Noise Immune TDLAS Temperature Measurement Through Spectrum Shifting by Using a Mach–Zehnder Interferometer

Xu, Lijun; Hou, Guangyu; Qiu, Shuang; Huang, Ang; Zhang, Hongyu; Cao, Zhang

doi:10.1109/tim.2021.3076852

Cited by 16 publications

(3 citation statements)

References 34 publications

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“…With the increase of detection iteration (along the Y-axis), environmental interference is added to the signal in the form of slow or fast time-varying noise. In the iterative process, the method dynamically selects useful features to minimize the objective function (9), that is, to find the feature points that have the most significant influence on the final decision (6). As shown in Figure 2(b), the burr weighting is minimal, and only some feature points (around 150 and 280) remain prominent, indicating that feature sparsity is effective.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…It has been recognized as an effective method to measure the sealing quality of encapsulated pharmaceutical vials by oxygen concentration in glass bottles [2][3][4][5] . Meanwhile, the wavelength-modulationbased tunable diode laser absorption spectroscopy (TDLAS/WMS) technology has been developed into a commonly used trace gas detection technology for high resolution and high detection accuracy [6][7][8][9][10] .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic sparse residual oxygen prediction method for encapsulated pharmaceutical vials under TDLAS/WMS framework

Luo

zhou

Yang

2023

Ninth Symposium on Novel Photoelectronic Detection Technology and Applications

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TDLAS/WMS-based oxygen detection has been proven to be an effective method for the sealability verification of encapsulated pharmaceutical vials of sterile preparations. However, under the actual aseptic preparation filling production mill, it is not easy to maintain high oxygen detection precision due to the multiple irritating noises from both the environment (e.g., temperature, moderation, vibration) and the detection system itself (e.g., laser, circuits). This paper proposes a novel dynamic sparse residual oxygen prediction method for pharmaceutical vials under TDLAS/WMS framework. On the one hand, we directly feed the decomposed wavelet sub-components to the prediction model, other than reconstructing them back to the time domain after some filtering measures in the wavelet domain. Then the fine-grained signal descriptive advantage of wavelet transform is preserved, and the rough reconstruction is dropped, instead by the adaptive feature selection managed by the subsequent classification model. On the other hand, to deal with the large data volume gathered from the high-speed production, we introduce the L1-norm to the target function of LSSVM, where sample-sparsity is added to the prediction model innovatively. Thus, by assigning more weight to valuable samples, the influence of environmental interference on prediction decision-making is weakened. Consequently, sample-sparsity and feature-sparsity are realized simultaneously to track the dynamic environmental variation. Experimental results show that the proposed method yields higher average accuracy than others, and provides a referred choice to suppress the inevitable detection interferences, not only from hardware and optical optimization but also from a signal processing perspective.

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Section: Experiments and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic sparse residual oxygen prediction method for encapsulated pharmaceutical vials under TDLAS/WMS framework

Luo

zhou

Yang

2023

Ninth Symposium on Novel Photoelectronic Detection Technology and Applications

View full text Add to dashboard Cite

show abstract

“…In addition, the sawtooth signal was modulated with a MHz-level high frequency carrier signal, so that the absorption spectrum was transferred from low frequency band to high frequency band. Using the two-color temperature extraction method, numerical simulations at unequal temperatures and experiments utilizing heating devices and Bunsen burners to verify noises resistance of this way [33]. So as to comprehend influence of flow field inhomogeneity on TDLAS measurement, Renjie Li et al quantified the integral absorbance (IA) error and gave the estimation error by analyzing the linear function and curve fitting, considering the fitting function's influence and the overlap of the absorption lines.…”

Section: Gas Detectionmentioning

confidence: 99%

Application and algorithm research of TDLAS

Lao

Chen

Zhongkai

2022

J. Phys.: Conf. Ser.

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Tunable diode laser absorption spectroscopy (TDLAS) is extensively utilized in monitoring of trace gases in the environment. With the relative entropy tomographic reconstruction, simultaneous multiplicative algebraic reconstruction technique algorithm and optimization of existing functions and models, TDLAS has been applied to reconstruction of temperature and humidity field, combustion diagnosis, mass flow monitoring and other domains, this paper will analyze the existing TDLAS application and algorithm research.

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A Interferometer modulated TDLAS Temperature Sensor by using Coherent Demodulation

Hou

Zhou

et al. 2022

2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

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Noise Immune TDLAS Temperature Measurement Through Spectrum Shifting by Using a Mach–Zehnder Interferometer

Cited by 16 publications

References 34 publications

Dynamic sparse residual oxygen prediction method for encapsulated pharmaceutical vials under TDLAS/WMS framework

Dynamic sparse residual oxygen prediction method for encapsulated pharmaceutical vials under TDLAS/WMS framework

Application and algorithm research of TDLAS

A Interferometer modulated TDLAS Temperature Sensor by using Coherent Demodulation

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