Methodology For Online Monitoring Research Articles

Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer

This work aims to propose an alternative methodology to measure acidity index and chlorophyll content in ground soybean grains using an ultra-compact near-infrared (NIR) spectrometer. Experiment was conducted using 592 soybean samples for acidity index and 348 for chlorophyll content, harvested in southern Brazil. A partial least squares (PLS) model was developed for both parameters, being optimized by outlier detection and validated through its merit figures. For the acid index model the root mean squared error for calibration (RMSEC) was 0.1974 and validation (RMSEP) 0.1694, correlation coefficient (Rcal) 0.8589. Moreover, residual prediction deviation for calibration (RPDcal; 1.7661) and validation (RPDval; 1.8525) were also determined. The results for chlorophyll content were RMSEC (623.2972 mg kg -1 ) and RMSEP (621.9778 mg kg -1 ), Rcal (0.8709), RPDcal (1.5956) and RPDval (1.6295). Results suggest that the NIR spectroscopy can be used to provide a suitable tool for the measurement of the acidity index and the chlorophyll content of the soybean, bringing a significant improvement mainly on the speed of analysis, what is an important goal to industrial routine purposes, besides advantages as non-invasively and non-destructive characteristics, exempt from waste generation and chemical reagents, being a potential alternative methodology for online monitoring in the soybean processing industries.

Non-invasive lactate- and pH-monitoring in porcine meat using Raman spectroscopy and chemometrics

The feasibility of using chemometrics and Raman spectroscopy as a fast and non-invasive method to monitor the early postmortem lactate accumulation and pH decline in pork meat has been investigated. For this application, an on-line monitoring methodology has not yet been established. Based on raw Raman spectra of porcine semimembranosus muscles, a range of spectral pre-processing and multivariate calibration techniques were investigated to develop and test on-line prediction models for the meat quality parameters. The influence of the pre-processing methods on the prediction speed, robustness and accuracy performance of the employed linear and non-linear algorithms was compared. Identification of the most effective chemometric evaluation procedure was performed using least square linear regression together with locally weighted regression and metaheuristic data optimization methods such as the genetic algorithm and the ant colony optimization. The herein presented analysis suggests that the locally weighted regression applied to the standard normal variate (SNV) normalized Raman spectra provides the most accurate and robust models with a cross-validated coefficient of determination (r2cv) of 0.97 for pH and lactate, a cross-validated root mean square error (RMSECV) of 4.5mmol/kg for the lactate prediction and 0.06pH-units for the pH prediction. These results demonstrate the great potential of combining chemometrics and Raman spectroscopy for on-line meat quality control applications.

Fatigue Monitoring by NDT of Austenitic Stainless Steel at Ambient Temperature and 300°C and New Attempts to Monitor a Fracture Mechanics Test

Abstract NDT on-line monitoring methodology was applied at the servo-hydraulic machine to monitor the propagation behavior of ultrasonic waves during LCF-tests. Coupling-free excitation and receiving of the waves by use of EMAT were applied. A high potential to early characterize fatigue before the end-of-life was documented. So far at ambient temperature a phase transformation to α’-martensite is observed micro-magnetic NDT is also appropriate. Destructive SE(B) Single Edge Bending Tests were online monitored to study NDT methodology to in-situ and on-line determine crack initiation and growth during the experiment. Time of flight of an EMAT-excited ultrasonic surface wave which travels around the crack shows a linear correlation to crack growth and by a Giant Magneto-Resistor-Line-Array the magnetic leakage flux of the crack is observed.

On-Line Monitoring Method of Drive Motor Operational for On-Load Tap Changers

Motor-driven on-load tap changers (OLTC) operational within power transformers are extensively used for voltage regulation in power systems, whose principal malfunctions or failures are of mechanical type. Hence, monitoring of the mechanical characteristics of OLTC is of utmost significance. Based on a rotating angular transducer as well as digital signal processing techniques, an on-line monitoring methodology is established to measure, analyze and evaluate the dynamic or transient changes of the rotating angle of the drive motor operational in an OLTC, which can effectively indicate the underlying deficiency or even potential fault of the mechanical drive system connected to the motor. Computer simulations and experiments are carried out respectively, both showing the proposed on-line monitoring scheme is feasible and applicable.

Determination of Gas Phase Isocyanates Using Proton Transfer Reaction Mass Spectrometry

We report the development of proton transfer reaction-mass spectrometry (PTR-MS) methodology for on-line monitoring, using a direct reading instrument, of several typical gas phase isocyanates, including isocyanic acid (ICA), ethyl isocyanate (EIC), phenyl isocyanate (PhI), hexamethylene diisocyanate (HDI) and toluene diisocyanate (TDI). In the study, ICA and MIC were generated by thermal degradation of urea and 1,3-dimethylurea, respectively, while the other isocyanates were generated by liquid and gas permeation techniques. Comparative, reference measurements were made by sampling isocyanate atmosphere using impinger flasks containing the reagent di-n-butyl amine (DBA) then determining the resulting DBA derivatives by liquid chromatography (LC)-MS/MS. Reproducible measurements were obtained, with a <10 %drift in PTR-MS responses during a 12 month period. Further, there were linear correlations (R2>0.99) between the data acquired by the PTR-MS technique and air sampling followed by LC-MS/MS for all tested isocyanates in the concentration range 2–100 ppb, with a PTR-MS detection limits in the low ppb range. For all isocyanates except EIC, BIC, HDI and IPDI, the protonated molecular ions were the most abundant ions in the PTR mass spectra. Overall, the results show that the developed method enables sensitive, time-resolved measurements of airborne isocyanates to be acquired over several weeks.

Simulation and Control of Glucose Concentration in Hot‐Water Blanching of Potatoes

AbstractThe methodology for online monitoring and computer control of glucose concentration in potatoes during hot‐water blanching is demonstrated. Process conditions, control parameters, and setpoints are determined with the aid of an unsteady‐state model. Glucose concentration in the blanch water is monitored and maintained at a setpoint value by adjustment of the fresh water flow rate to the blancher, while the glucose concentration of the potatoes is calculated by mass balance. Control is effected through feedback and anticipatory feedback control. Results indicate that glucose concentration in potatoes exiting the blancher may be maintained within 10% of the setpoint value. The use of computers to control glucose concentration in potatoes should prove useful in the control of the color and therefore the quality of processed potato products.