為什麼PAS DGA比GC更適合線上監測

2。氣相層析 (GC)

2.1 工作原理

氣相層析法是 DGA 的經典方法，被國際標準標準（IEEE C.其工作原理分為三步驟：

2.2技術原理特性

優點：

Step 1: Gas extraction
An oil sample is collected from the transformer, and dissolved gases are separated from the oil using vacuum degassing or headspace extraction.

Step 2: Chromatographic separation
The extracted gas mixture is carried by an inert carrier gas (such as helium, nitrogen, or argon) through a chromatographic column. The column is packed with a stationary phase. Different gas molecules interact differently with the stationary phase, so they travel through the column at different speeds, achieving separation.

Step 3: Detection and quantification
The separated gases enter a detector (commonly a Thermal Conductivity Detector, TCD, or a Flame Ionization Detector, FID). The detector output produces a chromatogram – peak position identifies the gas species, and peak area reflects gas concentration.

限制：82823f24b1d642da81358064e 82823f24b1d642da813580364207642da81580342085)在測量石油中溶解氣體濃度方面表現出高度一致性；這兩種技術都能有效測定氣體成分和濃度。

3。紅外線光譜

• High sensitivity: Down to 0.1 ppm; detection limit for key gases like acetylene ≤ 0.5 ppm

• High accuracy and repeatability: As a laboratory standard, results are reliable

• Comprehensive gas coverage: Can measure nine or more fault gases simultaneously

• Mature technology: Well‑established international standards and extensive application experience

紅外線光譜根據氣體對特定紅外線波長的吸收來檢測氣體，遵循朗伯比爾定律。不同的氣體分子具有獨特的紅外線吸收光譜—它們的「指紋」光譜。

• Requires carrier gas: Consumes high‑purity inert gases, increasing operating costs

• Requires regular calibration: Needs standard gas mixtures for calibration

• Discontinuous monitoring: Traditional GC is batch‑based – cannot provide real‑time continuous monitoring

• Complex maintenance: Columns, valves, and other parts require regular servicing

• Time delay: From sampling to results takes hours to days

3.1傅立葉變換紅外光譜(FTIR)

• Laboratory offline analysis: Used as a benchmark method for fault confirmation

• Periodic inspections: Regular sampling for non‑critical transformers

• Online monitoring systems: Miniaturized GC systems exist, but they still consume carrier gas

特性：

可同時測量多種氣體82823f24b1 016f9464e光譜分辨率高、良好選擇性

相對複雜的光路系統

痕量檢測值氣體的靈敏度有限（典型度數有限（典型靈敏度5554e痕量。 ppm)

Principle:
FTIR uses a Michelson interferometer to generate interference light. After passing through the gas sample, the light undergoes Fourier transformation to produce an infrared absorption spectrum. The position of absorption peaks identifies gas species, and the peak intensity corresponds to gas concentration.

3.2可調諧二極體雷射吸收光譜(TDLAS)

• 特性：82823f24b1d642da 8135803016f9464e每次測量只能測量一種或幾種氣體

• 高靈敏度，下降達到ppb級

• 抗干擾能力強，選擇性好82823f24b1d642da813580 3016f9464e多組分需要多個雷射或波長掃描measurement

• 3.3非色散紅外光譜(NDIR)

特性：

Principle:
TDLAS uses a tunable semiconductor laser whose emission wavelength is precisely aligned with the characteristic absorption line of the target gas. By scanning the laser wavelength and measuring the absorption peak intensity, gas concentration is quantified.

結構較簡單，成本較低

• 中等選擇性 – 容易受到其他氣體的干擾

• 檢測極限 ~0.5 ppm

• 常用於單組分或雙組分氣體檢測

• 4。光聲光譜 (PAS)

4.1 工作原理

光聲光譜是一種快速發展的光學氣體檢測技術。其原理基於光聲效應：當氣體分子吸收特定波長的紅外線光時，它們會從基態躍遷到激發態。透過碰撞弛豫，吸收的能量轉化為熱量，導致瞬時溫度升高。當光源被調製時，週期性加熱會產生壓力波，即聲波。高靈敏度麥克風偵測聲波強度，聲波強度與氣體濃度成正比。

• PAS的關鍵公式可以表示為：

• S = k·α·P· C82823f24b16f9464eS = k·α·P· C82823f24b16f9464eS = k·α·P· C82823f24b16f9464eS.技術特性

• 優點：

• 限制：82823f24b1d642da813580302da

環境振動可能影響測量精度82823f24b1d642da813580 3016f9464e對麥克風靈敏度要求高

4.3增強型光聲光譜（增強型PAS）

現代增強型 PAS 技術透過多項創新克服了傳統 PAS 的限制：

4.4 PAS 與GC：比較驗證

研究表明，PAS 和 GC 在測量各種油樣中溶解氣體濃度方面具有高度一致性。一項使用來自運行三年多的變壓器的 30 個油樣的對比實驗證實，兩種技術都可以有效地測定氣體成分和濃度。

Where:
S = photoacoustic signal intensity
k = instrument constant
α = gas absorption coefficient
P = optical power
C = gas concentration

實驗中觀察到的 PAS 測量值差異主要歸因於採樣過程中引入的空氣，導致 CO2 和 CH4 濃度略有增加。這凸顯了正確採樣程序的重要性，而不是任何固有的技術缺陷。

5。其他新興技術

• No carrier gas required: Direct gas measurement – no consumable carrier gas

• High sensitivity: Detection limit for key gases like acetylene reaches 0.1–0.5 ppm

• Fast response: Suitable for real‑time continuous monitoring

• No moving parts: When using MEMS electronic modulation, reliability is high

• Low maintenance: No consumables

5.1 拉曼光譜 (RS)

• 拉曼光譜基於拉曼散射效應。它透過測量雷射與氣體分子相互作用時產生的散射光譜來分析氣體成分。

• 特性：

• 無需樣品製備 -可直接測量石油

單一雷射可同時偵測多種氣體

靈敏度相對較低 -需要增強技術

• MEMS infrared light source: Electronic modulation replaces the mechanical chopper, eliminating vibration noise

• Dual‑chamber enhanced gas cell: Gold‑coated absorption cavities with resonance enhancement technology improve detection sensitivity

• Vacuum degassing: Temperature‑controlled vacuum degassing compatible with multiple oil types

Enhanced PAS achieves consumable‑free, maintenance‑free, full‑gas‑coverage online monitoring capability.

更高的系統cost

5.2 感測器陣列技術82823f24b16423f24b1642026000323f24b16423f採用模式辨識演算法分析氣體成分。

特性：

成本相對較低82823f24b1d642da8135803016–易於整合

選擇性和穩定性需要進一步改進

受環境溫度和濕度影響顯著52823f24b16f9464e受環境溫度和濕度影響技術比較摘要

（此處將放置詳細的比較表。以下是文字摘要。）82823f24b1d6 42da8135803016f9464e來源：多個同行評審的研究和技術資料表.

• 7。技術趨勢

• 7.1 無載氣操作

• 傳統氣相層析法需要載氣，增加了操作成本和複雜性。光學技術（PAS、紅外光譜等）不需要載氣，代表了未來線上監測的主流方向。

• 7.2 綜合監測參數

Current status:
With advances in laser and fiber optic technologies, RS is gradually expanding its role in DGA. Enhanced RS systems have reduced detection limits for gases such as C₂H₂ and CH₄ to tens of ppm, sufficient for online monitoring applications.

從單一氣體監測轉向多組分監測，結合濕度、溫度和其他參數，可實現全面的變壓器狀態評估。

7。未來趨勢有利於整合多種技術，實現優勢互補。

7.4 智慧診斷

• 結合人工智慧（AI）和機器學習演算法，實現自動故障類型識別和嚴重依賴評估方法的依賴關係。研究表明，人工神經網路（ANN）在DGA故障診斷中可以達到76.8%的準確率，顯著高於傳統方法（Dornenburg 55%、Duval三角40%、Roger 38.4%、IEC 31.8%）。

• 8。如何選擇正確的技術解決方案

• 結論

• 變壓器油溶解氣體分析已經從單組分發展到多組分、離線方法到電線方法到電線方法到電線方法到電線方法。

6. Technology Comparison Summary

(A detailed comparison table would be placed here. Below is a textual summary.)

Sources: Multiple peer‑reviewed studies and technical datasheets.

7. Technology Trends

7.1 Carrier‑Gas‑Free Operation

Traditional GC requires carrier gas, increasing operating cost and complexity. Optical technologies (PAS, infrared spectroscopy, etc.) require no carrier gas and represent the mainstream direction for future online monitoring.

7.2 Integrated Monitoring Parameters

Moving from single‑gas to multi‑component monitoring, combined with moisture, temperature, and other parameters, enables comprehensive transformer condition assessment.

7.3 Multi‑Technology Integration

Different technologies have different strengths: GC offers high accuracy, PAS provides maintenance‑free operation, and TDLAS delivers exceptional sensitivity. Future trends favor integrating multiple technologies to achieve complementary advantages.

7.4 Intelligent Diagnostics

Combining artificial intelligence (AI) and machine learning algorithms enables automatic fault type identification and severity assessment – overcoming the dependency on expert experience and inconsistent diagnostic results of traditional DGA methods. Studies show that artificial neural networks (ANN) can achieve 76.8% accuracy in DGA fault diagnosis, significantly higher than traditional methods (Dornenburg 55%, Duval triangle 40%, Roger 38.4%, IEC 31.8%).

8. How to Choose the Right Technical Solution

Conclusion

Dissolved gas analysis for transformer oil has evolved from single‑component to multi‑component, from offline to online, and from electrical to optical methods.

Gas chromatography, as the traditional standard method, remains irreplaceable in laboratory applications due to its high accuracy and comprehensive coverage. 
Photoacoustic spectroscopy, with its maintenance‑free and consumable‑free characteristics, has become the ideal choice for online continuous monitoring. 

For power utilities, selecting the right DGA technology requires balancing asset criticality, budget constraints, maintenance capabilities, and diagnostic needs. As next‑generation technologies like enhanced PAS mature, maintenance‑free, full‑gas‑coverage, intelligent diagnostic online monitoring is becoming a reality – providing strong support for the transition from “periodic maintenance” to “predictive maintenance” of power equipment.

HERTZINNO’s online DGA systems (DGA900, DGA500, DGA300) use enhanced MEMS‑based photoacoustic spectroscopy to deliver consumable‑free, maintenance‑free continuous monitoring, with flexible configurations ranging from single‑gas to 9+1 (nine gases + moisture). Learn more →