Analog and Photon Signal Splicing for CO2-DIAL Based on Piecewise Nonlinear Algorithm

In the CO2 differential absorption lidar (DIAL) system, signals are simultaneously collected through analog detection (AD) and photon counting (PC). These two kinds of signals have their own characteristics. Therefore, a combination of AD and PC signals is of great importance to improve the detection capability (detection range and accuracy) of CO2-DIAL. The traditional signal splicing algorithm cannot meet the accuracy requirements of CO2 inversion due to unreasonable data fitting. In this paper, a piecewise least square splicing algorithm is developed to make signal splicing more flexible and efficient. First, the lidar signal is segmented, and according to the characteristics of each signal, the best fitting parameters are obtained by using the least square fitting with different steps. Then, all the segmented and fitted signals are integrated to realize the effective splicing of the near-field AD signal and the far-field PC signal. A weight gradient strategy is also adopted in signal splicing, and the weights of the AD and PC signals in the spliced signal change with the height. The splicing effect of the improved algorithm is evaluated by the measured signal, which are obtained in Wuhan, China, and the splice of the AD and PC signals in the range of 800–1500 m are completed. Compared with the traditional method, the evaluation parameter R2 and the residual sum of squares of the spliced signal are greatly improved. The linear relationship between the AD and PC signals is improved, and the fitting R2 of differential absorption optical depth reaches 0.909, indicating that the improved signal splicing algorithm can well splice the near-field AD signal and the far-field PC signal.

Preliminary performance evaluation and verification of digital terrestrial television signal propagation

This article presents the computer simulation and field test measurement results on Channel 29 for the preliminary performance evaluation and verification of the newly-installed Lesotho digital terrestrial television network based on DVB-T2 standard following the guidelines and techniques specified by the ITU-R BT.2035-2. It evaluates, at predetermined outdoor locations for fixed and mobile reception, parameters such as received signal strength, signal quality, bit-error rate (BER) and threshold-of-visibility (ToV) together with TV signal decoding (observation of screen artefacts) for quasi error-free reception. The results indicate that at over 97% of the test sites/points at the university town of Roma, the main Berea Plateau transmitter from the capital city (Maseru) broadcasts digital television service with enough signal level and quality to be properly decoded. The measured signal strength threshold ranges above -50 dBm for good reception, -64 dBm to -50 dBm for acceptable reception and -69 dBm to -64 dBm for poor reception. With the noise floor at about -73 dBm, the minimum required C/N of around 23 dB for good reception and about 4 dB for ToV have been recorded. The relative values of minimum required respective signal strength and signal quality for ToV obtained from the set-top box are 33% and 18% for stationary reception, while they give 37% and 20% for mobile reception.

Increasing of the Accuracy of Signalsʼ Time Parameters Measuring Using Double Pulse Trains

In modern diagnostics, much attention is paid to measuring of time parameters, as well as their change over time. The purpose of this work is to develop a method for measuring of time intervals which made it possible to increase the measurement accuracy by reducing errors associated with the instability of main parameters of the pulse signal.In the most of approaches used, the error associated with the instability of main parameters of signals under study is not enough taken into account. As an alternative, a spectral method is proposed in which the measurement of time intervals, as well as their changes, is performed based on the analysis of pulse sequences formed on the basis of characteristic points of the measured signal. For this a double pulse sequence was considered, an equation for the amplitudes of its spectral components was obtained, and in accordance with this it was determined that the delay time between double pulses is the most informative parameter.Using the Mathcad software, an analysis of the sensitivity regions was carried out for the change in the main parameters of the pulse sequence, namely the repetition rate, as the main destabilizing factor.As a result of the implementation of the developed technique, a structural diagram of the measuring system is proposed and an analysis of the measurement error associated with the instability of the main parameters of the pulse sequence is carried out. This error is estimated to be less than 0.01 %.The considered method makes it possible to increase the accuracy of measuring time intervals due to the almost complete elimination of the influence of the instability of the reference frequency and the amplitude of the generated pulses which is unattainable with modern hardware, including digital signal processing.

Factors Influencing Temperature Measurements from Miniaturized Thermal Infrared (TIR) Cameras: A Laboratory-Based Approach

The workflow for estimating the temperature in agricultural fields from multiple sensors needs to be optimized upon testing each type of sensor’s actual user performance. In this sense, readily available miniaturized UAV-based thermal infrared (TIR) cameras can be combined with proximal sensors in measuring the surface temperature. Before the two types of cameras can be operationally used in the field, laboratory experiments are needed to fully understand their capabilities and all the influencing factors. We present the measurement results of laboratory experiments of UAV-borne WIRIS 2nd GEN and handheld FLIR E8-XT cameras. For these uncooled sensors, it took 30 to 60 min for the measured signal to stabilize and the sensor temperature drifted continuously. The drifting sensor temperature was strongly correlated to the measured signal. Specifically for WIRIS, the automated non-uniformity correction (NUC) contributed to extra uncertainty in measurements. Another problem was the temperature measurement dependency on various ambient environmental parameters. An increase in the measuring distance resulted in the underestimation of surface temperature, though the degree of change may also come from reflected radiation from neighboring objects, water vapor absorption, and the object size in the field of view (FOV). Wind and radiation tests suggested that these factors can contribute to the uncertainty of several Celsius degrees in measured results. Based on these indoor experiment results, we provide a list of suggestions on the potential practices for deriving accurate temperature data from radiometric miniaturized TIR cameras in actual field practices for (agro-)environmental research.

Quantification and Degradation of 2,2-Dibromo-3-Nitrilopropionamide (DBNPA) in Bioethanol Fermentation Coproducts

2,2-Dibromo-3-Nitrilopropionamide (DBNPA) has been used as a biocide in industrial water applications due to its instantaneous antimicrobial activity and rapid chemical breakdown. In this study DBNPA is considered as a potential alternative for antibiotics used for bacterial control during corn to ethanol fermentation. A method using LC/MS/MS was developed to accurately quantify DBNPA in water. When this method was applied to quantify DBNPA concentration in a fermentation matrix, DBNPA was found to be unstable and to decay rapidly, preventing validation of the method or quantitation. This method was then used to evaluate the degradation rate of DBNPA in whole stillage, which is the nonvolatile residue produced by removal of ethanol from corn-based fermentation beer by distillation through the relative decrease in measured signal. In addition, a method was developed and validated to quantify bromide, one of the degradation products of DBNPA, in whole stillage using LC/MS/MS. The degradation rate of DBNPA in whole stillage was found to display first order kinetics with a calculated half-life of 85 min. Laboratory analytical chemistry results on DBNPA degradation were confirmed in field trials.

Comparison of Heart Rate Monitoring Accuracy between Chest Strap and Vest during Physical Training and Implications on Training Decisions

Heart rate (HR) and heart rate variability (HRV) based physiological metrics such as Excess Post-exercise Oxygen Consumption (EPOC), Energy Expenditure (EE), and Training Impulse (TRIMP) are widely utilized in coaching to monitor and optimize an athlete’s training load. Chest straps, and recently also dry electrodes integrated to special sports vests, are used to monitor HR during sports. Mechanical design, placement of electrodes, and ergonomics of the sensor affect the measured signal quality and artefacts. To evaluate the impact of the sensor mechanical design on the accuracy of the HR/HRV and further on to estimation of EPOC, EE, and TRIMP, we recorded HR and HRV from a chest strap and a vest with the same ECG sensor during supervised exercise protocol. A 3-lead clinical Holter ECG was used as a reference. Twenty-five healthy subjects (six females) participated. Mean absolute percentage error (MAPE) for HR was 0.76% with chest strap and 3.32% with vest. MAPE was 1.70% vs. 6.73% for EE, 0.38% vs. 8.99% for TRIMP and 3.90% vs. 54.15% for EPOC with chest strap and vest, respectively. Results suggest superior accuracy of chest strap over vest for HR and physiological metrics monitoring during sports.

Machinery Fault Detection Through Ultrasound Technology

Ultrasound is a versatile advanced technology that is utilized in the oil and gas industry for various mechanical and electrical applications such as bearing's faults detection, pump's cavitation, valve's leakage, steam traps, electrical faults, gearbox's issues, compressed air and gas leak's detection..etc. The technology allows the end-user to measure dynamic data using contact (Structure borne) and non-contact (air borne) sensors and converts the ultrasound waves to an audible range for humans to associate sounds with the measured signal. As a result, the sound of the machine can be heard and recorded as voice clip as well as time wave form, which in turn can be translated into frequency spectrum for analysis. The technology has recently evolved in the industry as an important condition monitoring tool, to increase the reliability of rotating equipment. Moreover, it used as a complementary tool to vibration analysis. As well, it can be used as a tool for troubleshooting and preventive maintenance inspection. Background Ultrasound is sound waves with frequencies that are higher than the upper audible limit of human hearing. The human hearing limit varies from person to another, and it is approximated to be around 20Hz to 20 kHz. This is in contrary to the ultrasound range, which is above 20,000 Hz, and hence, it is in audible to human. This range is used widely in various industrial processes, including: cleaning, cutting, forming, testing of materials, and welding. It is characterized by its directional waves, unlike normal sound waves that travel in all directions. This directional characteristic makes ultrasound useful for many applications. Furthermore, ultrasound technology is used in different fields: medical, automotive, etc. and recently in the oil and gas industry as non-destructive-testing tool (NDT). The ultrasound technology in the oil and gas industry is used primarily in the following area's, for example Leak detection. Steam traps inspection. Bearing condition monitoring. Bearing lubrication monitoring. Electrical Inspection. Valve condition monitoring. Pump cavitation. Gearbox issues.

All-in-one Superparamagnetic and SERS-active Niosomes for Dual-targeted in Vitro Detection of Breast Cancer Cells

BackgroundIn vitro and in vivo biosensing through surface-enhanced Raman scattering often suffer from signal contamination diminishing both the limit of detection and quantification. However, overcoming the lack of specificity requires excessive nanoparticle concentrations, which may lead to adverse side effects if applied to patients. ResultsWe propose encapsulation of iron oxide (FexOy) and gold (Au) nanoparticles (NPs) into the bilayer structure of transferrin-modified niosomes. This approach enables achieving greatly enhanced and contamination-free SERS-signals in vitro as well as a dual-targeting functionality towards MCF-7 breast cancer cells. An in-depth characterization of FexOyNPs- and AuNPs-loaded niosomes (AuNPs/FexOyNPs/NIO) after magnetic downstream processing reveals defined hybrid niosome structures, which show a long-term SERS-signal stability in various media such as MCF-7 cell culture medium. In vitro 2D-SERS imaging unveil a successful incorporation of a non-toxic dose of hybrid NPs into MCF-7 cells, which leads to strong and almost contamination-free SERS-signals. The measured signal-to-noise ratio of the in vitro signal exceeds the values required by DIN 32645 for the successful validation of a detection method. ConclusionsThe hybrid niosomes can be considered a promising and efficient agent for the establishment and commercialization of a highly sensitive detection kit for monitoring cancerous tissue.

Measurement and interpretation of electrical signals in transient electrical discharges

Electrical discharges in experiments like Exploding Wire, Plasma Focus, or Z-pinch, involve regions where strong transient electrical currents generates magnetic flux variations within the limits of experiment and diagnostics regions. Due to different experimental conditions, time duration of the transient phase may vary from negligible to play an important role in the explanation of the measured signal of the experiment, in which case Faraday's law of induction cannot be neglected when analyzing the electrical signals. In this work the effects of circuit modeling taking into account Faraday's law will be discussed for the exploding wire experiment in a more detailed way than previous works.

Correlation Analysis and Its Application on an Asymmetry Rotor Structure with Overhang

Overhung rotors are widely used in the industrial field. However, compared with normal structure rotors, the prediction and control of overhung rotors cannot achieve good performance. The work aims to investigate the dynamical behaviours of an overhung rotor by means of correlation analysis, and find its possible application. In this work, based on a real type of rotor, the dynamic model of the rotor with overhang is established by means of the finite element method. Simulation of the dynamic model with different input positions and support stiffnesses is conducted. Based on the methodology of correlation analysis, by introducing a correlation parameter of a proportion of amplitude of measured signal and imbalance mass, the position which has most effect on the vibration is found. Meanwhile, an experiment on the same type of overhung rotor is carried out to validate the results. The numerical results and corresponding experimental results prove that the overhung node has the most effect on the vibration amplitudes of the measured points. Choosing the overhung node to add trial weight, the overhung rotor can be easily balanced. The theory provides an alternative approach to modal analysis which needs more knowledge of the system.