, and η_desorb is the thermal desorption efficiency. The penetration monitoring port is set at the rear end of the enrichment unit and connected to the micro detector, and the response factors of each component are weighted and corrected according to η_total.

[0021] In the above technical solution, when |Δt_R|≤0.05 min, the integral window is shifted by the same amplitude; when Rs<1.2, the column temperature, programmed temperature rise or carrier gas flow rate is adjusted, and the method version number is recorded for traceability.

[0022] The above technical solution is applicable to vehicle-mounted or ship-mounted mobile platforms, and its characteristics are as follows:

[0023] Record GNSS position, velocity, and heading information;

[0024] Periodically perform moving blank and MBI assessments;

[0025] In map registration, spatial expansion L=v·τ_cycle is used to label the uncertainty, where v is the platform speed and τ_cycle is the analysis cycle duration. Kinematic parameters are written into QC tags for geographic registration and quality evaluation.

[0026] A VOCs quality control system, comprising:

[0027] Sampling quality control module;

[0028] Humidity-adjustable standard source module;

[0029] Dynamic blank valve assembly module;

[0030] Preprocessing enrichment module;

[0031] Penetration monitoring module;

[0032] Internal standard injection module;

[0033] Chromatography / mass spectrometry detection module;

[0034] The controller is configured to execute steps S0-S10 of the VOCs quality control method and output QC tags and alarm signals, wherein the QC tags are stored in an immutable data record structure;

[0035] The controller includes:

[0036] Computing unit, analog and digital I / O interfaces;

[0037] Serial port, Ethernet interface and time synchronization module;

[0038] The log storage module is used to record audit trail data.

[0039] In the above technical solution, the system housing dimensions are 500×250×90 mm, the protection level is IP55, the power supply is AC220 V±10%, 50 Hz±5%, and it is suitable for high humidity and vibration environments.

[0040] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements steps S0-S10 of the VOCs quality control method and generates a traceable QC record structure.

[0041] Beneficial effects:

[0042] Compared with existing technologies, this invention constructs a "sampling-preprocessing-analysis-data full-link closed-loop quality control" system. Through the combination of "humidity three-dimensional compensation + MBI index + η_online enrichment efficiency + linkage state machine + rule base review + QC tag", it achieves the following: (1) a significant reduction in quantitative deviation under humidity / load fluctuations; (2) memory effect and blank residue can be quantitatively evaluated and automatically handled; (3) low enrichment efficiency can be diagnosed and corrected online; (4) automated operation and maintenance, reducing reliance on manual labor; (5) data review can be programmed and traceable; (6) the system structure supports vehicle / ship mobile monitoring, is compatible with the quality control requirements of complex working conditions such as vibration, salt spray, and position and velocity changes, and improves the reliability of environmental monitoring in mobile scenarios. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the method flow of the present invention (S0-S10).

[0044] Figure 2 This is a block diagram of the system structure of the present invention;

[0045] Figure 3 This is a schematic diagram of the three-dimensional calibration and compensation surface for humidity-concentration-response.

[0046] Figure 4 This is a schematic diagram illustrating the decay and threshold of the memory effect index (MBI).

[0047] Figure 5 This is a quality control state machine limit-action mapping diagram;

[0048] Figure 6 A schematic diagram of the distribution of signal bands for species pairs / cumulative scores in the data rule base review;

[0049] Figure 7 This is a schematic diagram of the hardware structure. Detailed Implementation

[0050] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. However, the following embodiments are only for explaining the present invention, and the scope of protection of the present invention should include all the contents of the claims. Moreover, through the description of the following embodiments, those skilled in the art can fully implement all the contents of the claims of the present invention.

[0051] Example 1:

[0052] A VOCs quality control method includes the following steps:

[0053] S0, Sampling Quality Control:

[0054] During the sampling phase, the sampling flow rate, pipeline pressure, and ambient temperature are monitored and recorded in real time. When the flow rate deviation exceeds ±5% or a pipeline leak is detected, an alarm is automatically triggered and the correction factor V_corr of the sampling volume for that period is marked. The sampling time, location (such as GNSS coordinates), and meteorological parameters are recorded simultaneously to provide a basis for subsequent data tracing.

[0055] S1. Dynamic blank baseline establishment: Switch the zero gas / internal standard blank channel between the sampling end and the analysis end to obtain the blank signal sequence and establish a time rolling baseline.

[0056] S2. Adjustable humidity multi-point calibration: Perform at least 5-point (preferably 7-point) calibration on the target analyte under relative humidity RH∈{20%, 50%, 80%} conditions to construct a three-dimensional response-concentration-humidity model. ,in ;reference Figure 3 A three-dimensional surface model of calibration point (C) - relative humidity (RH) and response (R) is established.

[0057] S3. Method Detection Limit and Lower Limit of Quantification: Low-concentration standards were repeatedly measured at near-LOQ levels (n=7 replicates). and Calculate and verify that "the lowest point of the calibration line is greater than or equal to the LOQ".

[0058] S4. Retention time drift and separation linkage: Based on the internal standard to lock the retention time, if |Δt_R|≤0.05 min (or≤0.5%), the integration window is shifted by the same amplitude; if peak overlap still occurs and Rs<1.0 (preferably 1.2), the column temperature / programmed temperature rise / carrier gas flow rate is automatically adjusted and the method version is recorded.

[0059] S5. Assessment of memory effect and blank residual capacity: Refer to Figure 4 Immediately after the highest concentration calibration point, switch to zero gas, record the decay of the blank signal over time as A_blank(t)=A0·e^{-kt}, calculate the memory effect index MBI=A0 / A_high, and determine that MBI≤1% is qualified.

[0060] S6. Online estimation of enrichment efficiency: The enrichment unit is equipped with a breakthrough monitoring port and injected with early / late dual internal standards. The adsorption efficiency η_enrich, desorption efficiency η_desorb, and total efficiency η_total = η_enrich × η_desorb are calculated, and the response factor or weighted quantitative results are corrected accordingly.

[0061] S7. Continuous Calibration Verification (CCV) and Operational Precision: Verify the standard of inserting medium concentration every ≤5 days, with a limit deviation of ≤±10% (permissible level ±15%), and calculate the %RSD of the most recent k (≥7) times ≤15%.

[0062] S8. Quality Control State Machine and Limit Exceedance Handling: Refer to Figure 5 When any indicator exceeds the limit, the sequence of actions is triggered according to priority: "retest → recalibrate → extend desorption / baking → replace adsorption tube / chromatographic column → shutdown alarm".

[0063] S9. Data Rule Base Review: Utilizing rules such as species pairs, cumulative distribution, and database comparison, the measured concentrations are assessed for consistency and anomalies, outputting category labels (quantitative error / integration error / identification error / reasonable). Furthermore, speed, wind direction, and acceleration are introduced as covariates under mobile operating conditions. Figure 6 The empirical distribution among typical VOC species pairs is shown, along with the confidence interval structure used to identify integrals / identification errors.

[0064] The data rule base is used to review the consistency and rationality of observation data. The rule base is constructed based on general principles of atmospheric chemistry and environmental statistics, and includes, but is not limited to, the following types:

[0065] 1. Absolute concentration consistency rule: Based on the regional background distribution characteristics of long-lived components, combined with their cumulative distribution or statistical interval, results that deviate significantly from the physically reasonable range are marked as abnormal;

[0066] 2. Temporal variation characteristic rules: By utilizing the characteristic that some components have stable variation patterns on diurnal and seasonal scales, results that significantly deviate from typical time series patterns can be identified;

[0067] 3. Relative ratio rule: Constrain the concentration ratio of components with similar origin or chemical lifetime. If the ratio deviates from the empirical statistical range, it is marked as a possible integral or quantitative anomaly.

[0068] 4. Chemical activity and lifetime rules: Based on the differences in atmospheric lifetime among species, the rationality of the concentration ranking or relative change range is checked, and situations such as abnormally high levels of short-lived components that do not conform to chemical behavior are identified.

[0069] The audit results are used to output the anomaly category and write it into the QC tag. The rule base can be adaptively updated through historical observation data or model statistical features.

[0070] S10, QC Tagging and Audit Trail: Write immutable QC metadata {V_corr, CalVer, β coefficient, RsOK, Δt_R, MBI, η_total, CCV deviation, %RSD, RuleID, AlarmCode} for each measurement and retain audit logs.

[0071] Example 2 (Online TD-GC-MS / FID System):

[0072] Device components: such as Figure 2 As shown, the system includes an adjustable humidity standard source (dual MFC + membrane humidifier + temperature control + RH sensor), a dynamic blank valve group (sample gas / zero gas / standard gas / breakthrough / tailblowing channel), a multi-bed adsorption tube enrichment unit (heatable for desorption and baking), a breakthrough detector (miniature FID / PID or MS TIC window), dual internal standard injection, a chromatography-mass spectrometry detection module, a VQCS-A controller, and a display and communication module.

[0073] Key parameters: RH set at 20%, 50%, and 80%; calibrate 5-7 points, R≥0.995 (strict ≥0.998), single-point deviation ≤10% (allowable 15%); MBI≤1%; η_total≥85% (allowable ≥75%); CCV≤once every 5 days, deviation ≤±10% (allowable ±15%); %RSD≤15%; |Δt_R|≤0.05 min; Rs≥1.0 (strict ≥1.2).

[0074] Process: such as Figure 1 As shown, execution proceeds according to S1–S10, triggering action sequences and logs when limits are exceeded.

[0075] Example 3 (TO-15 tank sampling-GC-MS system):

[0076] Differences:

[0077] 1. Since there is no enrichment module at the sampling end, S6 (η_online) is not executed in this embodiment; however, S0 (sampling quality control) and S1 (dynamic blank) still achieve equivalent functions through tank cleanliness / leakage rate.

[0078] 2. The complete blank procedure includes tank cleanliness verification (24 h leakage rate ≤0.1%) and sampling / injection pipeline inertization verification.

[0079] 3. Humidity compensation is achieved by introducing zero air + standard air with a set RH into the tank, while still executing the S2 humidity three-dimensional compensation model.

[0080] Results: Comparison before and after compensation, the CCV deviation of components such as formaldehyde and butenal decreased from ±18% to ±7% (example data).

[0081] Example 4 (Portable PID / IMS Terminal):

[0082] Differences: Built-in standard bladder + micro-humidification module for daily CCV and RH compensation; simplified state machine, retaining only CCV / blank / flow / sensor self-test. Can be combined with the S9 rule base for rapid consistency determination of monitoring data.

[0083] Mobile operating condition quality control extension (system layer):

[0084] To adapt to shipborne / vehicle-mounted mobile monitoring scenarios (urban mobile monitoring, park inspection, nearshore / inland waterway discharge mobile monitoring, oil spill / emergency monitoring, etc.), the S0-S10 system has been expanded at the system level within the quality control system, including sampling end, enrichment end, data end and control end.

[0085] A. Sampling and piping (corresponding to S0 / S1 / S5 / S6):

[0086] A1. The sampling main pipe is equipped with PTFE / stainless steel inert heating (40-80℃) and a bypass high-speed air extraction and dynamic zero air / moving blank channel.

[0087] A2. During driving, automatically switch to zero air once every T_mb (recommended 5-15 min) for rapid MBI and leak verification;

[0088] A3, MBI>1% triggers state machine: Extend desorption → Baking → Replace adsorption tube → Leak detection;

[0089] A4. The forward sampling probe is placed on the windward side of the foreboard of the vehicle / ship to record the installation position and heating status into the QC tag.

[0090] B. Movement and Geographic Labelling (S10)

[0091] B1. GNSS (GPS / BeiDou) + IMU recording: {lat, lon, alt, speed, heading, acc}; Time synchronization between the controller and the instrument's NTP / GNSS, time difference ≤ ±0.5 s;

[0092] B2. Write the Geo-QC field in the QC tag: {lat, lon, alt, speed, heading, geohash, time_sync, install_id};

[0093] B3. If time_sync > 0.5 s or GNSS accuracy is poor, set Flag_time = 1 and reduce the weight or pause quantitative analysis.

[0094] C. Temporal / spatial resolution and registration (S3 / S4 / S7 / S9)

[0095] C1. For chromatographic methods: spatial broadening is used, L=v·τ_cycle (v is the plateau speed, τ_cycle is the center time of one analysis cycle); the output is the geographic coordinates and uncertainty bands registered with the peak center time centroid.

[0096] C2. For PID / IMS: Use sliding window noise reduction (e.g., 3-5 s) and wind direction correction;

[0097] C3. When v > v_max or the heading changes frequently (|Δheading| > θ_thr @ Δt): automatically extend the sampling / enrichment time or pause quantification, and set Flag_motion=1.

[0098] D. Vibration / Power Supply / Thermal Management (S2 / S6 / S8)

[0099] D1. Vibration damping bases are installed on key components (≥6 dB@10-200 Hz), and valve assembly and MFC cable are prevented from loosening;

[0100] D2. Vehicle-mounted 12 / 24 V → AC / DC converter with built-in UPS; critical chamber temperature control (±1 ℃); marine-mounted design considers salt spray and corrosion protection (IP54 / 55).

[0101] D3, power surge / undervoltage set Flag_power, and trigger recalibration / move blank;

[0102] E. Mobile SOPs and Rule Base Extensions (S7 / S8 / S9)

[0103] E1. Added the steps "Parking Point Verification / Moving Blank / Moving CCV (Permeation Tube or Standard Capsule) / Speed ​​Threshold Filtering / Sharp Turn and Acceleration Anomaly Removal";

[0104] E2. The rule base introduces speed, wind direction, and acceleration as covariates under moving conditions; when the probability of an anomaly being explained by motion factors is greater than p_thr, it is classified as a suspicious point caused by motion and its weight is reduced instead of being directly eliminated.

[0105] E3, Layer rendering output Layer_QC: {Flag_time, Flag_motion, Flag_power, MBI, η_total, CCV bias, out-of-confidence band scale}, used for quality visualization on the map.

[0106] Controller VQCS-A (Hardware Platform and Interchangeability, Environment and Reliability):

[0107] Reference Figure 7 The schematic diagram of the hardware structure of this invention shows a typical layout of a 500×250×90 mm aluminum alloy housing, front panel interfaces, valve group module, enrichment module, sensor placement, and controller VQCS-A. This diagram is for illustrative purposes only and does not relate to commercial design.

[0108] Computing and Interfaces: Quad-core ≥3.4 GHz, Memory ≥16 GB, Storage ≥1 TB; USB×4, HDMI×1, VGA×1, RS-232×2, RS-485×2, Gigabit Ethernet×4, DI / DO×8 / 8, Analog×8; Power Supply AC220 V±10% / 50Hz±5%, ≤5 A; Local environmental monitoring and air conditioning linkage; GPS / BeiDou timing optional.

[0109] Structural dimensions: 500×250×90 mm, aluminum alloy shell, corrosion-resistant coating, IP55.

[0110] Environment: Storage -40~+80 ℃, operation -20~+60 ℃; 0-95%RH (non-condensing); altitude ≤5000 m.

[0111] Interchangeability: Products in the same batch maintain hardware / firmware version compatibility and interchangeability; remote firmware upgrades and rollbacks are supported.

[0112] Measurement and Calibration: All input / output channels provide two-point or multi-point calibration and traceability records (flow rate, pressure, temperature and humidity, analog quantity).

[0113] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A VOCs quality control method, characterized in that, include: S0, Sampling quality control; S1. Establish a dynamic blank baseline; S2. Perform multi-point calibration under at least three relative humidity conditions to construct a response-concentration-humidity model R=α·C·f(RH), where f(RH)=1+β1·ΔRH+β2·(ΔRH) 2 Where R is the instrument response value, α is the response factor, C is the concentration of the target VOCs component, f(RH) is the relative humidity correction function, β1 is the coefficient of the first term of humidity correction, β2 is the coefficient of the second term of humidity correction, and ΔRH is the relative humidity deviation. S3. Calculate the limit of detection (MDL) and lower limit of quantitation (LOQ) using the low-concentration standard repeated determination method, and verify that the lowest point of the calibration line is ≥LOQ; S4. Based on the retention time locked by the internal standard, shift the integral window when the retention time drift |Δt_R|≤ the first threshold, and adjust the chromatographic conditions when the resolution Rs is lower than the second threshold. S5. Assess blank residual and calculate the memory effect index (MBI), and determine if MBI ≤ the third threshold; S6. Estimate the enrichment efficiency η_total and correct the response factor by using penetration monitoring and dual internal standards; S7. Perform continuous calibration and verification periodically and calculate operational precision; S8. Trigger actions for out-of-limit events based on state machines; S9. Perform consistency checks on the observation data based on the rule base and output the anomaly category; S10. Generate tamper-proof QC tags and write them into metadata for audit trails and quality assessment.

2. The VOCs quality control method as described in claim 1, characterized in that, The modules used for sampling quality control include at least an integrated flow controller, pressure sensor, temperature sensor, and leak detection unit. When the flow deviation exceeds ±5% or a pipeline leak is detected, an alarm is triggered and the sampling volume correction factor V_corr is recorded and written to the QC metadata.

3. The VOCs quality control method as described in claim 1, characterized in that, The relative humidity conditions are 20%, 50%, and 80%. Weighted least squares fitting is used to output the β coefficient. When the β coefficient drifts beyond the fourth threshold, recalibration is triggered.

4. The VOCs quality control method as described in claim 1, characterized in that, The memory effect index MBI = A0 / A_high, where A0 is the value of the blank decay model A_blank(t) = A0·e^{-kt} at t=0. The qualified threshold is MBI≤1%. When the threshold is exceeded, the desorption / baking / adsorption tube replacement sequence is executed according to the state machine. A_high is the signal amplitude of the high concentration standard point, t is the decay time, and k is the decay rate constant.

5. The VOCs quality control method as described in claim 1, characterized in that, The enrichment efficiency η_total = η_enrich × η_desorb, where η_total is the total enrichment efficiency, η_enrich is the adsorption enrichment efficiency, and η_desorb is the thermal desorption efficiency. The penetration monitoring port is set at the rear end of the enrichment unit and connected to the micro detector, and the response factors of each component are weighted and corrected according to η_total.

6. The VOCs quality control method as described in claim 1, characterized in that, When |Δt_R|≤0.05 min, the integral window is shifted by constant amplitude; when Rs<1.2, the column temperature, programmed temperature rise, or carrier gas flow rate is adjusted, and the method version number is recorded for traceability.

7. The VOCs quality control method as described in claim 1, applicable to vehicle-mounted or ship-mounted mobile platforms, characterized in that: Record GNSS position, velocity, and heading information; Periodically perform moving blank and MBI assessments; In map registration, spatial expansion L=v·τ_cycle is used to label the uncertainty, where v is the platform speed and τ_cycle is the analysis cycle duration. Kinematic parameters are written into QC tags for geographic registration and quality evaluation.

8. A VOCs quality control system, characterized in that, include: Sampling quality control module; Humidity-adjustable standard source module; Dynamic blank valve assembly module; Preprocessing enrichment module; Penetration monitoring module; Internal standard injection module; Chromatography / mass spectrometry detection module; The controller is configured to perform steps S0-S10 of the VOCs quality control method according to any one of claims 1-7 and output a QC tag and an alarm signal, wherein the QC tag is stored in an immutable data record structure; The controller includes: Computing unit, analog and digital I / O interfaces; Serial port, Ethernet interface and time synchronization module; The log storage module is used to record audit trail data.

9. The VOCs quality control system as described in claim 8, characterized in that, The system has a housing size of 500×250×90 mm, an IP55 protection rating, and a power supply of AC220 V±10%, 50 Hz±5%, making it suitable for high humidity and vibration environments.

10. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements steps S0-S10 of the VOCs quality control method according to any one of claims 1-7 and generates a traceable QC record structure.

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