On-line Measurement System Research Articles

Process-based modeling of energy consumption for multi-material FDM 3D printing

Purpose This paper endeavors to create a predictive model for the energy consumption associated with the multi-material fused deposition modeling (FDM) printing process.Design/methodology/approach An online measurement system for monitoring power and temperature has been integrated into the dual-extruder FDM printer. This system enables a comprehensive study of energy consumption during the dual-material FDM printing process, achieved by breaking down the entire dual-material printing procedure into distinct operational modes. Concurrently, the analysis of the G-code related to the dual-material FDM printing process is carried out.Findings This work involves an investigation of the execution instructions that delineate the tooling plan for FDM. We measure and simulate the nozzle temperature distributions with varying filament materials. In our work, we capture intricate details of energy consumption accurately, enabling us to predict fluctuations in power demand across different operational phases of multi-material FDM 3D printing processes.Originality/value This work establishes a model for quantifying the energy consumption of the dual-material FDM printing process. This model carries significant implications for enhancing the design of 3D printers and advancing their sustainability in mobile manufacturing endeavors.

Online Measurement Method and System of Excitation Impedance of Current Transformers Based on Norton's Theorem and Differential Method to Measure Difference of Two Currents.

An online measurement method is proposed in this paper, and a system is established for detecting the excitation impedance of current transformers (CTs) based on Norton's theorem. The theorem is carried out by connecting a resistance and an inductance at the secondary side port of the CT to get the equations for calculating the impedance. The iterative method is used to solve the equations, and the solution is revised to consider the nonlinearity of the core. The main variable in the equations is the variation of the secondary current with the resistance or inductance. To obtain the secondary current variation accurately, which is less than 1‱ of the current, a differential method is proposed, which is based on charging two capacitors and measuring the difference of their voltages instead of measuring each current separately first and then obtaining the current variation by subtraction. This is equivalent to saving two currents first and then measuring the current difference. The differential method avoids the problem of error amplification in the process of measuring two currents separately first and then subtracting them to obtain the current variation and solves the problem that two currents do not appear simultaneously. The results verify the correctness and accuracy of the proposed method and system. The acquisition of the excitation impedance is the basis for obtaining the working characteristics of CT cores, including magnetic and loss characteristics, as well as the error of CTs.

Precision Optimization Analysis of Online Measurement System for Laser Melting Pool Morphology in Additive Manufacturing Process

Selective Laser Melting (SLM), as the most precise and highest quality processing technology in additive manufacturing, is widely used in fields such as aerospace. Online measurement of the laser melting pool, the basic unit of the SLM process, reflects the precision and process stability of SLM. The accuracy of the online measurement system for laser melting pool morphology, which is based on the principle of visual measurement, is crucial for accurate evaluation of the laser melting pool morphology. This paper firstly conducts research on visual calibration technology for the online measurement system of laser melting pool morphology, achieving precise positioning of the visual system and effectively calculating target-related feature information, which is then converted into corresponding digital information for further processing and analysis. Secondly, the paper completes the system error analysis and parameter optimization design, effectively improving the accuracy of the visual measurement system. Finally, theoptimized online measurement system is verified for accuracy and evaluated for precision, proving the feasibility and effectiveness of the methods presented in this paper.

Online monitoring of the respiration activity in 96-deep-well microtiter plate Chinese hamster ovary cultures streamlines kill curve experiments.

Cell line generation of mammalian cells is a time-consuming and labor-intensive process, especially because of challenges in clone selection after transfection. Antibiotics are common selection agents for mammalian cells due to their simplicity of use. However, the optimal antibiotic concentration must be determined with a kill curve experiment before clone selection starts. The traditional kill curve experiments are resource-intensive and time-consuming due to necessary sampling and offline analysis effort. This study, thus, explores the potential of online monitoring the oxygen transfer rate (OTR), as a non-invasive and efficient alternative for kill curve experiments. The OTR is monitored using the Transfer-rate Online Measurement (TOM) system and the micro(μ)-scale Transfer-rate Online Measurement (μTOM) device, which was used for mammalian cells first. It could be shown that the OTR curves for both devices align perfectly, affirming consistent cultivation conditions. The μTOM device proves effective in performing kill curve experiments in 96-deep-well plates without the need for sampling and offline analysis. The streamlined approach reduces medium consumption by 95%, offering a cost-effective and time-efficient solution for kill curve experiments. The study validates the generalizability of the method by applying it to two different CHO cell lines (CHO-K1 and sciCHO) with two antibiotics (puromycin and hygromycin B) each. In conclusion, the broad application of OTR online monitoring for CHO cell cultures in 96-deep-well plates is highlighted. The μTOM device proves as a valuable tool for high-throughput experiments, paving the way for diverse applications, such as media and clone screening, cytotoxicity tests, and scale-up experiments.

Characterization of the Vaporization Inlet for Aerosols (VIA) for online measurements of particulate highly oxygenated organic molecules (HOMs)

Abstract. Particulate matter has major climate and health impacts, and it is therefore of utmost importance to be able to measure the composition of these particles to gain insights into their sources and characteristics. Many methods, both offline and online, have been employed over the years to achieve this goal. One of the most recent developments is the Vaporization Inlet for Aerosols (VIA) coupled to a nitrate Chemical Ionization Mass Spectrometer (NO3-CIMS), but a thorough understanding of the VIA–NO3-CIMS system remains incomplete. In this work, we ran a series of tests to assess the impacts from different systems and sampling parameters on the detection efficiency of highly oxygenated organic molecules (HOMs) in the VIA–NO3-CIMS system. Firstly, we found that the current VIA system (which includes an activated carbon denuder and a vaporization tube) efficiently transmits particles (> 90 % for particles larger than 50 nm) while also removing gaseous compounds (> 97% for tested volatile organic compounds – VOCs). One of the main differences between the VIA and traditional thermal desorption (TD) techniques is the very short residence time in the heating region, on the order of 0.1 s. We found that this short residence time, and the corresponding short contact with heated surfaces, is likely one of the main reasons why relatively reactive or weakly bound peroxides, for example, were observable using the VIA. However, the VIA also requires much higher temperatures in order to fully evaporate the aerosol components. For example, the evaporation temperature of ammonium sulfate particles using the VIA was found to be about 100–150 °C higher than in typical TD systems. We also observed that the evaporation of particles with larger sizes occurred at slightly higher temperatures compared to smaller particles. Another major aspect that we investigated was the gas-phase wall losses of evaporated molecules. With a more optimized interface between the VIA and the NO3-CIMS, we were able to greatly decrease wall losses and thus improve the sensitivity compared to our earlier VIA work. This interface included a dedicated sheath flow unit to cool the heated sample and provide the NO3-CIMS with the needed high flow (10 L min−1). Our results indicate that most organic molecules observable by the NO3-CIMS can evaporate and be transported efficiently in the VIA system, but upon contact with the hot walls of the VIA, the molecules are instantaneously lost. This loss potentially leads to fragmentation products that are not observable by the NO3-CIMS. Thermograms, obtained by scanning the VIA temperature, were found to be very valuable for both quantification purposes and for estimating the volatility of the evaporating compounds. We developed a simple one-dimensional model to account for the evaporation of particles and the temperature-dependent wall losses of the evaporated molecules, and we thereby estimate the concentration of HOMs in secondary organic aerosol (SOA) particles. Overall, our results provide much-needed insights into the key processes underlying the VIA–NO3-CIMS method. Although there are still some limitations that could be addressed through hardware improvements, the VIA–NO3-CIMS system is a very promising and useful system for fast online measurements of HOMs in the particle phase.

A dynamic electrochemiluminescence system for continuous on-line measurements based on potential stepping pulse strategy

A dynamic electrochemiluminescence (ECL) detection system combining flow injection analysis with a potential stepping pulse strategy was developed. It contains a flow injection unit that carrying the sample solution flow through a specially designed ECL detection cell continuously, ensuring the valid renew of the test solution and thus is favorable for continuous on-line measurements. This dynamic ECL analytical system based on potential stepping pulse strategy is very efficient and time-saving. Taking the ruthenium(II) tris(bipyridine) (Ru(bpy)32+)-tripropylamine (TPA) system as an example, the ECL responses to step pulse potentials and pulse period, as well as the sample flow rate were examined. Under optimized experimental parameters, the proposed protocol was further successfully applied for the continuous detection of TPA, and malachite green based on its inhibitory effect on the ECL of Ru(bpy)32+-TPA system with a limit of detection of 17.77 nM. The relative standard deviation of 97 cycles measurements was only 0.46 % under ideal conditions. The results indicate that this system could provide reproducible and reliable ECL signals. As a versatile and efficient ECL detection protocol, it has a broad prospect of application.

Dynamic evolution investigation on crystal size and morphology of sodium sulfate based on a combination of ultrasonic and image on-line testing

Crystallization is widely used in the fine chemical processes of purification and separation, where the crystal size variation, together with the crystallization temperature, plays a crucial role. An online measurement system for the simultaneous characterization of crystal size and other morphological parameters was studied, in which an ultrasonic spectrometer and image analysis was effectively combined for the monitoring and understanding of key parameters during the entire crystallization of sodium sulfate solution. The change in crystallization temperature, crystal size, and morphology at different cooling rates and stirring rates were analyzed, which shows that the cooling rate plays a dominant role in the variation of the critical time of crystal precipitation and average crystal size. In the middle stage of the crystallization, the median diameter change obtained by the ultrasonic and image analysis is close together, with a relative deviation of less than 10%. While the aspect ratio is mainly distributed in the range of 1–1.6, the crystal size has a relatively stable growth rate. An ultrasonic spectrometer can be used to measure particle size distribution of higher concentrations compared with image analysis. The combination actually provides an effective complement to implementing straightforward testing during the relatively complete crystallization process.

On-Line Metal Concentration Measurement at an Ultra-Trace Level in DIW by Solid Phase Extraction Method Coupled with ICP-MS

Metal contamination is a critical issue in semiconductor manufacturing processes, where controlling the concentration of metals in the deionized water (DIW) used for wafer rinsing and chemical dilution is necessary. In our previous study, we reported an ultra-trace level measurement method using solid-phase extraction (SPE) with a monolithic resin and inductively coupled plasma mass spectrometry (ICP-MS). However, this method had limitations regarding rapid metal concentration confirmation and contamination risks due to manual processing and sample delivery. This study proposes an on-line metal measurement system that uses an automated SPE technique coupled with ICP-MS to address the shortcomings of the conventional method. The system provides continuous on-site monitoring of ultra-trace metal concentrations in DIW, reducing preconcentration volume by up to 60% compared to the conventional method owing to minimizing contamination by automating all processes. Moreover, the system achieved reliable results similar to the conventional method, high analytical stability, with the relative standard deviations (RSDs) within 5% for a concentration of around 0.05 ng/L (n=4) using a test solution. We also evaluated the metal removal filter as an application of the system mentioned above, simultaneously analyzing multiple elements at the single-pg/L level and confirming the performance of the filter.

Online measurement system of slab front-end bending in hot rough rolling based on line structured light vision

Front-end bending is one of the most significant defects of slabs in hot rough rolling. To address the lack of effective methods to detect slab front-end bending in hot rolling, a measurement system based on line structured light vision is proposed in this paper. Line structured light lasers and area-scan cameras are arranged on the supports on both the exit and entrance of a roughing mill. First, the calibration of the measurement system is completed by camera calibration and the random sampling consistency algorithm. Second, multiple regions of interest gray thresholds and the Steger algorithm are used to realize laser centerline extraction on the surface of a large-scale and high-temperature slab. Last, the actual value of the slab front-end bending is obtained and calculated through coordinate transformation. The proposed measurement system can detect slab front-end bending in real time and the relative mean deviation is 0.93%.

Optimized Design of Source Energy for Manufacturing Machine by Digital Numerical Control

The quality of the power supplied to the machining center is a key factor in determining the accuracy of the machine’s operation. The precision of the machining center is to ensure that the spindle accuracy is less than 3 microns. This study proposes a digital numerical control system to control the quality of the power supply and control the accuracy of the spindle axis of the machining center to monitor the measurement results in real time. The computer vision system is set up according to the artificial intelligent (AI) technique to recognize human face objects and control the position of the processor respectively on each line. The online measurement system follows the digital numerical control (DNC) system applied at each processing line, measuring product dimensions, measuring conditions for setting up machining tools, and measuring machine coordinates. The system operates fully automatically, eliminating dependence on operator skill, and facilitating operation in control of machining conditions. Improve machining center operator satisfaction. After implementation of the improvement options, total cost down 1.740 USD per year, the monthly repair cost due to broken drill, spindle alignment decreased from $5000 to $3,300 per month. The scrap rate related to the hole size decreased from 0.47% to 0.23% (cost down $35 per month). Downtime for repair reduced from 20 hours per month to 7.5 hours per month (cost down $10 per month). Broken drill rate was reduced from 0.20% to 0.06% (cost down $100 per month).

The characteristics of gas-liquid dispersive mixing and microbubble generation in turbulent adjustable jet flow field

In this study, the gas-liquid two-phase mixing process and the microbubbles formation process in a jet flow field has been investigated by using a self-designed on-line measurement system for measuring bubble generation characteristics and the Volume of Fluid (VOF) model in numerical simulation methods for analyzing flow field distribution characteristics. The effect of turbulence intensity on the dynamic size distribution of microbubble has been considered. The characteristics and duration of the three stages during the bubble breaking process, namely, surface oscillation stage, surface tension stage and fracture stage, were analyzed. The results show that the increase of turbulence intensity in jet flow will further promote the imbalance between the external deformation force and the surface tension resisting the deformation of the bubble, and promote the breaking probability of bubble. However, when the bubble breaks to a sufficiently small size, the surface tension against bubble deformation will increase sharply, the surface free energy needed to overcome for bubble breakage is very large, and the breakage probability of bubble will significantly decrease. Compared with the breaking process of bubbles, the increase in turbulence intensity will greatly promote the bubble coalescence process, which will ultimately become the main reason for affecting the bubble size distribution. Moreover, the influence of flow field distribution characteristics on bubble size distribution and average bubble size change is analyzed by using Population Balance Model.

Practical Online Characterization of the Properties of Hydrocracking Bottom Oil via Near-Infrared Spectroscopy

Providing real-time information on the chemical properties of hydrocracking bottom oil (HBO) as the feedstock for ethylene cracker while minimizing processing time, is important to improve the real-time optimization of ethylene production. In this study, a novel approach for estimating the properties of HBO samples was developed on the basis of near-infrared (NIR) spectra. The main noise and extreme samples in the spectral data were removed by combining discrete wavelet transform with principal component analysis and Hotelling’s T2 test. Kernel partial least squares (KPLS) regression was utilized to account for the nonlinearities between NIR data and the chemical properties of HBO. Compared with the principal component regression, partial least squares regression, and artificial neural network, the KPLS model had a better performance of obtaining acceptable values of root mean square error of prediction (RMSEP) and mean absolute relative error (MARE). All RMSEP and MARE values of density, Bureau of Mines correlation index, paraffins, isoparaffins, and naphthenes were less than 1.0 and 3.0, respectively. The accuracy of the industrial NIR online measurement system during consecutive running periods in predicting the chemical properties of HBO was satisfactory. The yield of high value-added products increased by 0.26 percentage points and coil outlet temperature decreased by 0.25 °C, which promoted economic benefits of the ethylene cracking process and boosted industrial reform from automation to digitization and intelligence.

Further refinements of a continuous radon monitor for surface ocean water measurements

Radon is an excellent natural tracer for studying various geophysical processes. In the past centuries, radon isotopes measurement approaches for marine research have been fully developed but still suffer limitations. Here we present the setup and validation of an improved continuous online measurement system (PIC-ORn) to measure dissolved radon in the surface ocean and other water bodies. We demonstrated that the PIC measurement efficiency is ~2 times higher than a RAD7 and is less affected by relative humidity and produces reliable results. Laboratorial measurements indicated that the new PIC-ORn system responded timely to the change of radon activities in water. The new system was successfully deployed during a cruise to the northwest Pacific Ocean in June 2021. Despite low radon-in-water activities, the results obtained by the new PIC-ORn system matched the traditional measurement systems within the estimated uncertainties. The PIC-ORn detector takes advantage of higher efficiency, lower cost, and power consumption, and is less affected by air moisture. The new system does not rely on drying units, further reducing on-site supervision, which would benefit the researches in submarine groundwater advection and diffusion and ocean-atmosphere gas exchange.

Improvement in the efficiency of the five-axis machining of aerospace blisks.

Blisks are not easily machined because of their complex curved surfaces and the high-precision requirements of surface machining. Lightweight alloy materials with superior mechanical properties, such as titanium alloy and stainless steel, are popular material choices for manufacturing turbine blisks. However, these materials are difficult to cut and require advanced machine tools and processing technologies. Because aerospace-grade parts are complex and require precise dimensions and high surface quality, machining these parts by using three-axis machine tools is difficult. Using multi-axis machine tools for the machining of complex parts can cause the achievement of precise dimensions, high quality, and the required surface roughness. In the multi-axis machining of aerospace blisks, tool path planning is considered the most difficult task. In this study, we examined the implementation of five-axis machining technology for the manufacturing of an aerospace blisk. Processing modules from computer-aided manufacturing software (NX10) are used for five-axis tool path generating, and 5-axis machining numerical control code is generated through post-processing calculations. Solid cutting simulation software (VERICUT) is used to verify whether tools exhibited overcut or interference. A sensory tool holder (SPIKE) is used to analyze cutting force during the rough machining of a blisk. The sensory tool holder is also adopted to evaluate the spindle runout and tool holding status. In order to obtain a consistent cutting allowance and surface accuracy, the online measurement system is used to generate a measurement path for semi-finish and finish machining. The real cut is performed with SUS304 and demonstrates the practical application. Through improvements in process planning, the machining time was shortened by 16.5%.

Online deviation measurement system of the strip in the finishing process based on machine vision

In the production of hot rolling, the deviation of the strip in the finishing process has always been a technical problem that plagues enterprises. However, there is currently no effective measurement method for the deviation of the strip in the finishing process. To this end, this paper proposed a non-contact strip deviation online measurement scheme based on machine vision technology and image detection. On the one hand, the principle of deviation measurement of binocular line scan camera and the error compensation model was established. On the other hand, a new calibration principle of binocular line scan camera was established, corresponding to the measurement principle. Finally, the real-time deviation of the strip was calculated. The field experiment showed that the strip deviation measurement system in this paper has high measurement precision and could be well adapted to the changing of the strip height.

Detection of pears with moldy core using online full-transmittance spectroscopy combined with supervised classifier comparison and variable optimization

Moldy core is a serious disease that influences the quality of pears. There is no apparent difference between the diseased and sound fruit because this kind of disease mainly occurs in core of pears. In automatic detection and grading of pear quality, it is very desirable to detect pears with moldy core, especially at the early stage. This study used the visible and near infrared (Vis/NIR) full-transmittance spectroscopy, combined with wavelength selection algorithms and supervised classifiers, to discriminate 'Ya' pears with moldy core. The spectra of pears were collected using an online measurement system. Savitzky-Golay smoothing and standard normal variables (SGS-SNV) were used to preprocess the spectra. Four variable selection algorithms, including Monte Carlo-uninformative variable elimination (MC-UVE), bootstrapping soft shrinkage (BOSS), combination algorithm MC-UVE-SPA (successive projections algorithm), and combination algorithm BOSS-SPA, were used to extract the effective wavelengths. Four supervised classifiers, including support vector machine (SVM), least squares-support vector machine (LS-SVM), random forest (RF), and partial least square discriminant analysis (PLS-DA), were used for modeling. The two-class classification (i.e., sound and diseased) and the three-class classification (i.e., sound, slightly moldy, and severely moldy) models were established based on full wavelengths and selected wavelengths, respectively. The performance of all models was evaluated by considering some indicators such as 'Tolerability', ‘Stability’, ‘Accuracy’ and ‘Complexity’. It indicated that BOSS-SPA-PLS-DA and BOSS-SPA-LS-SVM were the optimal models for two-class and three-class classification with the overall accuracy of 99.76 % and 94.71 %, respectively. This study indicated that the online detection of 'Ya' pears with moldy core using the Vis/NIR full-transmittance spectra technology was feasible. Moreover, the proposed method has the potential to be used for online detection of early moldy core.

Online measurement of the elastic recovery value of machined surface in milling titanium alloy

This paper aimed to obtain the elastic recovery value of the machined surface of the workpiece in the milling process of titanium alloy, because it can cause strong friction between the tool flank and the workpiece surface. A new online measurement system was designed to monitor the elastic recovery behavior of Ti6Al4V alloy in dry milling based on the digital image correlation (DIC). DIC measurement principle was intuitively analyzed by means of picture illustration. The orthogonal milling experiments were designed with different cutting parameters and the experiment processes were designed in detail, including the installation of DIC measurement system, the speckle disposal of the measured surface and the field calibration of test instrument. The displacement curve of the target region was analyzed according to the material deformation characteristics of metal materials in the cutting process and thus the calculation method of elastic recovery value of machined surface was obtained. Besides, the optimization method of cutting parameters with the minimum elastic recovery value in titanium alloy milling was also obtained, which can be expanded to the machining measurement of other difficult -to-machine materials.

Analysis of gamma spectra from burnup measurement in HTR-10

HTR-10, the 10 MW pebble-bed High Temperature Gas-cooled Reactor-Test Module designed by Tsinghua University, achieved its first criticality in 2000. One of the unique features of HTR-10 is the continuous fuel feeding achieved by its fuel cycle system, in which the fuel sphere is allowed to pass through the core several times before discharged out. During the fuel circulation, the on-line burnup measurement system is used to ensure fuel credit. Up to now, after nearly 21 years of operation, huge data including gamma spectra have been collected by this on-line burnup measurement system. In this paper, the gamma spectra data collected from Nov. 2005 to Mar. 2006 are analyzed to identify the radionuclides left in the irradiated fuel sphere after a long decay. The analysis includes energy identification, decay scheme confirmation, activity estimation and so on. This work shows that radionuclides and corresponding activities are preliminarily identified, which lays a base for R&D of new burnup measurement apparatus and the profiling of fuel irradiation history. That would help to increase accuracy for the nuclear material accounting and to improve the operation strategy of pebble bed high-temperature gas-cooled reactors.

Design and Structure of an Electronic Switching System for Remote Circuits Structuring and Online Measurements

this paper presents design and structure of an electronic switching system for remote circuits structuring through internet, where the possibility of building circuits from scratch while conducting electrical measurements at any point of built circuits by online experimenters. This switching system enables to interconnect between electrical and electronic components in different combinations of circuits while providing an online environment highly approximated to physical environments of traditional hands-on laboratories in terms of manipulating measurement instruments and building experimental circuits. This paper also presents results of deployed topology for remote exploit of this switching system along with results of its deployed online engineering experiments.

Non-destructive prediction of soluble solid contents in Fuji apples using visible near-infrared spectroscopy and various statistical methods

The increasing awareness regarding dietary diversity and pattern has increased the demand for quality over quantity. Numerous non-destructive measurements, including visible near-infrared spectroscopy, have been used in assessing the soluble solid content (SSC) in foods. With advances in statistics, various statistical methods have been developed. These methods need to be verified for their application in effective SSC prediction models. This study aims to review the utility of various statistical methods for the SSC prediction of apples. In this study, we constructed a sorting device for Fuji apples. The spectra of the apples were measured, and the potential of the SSC prediction model was evaluated using various pre-processing methods and machine learning techniques. A developed support vector regression model with a first-order derivative method exhibited the highest prediction accuracy (R 2 = 0.8503, RMSEP = 0.4781). Therefore, the developed efficient spectrum pre-processing method coupled with a robust machine learning model was useful for improving the prediction performance of the sorting device. • Spectra of apples and SSC values were measured. • Spectra were acquired using online measurement system functioning like actual sorting condition. • Various preprocessing methods and machine learning techniques were used. • Spectrum preprocessing with robust statistical regression model improves SSC prediction.