simultaneous identification
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2022 ◽  
Author(s):  
Jiahao Chen ◽  
Jie Mei ◽  
Xin Yuan ◽  
Yuefei Zuo ◽  
Jingwei Zhu ◽  
...  

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>


2022 ◽  
Author(s):  
Meixiang Wang ◽  
Xiaoxiao Niu ◽  
Rui Cao ◽  
Mengyu Zhang ◽  
Huajie Xu ◽  
...  

The Cu2+ and inorganic phosphates play an extremely important role in the organism and the environment. However, designing simultaneous identification and detection of Cu2+ and phosphates probe to construct multi-input...


2021 ◽  
Vol 14 (1) ◽  
pp. 119
Author(s):  
Solmaz Pourzeynali ◽  
Xinqun Zhu ◽  
Ali Ghari Zadeh ◽  
Maria Rashidi ◽  
Bijan Samali

Bridge infrastructures are always subjected to degradation because of aging, their environment, and excess loading. Now it has become a worldwide concern that a large proportion of bridge infrastructures require significant maintenance. This compels the engineering community to develop a robust method for condition assessment of the bridge structures. Here, the simultaneous identification of moving loads and structural damage based on the explicit form of the Newmark-β method is proposed. Although there is an extensive attempt to identify moving loads with known structural parameters, or vice versa, their simultaneous identification considering the road roughness has not been studied enough. Furthermore, most of the existing time domain methods are developed for structures under non-moving loads and are commonly formulated by state-space method, thus suffering from the errors of discretization and sampling ratio. This research is believed to be among the few studies on condition assessment of bridge structures under moving vehicles considering factors such as sensor placement, sampling frequency, damage type, measurement noise, vehicle speed, and road surface roughness with numerical and experimental verifications. Results indicate that the method is able to detect damage with at least three sensors, and is not sensitive to sensors location, vehicle speed and road roughness level. Current limitations of the study as well as prospective research developments are discussed in the conclusion.


2021 ◽  
Author(s):  
Jiahao Chen ◽  
Jie Mei ◽  
Xin Yuan ◽  
Yuefei Zuo ◽  
Jingwei Zhu ◽  
...  

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>


2021 ◽  
Author(s):  
Jiahao Chen ◽  
Jie Mei ◽  
Xin Yuan ◽  
Yuefei Zuo ◽  
Jingwei Zhu ◽  
...  

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>


Molecules ◽  
2021 ◽  
Vol 26 (24) ◽  
pp. 7705
Author(s):  
Magdalena Ligor ◽  
Anna Kiełbasa ◽  
Ileana-Andreea Ratiu ◽  
Bogusław Buszewski

Saponins are an important group of secondary metabolites naturally occurring in plants with important properties like: antibacterial, antiviral and antifungal. Moreover, they are widely used in the cosmetic industry and household chemistry. The sapogenins are saponin hydrolyses products, frequently used to facilitate saponin detection. In the present study, an improved methodology for isolation and separation of five sapogenins extracted from nettle (Urtica dioica L.), white dead-nettle (Lamium album L.), common soapwort (Saponaria officinalis L.) and washnut (Sapindus mukorossi Gaertn.) was developed using ultra-high-performance liquid chromatography with an evaporative light-scattering detector (UHPLC-ELSD). Based on quantitative analysis, the highest content of hederagenin (999.1 ± 6.3 µg/g) and oleanolic acid (386.5 ± 27.7 µg/g) was found in washnut extracts. Good recoveries (71% ± 6 up to 99% ± 8) were achieved for four investigated targets, while just 22.2% ± 0.5 was obtained for the fifth one. Moreover, hederagenin and oleanolic acid of whose highest amount was detected in washnut (999.1 ± 6.3 µg/g and 386.5 ± 27.7 µg/g, respectively) were subject to another approach. Consequently, liquid chromatography coupled mass spectrometry (LC/MS) with multiple reaction monitoring mode (MRM) was used as an additional technique for fast and simultaneous identification of the mentioned targets.


2021 ◽  
Author(s):  
Krista L Newell ◽  
Mitchell J Waldran ◽  
Stephen J Thomas ◽  
Timothy P Endy ◽  
Adam Tully Waickman

Conventional methods for quantifying and phenotyping antigen-specific lymphocytes can rapidly deplete irreplaceable specimens. This is due to the fact that antigen-specific T and B cells have historically been analyzed in independent assays each requiring millions of cells. A technique that facilitates the simultaneous detection of antigen-specific T and B cells would allow for more thorough immune profiling with significantly reduced sample requirements. To this end, we developed the B And T cell Tandem Lymphocyte Evaluation (BATTLE) assay, which allows for the simultaneous identification of SARS-CoV-2 Spike reactive T and B cells using an optimized Activation Induced Marker (AIM) T cell assay and dual-color B cell antigen probes. Using this assay, we demonstrate that antigen-specific B and T cell subsets can be identified simultaneously using conventional flow cytometry platforms and provide insight into the differential effects of mRNA vaccination on B and T cell populations following natural SARS-CoV-2 infection.


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