Measurement Technology Research Articles

Non-contact laser vibrometry for rock failure precursor analysis: a comparative study with AE methods

ABSTRACT To explore the precursory characteristics of failure in fractured sandstone. This paper uses laser vibration measurement technology and acoustic emission (AE) technology to monitor the failure process of red sandstone. The wavelet packet energy entropy (WPEE) method was used to process rock vibration data, indicating a sharp increase in WPEE as a precursor to rock failure. Concurrently, ring count, b-value, variance, and autocorrelation coefficient (AC) methods were applied to analyze AE precursors.The results show that ring count, variance, and AC increase significantly while the b-value decreases sharply prior to rock failure. These changes can all be used as precursor information of rock failure. Subsequently, in order to compare the advantages of different methods, we proposed a comparative framework that includes the timeliness, stability, and discriminability of predictions. The results indicate that the discriminability and stability of ring count and variance are the best, but their timeliness is the worst. The timeliness of b-value and autocorrelation coefficient is the best, but their stability and discriminability are the worst. The timeliness, stability, and distinguishability of WPEE are all in the middle position, and its overall performance is relatively good compared to other methods.

Eulerian Parameter Inference: a probabilistic change of variables for model-based inference with high-variability data sets

Advances in measurement technology have led to the generation of increasingly large data sets across various scientific fields. Data that capture the variability of the underlying system or process, such as single-cell or imaging data, are particularly interesting. However, calibrating computational models to explain this type of data remains challenging.We interpret the model calibration as a Stochastic Inverse Problem (SIP), where the measurements are interpreted as probabilistic samples. Our new SIP solution approach, Eulerian Parameter Inference (EPI), only requires data with large empirical variance and a deterministic simulation model that maps model parameters to simulation results. EPI solves the SIP through a change of variables. This computationally efficient approach allows for direct and point-wise evaluation of parameter densities without ever inverting the simulation model. The resulting parameter distribution captures data variability completely, enabling full data reconstruction. Further, estimating multivariate model parameters can be reduced to a series of one-dimensional problems under the assumption of stochastically independent parameters. This property is vital for complex simulation models and involved problems.With EPI, we explain 1) annual average temperature data of 3168 weather stations around the world with an arithmetic model, 2) German district-specific COVID-19 infection data through a differential equation model, and 3) artificial data generated via a partial differential equation model with independent parameters. With a robust mathematical foundation and an easily accessible Python package, we provide a versatile solution framework for integrating data with a high variance into simulation models that promotes application to various research questions.

Distance Estimation with a Stereo Camera and Accuracy Determination

Distance measurement plays a key role in many fields of science and technology, including robotics, civil engineering, and navigation systems. This paper focuses on analyzing the precision of a measurement system using stereo camera distance measurement technology in the context of measuring two objects of different sizes. The first part of the paper presents key information about stereoscopy, followed by a discussion of the process of building a measuring station. The Mask R-CNN algorithm, which is a deep learning model that combines object detection and instance segmentation, was used to identify objects in the images. In the following section, the calibration process of the system and the distance calculation method are presented. The purpose of the study was to determine the precision of the measurement system and to identify the distance ranges where the measurements are most precise. Measurements were made in the range of 20 to 70 cm. The system demonstrated a relative error of 0.95% for larger objects and 1.46% for smaller objects at optimal distances. A detailed analysis showed that for larger objects, the system exhibited higher precision over a wider range of distances, while for smaller objects, the highest accuracy was achieved over a more limited range. These results provide valuable information on the capabilities and limitations of the measurement system used, while pointing out directions for its further optimization.

From Individual Observations to Global Assessments: Tracing the Marine Carbon Knowledge Value Chain

Marine carbon observations (MCOs) provide essential data to trace historical and current changes in marine carbon storage and fluxes that ultimately feed into the Global Carbon Budget and the Intergovernmental Panel on Climate Change report. Therefore, MCOs play a key role in informing global climate policy as well as ocean governance. However, they only achieve this potential if multiple sources of observations are combined and analyzed jointly. This implies an immense coordination effort by the international MCO community which developed, e.g., joint standards for the collection of (meta‐)data, quality control processes, data platforms, etc. This article traces the value chain of MCOs, concretely for CO2, from data collection to the Intergovernmental Panel on Climate Change report. Based on an interdisciplinary research project, the study illuminates which structures and practices the marine carbon community has developed to integrate different observations and measurement technologies, starting from German research institutes and agencies and expanding to the European and international networks to which they contribute. Combining a social network analysis with qualitative insights from in‐depth interviews, the article identifies key information providers and brokers and pinpoints systemic vulnerabilities, e.g., where connections between observation networks or data platforms are maintained based on personal relationships or ad‐hoc interactions rather than automated data submissions, or where temporally limited third party funding threatens the continued existence of the observation network.

Technology Focus: Bits and Bottomhole Assemblies (December 2024)

Drillstring dynamics has been a central focus of research and mitigation efforts in the drilling industry for many years. The effect of dysfunction and poor dynamic motion extends far beyond simply reducing the lifespan of drilling equipment. When these issues degrade borehole quality to the extent that petrophysical measurements become compromised, managing these dynamics becomes crucial. Addressing drillstring dynamics in these cases effectively can be the key to improving our understanding of reservoir characterization, which directly affects hydrocarbon-recovery strategies. Neglecting to manage these dynamics thus not only risks immediate operational setbacks but also threatens to diminish overall hydrocarbon recovery. The integration of the latest state-of-the-art technology in modeling and measurement of drilling dynamics and borehole quality has enhanced the understanding of bit, bottomhole assembly (BHA), and drillstring design. This can be seen in recent work on analysis of cutter-formation interaction, borehole-quality improvement, and modeling improvements. This progress allows drilling teams to make more-informed, proactive adjustments to drilling parameters, thereby avoiding the negative consequences of dysfunction. As the drilling industry shifts its focus toward geothermal drilling, understanding and modeling drillstring dynamics takes on even greater importance. Geothermal drilling frequently encounters harder igneous and metamorphic rocks, which pose unique challenges. In these conditions, the performance of the drill bit, BHA, and drillstring becomes critical. Accurate modeling and effective management of these dynamics are essential to optimizing drilling efficiency and minimizing the risk of equipment loss or operational failures. In this context, ongoing research and innovation in both drillstring dynamics and its modeling are vital to the success of geothermal, hydrocarbon, and other drilling projects. Yet the best mitigation applied may not be the latest but existing tried and tested equipment. Recommended additional reading at OnePetro: www.onepetro.org. OTC 35320 Applications, Results, and Lessons Learned From Using Roller Reamers in Hard, Abrasive Formations—The FORGE Project Application by E. Almanza, Redback Drilling Tools, et al. SPE 217939 Avoiding High Local Doglegs by Integrating the Drill Bit Into the Rotary Steerable System by M. Hahn, Baker Hughes, et al. SPE 220789 Modeling PDC Cutter Loads When Drilling Interbedded Formations at Constant Penetration per Revolution vs. Weight on Bit by Paul E. Pastusek, Pastusek and Associates, et al.

A structural scheme design of internal thread detection based on laser profile scanning

Abstract Based on the analysis and comparison of the advantages and disadvantages of various existing thread detection methods, a kind of internal thread detection equipment and detection method based on laser contour scanning is designed, involving intelligent non-destructive testing technology and laser precision measurement technology, which can be extended into the workpiece to be measured, especially for various kinds of workpiece with small diameter of internal thread and cannot be accurately measured by the measuring device. Through the laser profile scanner and optical reflection element, the internal thread size of the workpiece, including large diameter, small diameter, pitch, thread length, thread chamfer, thread chamfer diameter, and other parameters, can be measured with high precision and high efficiency, and the detection efficiency is high. There is no need to touch the workpiece to achieve a non-destructive inspection of the workpiece surface. The test results are accurate, comprehensive, and reliable.

Optimized binarization algorithm-based method for the image recognition and characterization of explosion damage in rock masses

The quantitative analysis of rock mass damage is crucial in fields such as engineering geology, disaster prevention, mining, geotechnical engineering, and structural engineering. With the advancement and application of noncontact measurement technologies and fractal theory, image-based damage identification methods are gaining increasing importance. This paper presents an optimized binarization algorithm for identifying and characterizing damage zones in granite explosion images. The method involves filtering, mathematical morphology operations, and connectivity recognition to effectively remove background noise while preserving clear boundaries of the damaged areas. It accurately captures the explosion damage in granite, both in terms of damage morphology and characteristic parameters. Additionally, the coefficient of agreement (COA) is introduced to quantitatively assess the accuracy of different methods in identifying damaged areas. The experimental results show that, compared with commonly used methods such as Otsu's method, Bernsen's algorithm, Niblack's algorithm, Sauvola's algorithm, and the K-means image clustering algorithm, the proposed method performs better in terms of identification accuracy and parameter agreement, achieving COA values near 1 across diverse experimental environments. Furthermore, the proposed method excels in handling uneven lighting, mitigating interference from rock surface textures and explosion carbonization zones, and demonstrates significant robustness in complex scenarios. The findings of this paper provide insights into the integration of engineering geology and computer vision technology. They offer valuable references for damage identification in excavation damage zones (EDZs), geological disaster evaluation, and structural damage warning systems.

Methodology for measuring greenhouse gas concentrations at a test site near the Blue Bay (northeast of the Black Sea)

The article presents the results of monitoring the concentrations of carbon dioxide (CO2), methane (CH4), volatile organic substances (VOCs) and a mixture of ozone and nitrogen dioxide carried out at a test site located in the Blue Bay area (Gelendzhik). The technical capabilities of the scientific equipment used and the features of the methodology for working with it are described. An analysis of the data acquisition process was performed, and some optimizations of measurement technology and statistical processing were shown in order to increase the reliability of the results. A brief summary of the measurements performed is given. During the research, the concentration of greenhouse gases and harmful substances was within the global average.

A novel effective stress sensor based on FBG sensing technology for effective stress measurement in soil

The effective stress in saturated soil is typically indirectly measured in geotechnical engineering. Thus, the present study developed an equal-strength cantilever beam effective stress sensor (ECB-ESS) based on fiber Bragg grating technology that can measure the effective stress directly. ECB-ESS can significantly eliminate the wavelength measurement error caused by uneven strain along the grating because of the advantage of equal strain distribution along the cantilever beam. To further validate the superiority of the equal-strength cantilever beam structure from both initial and actual performance aspects, comparison tests are conducted using both water pressure calibration and earth pressure calibration methods. To fully evaluate the performance of the ECB-ESS, water pressure test, earth pressure test, and temperature test were conducted separately. Additionally, the capability of the sensor to measure effective stress under different loading levels was examined through effective stress test.

Development of Non-Invasive Continuous Blood Pressure Measurement System Based on Multiple Feature Parameters

To address the issue of the difficulty in implementing non-invasive continuous blood pressure measurement technology in China, this study developed a high-performance synchronous electrocardiogram (ECG) and photoplethysmography (PPG) signal acquisition system. A PC-based human-computer interaction software platform was constructed, and continuous blood pressure measurement-related algorithms were integrated. Multiple feature parameters such as pulse wave transit time based on synchronous ECG and PPG signals were extracted, enabling non-invasive continuous blood pressure measurement. To verify the measurement accuracy of the system, tests and comparative verifications were carried out. The results demonstrated that the system could meet the requirements of relevant standards and have good application value.

Full-scale testing of the bending behaviour of UHPC gravity–grouted sleeve–prestressed anchor joints in assembled frame tunnels

Joints are weak parts of a prefabricated tunnel frame structure, and the joint bending resistance is a crucial factor controlling the deformation and bearing capacity of the tunnel structure. This study proposes a joint with dual anchoring of ultrahigh-performance concrete (UHPC) gravity-grouted sleeves and prestressed steel reinforcement. The material strain, opening amount, deflection, stiffness, rotation angle, and ductility of the grouted sleeve-prestressed anchor joint and grouted sleeve joint types were tested through full-scale bending tests, and with the help of noncontact measurement technology, the dynamic process of joint bending failure was captured. In addition, the finite element method was used to evaluate the influences of the prestressing magnitude and the position of the prestressing steel bars on the bending performance of the joints. The results indicate that the damage to the concrete joint is concentrated at the top of the joint and that the damage to the top surface of the joint concrete is distributed in an "m" shape, indicating that the damage to the concrete in the area between the sleeves is relatively extensive. Owing to the turning points of grouting material fracture and joint yielding, the joint bending process clearly shows a three-stage change. The grouted sleeve-prestressed anchor joint exhibits greater bending stiffness than the grouted sleeve joint does, and the slip of the grouting material in the sleeve is smaller. Prestressing plays a key role in enhancing the bearing capacity and deformation resistance of joints. Considering that excessive prestress may increase the brittleness of the structure, the prestress of the grouted sleeve-prestressed anchor joint is recommended to be 200 kN. This study provides theoretical support for the joint design and construction of prefabricated tunnel frame structures.

The Dual Face of Smart Glasses: Health Benefits, Lifestyle Convenience, and the Hidden Challenges

Smart wearable devices have transformed how individuals track health and manage daily activities, providing real-time insights into vital signs and convenient fitness monitoring. Yet, these advancements come with challenges, including data privacy risks, measurement accuracy concerns, and potential over-reliance for health decisions. This study aims to balance the promise of health benefits and lifestyle convenience against these challenges. Limitations include evolving data security standards and measurement technologies, suggesting that future smart wearables should prioritize user safety through enhanced security and more robust health metrics.

Non-contact measurement method of liquid composition using microwave radar cross-section

This study aims to provide a non-contact detection of liquid composition inside containers using Microwave Radar Cross-section (RCS) measurement technology. Firstly, it analyzes the limitations of traditional near-infrared spectroscopy methods and proposes the necessity of introducing microwave detection methods. The research demonstrates through experiments a significant correlation between polar substances like total acid content and radar scattering capability, showing microwave radar’s effectiveness in reflecting the polarity characteristics of liquids. Furthermore, theoretical derivations and experimental validations illustrate that differences in electromagnetic properties of different liquid components lead to variations in echo loss, thereby impacting RCS levels. Experimental results indicate that microwave radar RCS measurement technology achieves an accuracy level of 2%, capable of distinguishing between different concentrations of ethanol, acetic acid, and other solutions. This study highlights the significant advantages of microwave radar RCS measurement technology in non-contact detection of liquid composition, providing new methods and a technological foundation for precise liquid component detection.

Computer Vision Technology for Short Fiber Segmentation and Measurement in Scanning Electron Microscopy Images

Computer vision technology for the automatic recognition and geometric characterization of carbon and glass fibers in scanning electron microscopy images is proposed. The proposed pipeline, combining the SAM model and DeepLabV3+, provides the generalizability and accuracy of the foundational SAM model and the ability to quickly train on a small amount of data via the DeepLabV3+ model. The pipeline was trained several times more rapidly with lower requirements for computing resources than fine-tuning the SAM model, with comparable inference time. On the basis of the pipeline, an end-to-end technology for processing images of electron microscopic fibers was developed, the input of which is images with metadata and the output of which is statistics on the distribution of the geometric characteristics of the fibers. This innovation is of great practical importance for modeling the physical characteristics of materials. This paper proposes a few-shot training procedure for the DeepLabV3+/SAM pipeline, combining the training of the DeepLabV3+ model weights and the SAM model parameters. It allows effective training of the pipeline using only 37 real labeled images. The pipeline was then adapted to a new type of fiber and background using 15 additional real labeled images. This article also proposes a method for generating synthetic data for training neural network models, which improves the quality of segmentation by the IoU and PixAcc metrics from 0.943 and 0.949 to 0.953 and 0.959, i.e., by 1% on average. The developed pipeline significantly reduces the time required to evaluate fiber length in scanning electron microscope images.

High-stability adaptive frequency comparison method based on fuzzy area characteristics

To meet the high-accuracy requirement of time and frequency measurement and its synchronization in complex environment, a high- stability adaptive frequency comparison method based on fuzzy area characteristics is proposed in this paper. First, the frequency of the measured signal is measured by using FPGA and pulse-filling frequency measurement technology to obtain the frequency coarse value of the measured signal. Second, a communication protocol between FPGA (Field Programmable Gate Array) and DDS (Direct Digital Synthesizer) is established to enable DDS to recognize the information from FPGA. Third, the frequency coarse value of the measured signal is sent to FPGA and converted into the corresponding “frequency word” by DDS. Finally, according to the communication protocol between FPGA and DDS, an adaptive frequency standard signal with the same frequency coarse value as the measured signal is generated by controlling the DDS with the “frequency word”. Then there is a small relative frequency deviation between the frequency of the measured signal and the frequency of the adaptive frequency standard signal. The experiment results show that the frequency stability based on the proposed method can reach 1.76 × 10-13 /s, and the accuracy of the frequency synchronization is better than 5 Hz.

Predicting wave run-up on vertical columns based on thermal stereography measurements

Accurate estimation of wave run-up is crucial for the design and safety of marine structures. To facilitate more precise and convenient predictions of wave run-up on vertical columns, including circular and square columns, many empirical formulas have been proposed. However, those derived from wave probe measurements typically underestimate the maximum wave run-up height due to the inability of wire-type wave gauges to closely adhere to the column surface. This study employed the non-contact wave measurement technology based on thermal stereography to measure the wave run-up distributions on vertical columns under regular waves, providing a more accurate measurements of wave run-up closer to the column surface. Utilizing the measurements, a modified formula was proposed to predict the wave run-up on circular columns. Additionally, considering the effects of scattering parameter (kD) and wave steepness (kηmax), a new empirical formula for predicting the wave run-up on square columns was developed based on the velocity stagnation head theory. These formulas were validated using the experimental data from the present study and the literature, demonstrating their ability to provide satisfactory wave run-up predictions. Furthermore, the spatiotemporal wave evolution for circular and square columns were compared. The wave profile in front of the circular cylinder at a half diameter tends to flatten, with water flowing along the cylinder surface to the sides, leading to a significantly lower wave run-up height ratio compared to the square column. This study provides the valuable insights for predicting the wave run-up on vertical columns, contributing to the design and safety assurance of marine structures.

High‐Pressure Reactor Technology for Aerated Biotransformations

AbstractUtilizing pressure as a process parameter can make biotechnological processes more efficient and attractive compared to established ones. This paper presents a high‐pressure reactor setup for enzymatically catalyzed gas–liquid reactions, which can be operated up to 15.0 MPa. The reactor is equipped with optical measurement technology for inline and in situ monitoring of the oxygen concentration under high‐pressure conditions. The setup is characterized by assessing the influence of the process parameter pressure on the conversion of the glucose oxidation to d‐glucono‐δ‐lactone by immobilized glucose oxidase. The study demonstrates that the increased oxygen availability due to higher solubility reduces the reaction time in a batch reactor from 270 to 90 min.

A Review of Research Progress in Carbon Monitoring and Carbon Metering Methods: Comparison at Home and Abroad

Carbon monitoring and carbon measurement are not only important foundations for realizing the marketization of carbon trading, but also a key link in realizing China’s strategic “dual carbon” goal. The aim of this research is to comprehensively summarize and compare carbon monitoring and carbon metering technologies, as well as to analyze their current status and challenges. This study adopts literature research, comparative analysis, case analysis, policy interpretation, and other methods to comprehensively and deeply explore the relevant content of carbon monitoring and carbon metering technology. An in-depth exploration of relevant methods, standards, and applications provides a reference for promoting the sustainable development of global carbon monitoring and carbon metering technologies. By summarizing the difficulties of carbon monitoring and the characteristics of existing technologies, as well as comparing carbon measurement methods and the relevant measurement standards, this paper focuses on the difficulty of carbon monitoring, which lies in the credibility and accuracy of the data, where remote sensing technology possesses higher applicability. The principles of carbon measurement methods mainly include direct underlying data measurements, indirect measurements through statistical modelling, and market mechanism measurements. The relevance and precision of carbon measurement methods have been gradually strengthened as the measurement standards have been developed and implemented. Finally, future development directions and relevant suggestions will be described in detail and put forward in combination with the application of carbon monitoring and carbon measurement. Among them, blockchain technology is considered to be one potential area for future development, and data standardization will play an important role in the development of carbon monitoring and measurement technology. We recommended establishing and perfecting data-sharing mechanisms in future policies to improve the accuracy and credibility of data.

Optimal Prototyping with Noisy Measurements

Problem definition: Prototyping and testing are an integral part of almost any new product development process, helping firms navigate the inherent uncertainties of creating new products. Recent developments in rapid prototyping, including technologies that enable cheaper low-fidelity tests, have opened up the possibilities for firms in reconfiguring their product development processes. Firms can, by choosing the level of evaluation fidelity, alter the traditional cost-quality trade-offs inherent in sequential prototyping. Methodology/results: The current article formulates a general model of sequential search where firms can proceed by obtaining noisy low-fidelity evaluations of their prototypes. Our results demonstrate that the imperfect fidelity of evaluations alters the firm’s optimal experimentation, with the starkest difference being that it may make it optimal for the firm to select and launch a prototype that did not yield the best evaluation. In addition, our analysis of optimal measurement technology reveals that the focal firm should demand the most precise measurements when their ex-ante uncertainty is moderate (not too high or low). We also consider extensions analyzing how the optimal choice of evaluation fidelity is affected by the number of available prototypes, by operational flexibility (to dynamically change measurement technology), and by the ability to outsource evaluations to an experimentation platform. Managerial implications: We develop managerial insights for how the optimal choice of fidelity and the optimal length of the evaluation cycle should be planned depending on the evaluation costs and the firm’s ex-ante uncertainty. The resulting framework offers guidance to product and software development firms to successfully leverage imperfect fidelity experiments. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.1133 .

Pathways for the Construction of Labor Education Courses for Students Major in Measurement and Control

In March 2020, the Central Committee of the Communist Party of China and the State Council issued the Opinions on Comprehensively Strengthening Labor Education in Primary and Secondary Schools in the New Era, emphasizing that "fully understand the new requirements for strengthening labor education in the new era to train socialist builders and successors; Comprehensively build a labor education system that reflects the characteristics of The Times; Carry out labor education practice extensively; Efforts to improve labor education support and security ability; Effectively strengthen the organization and implementation of labor education." Therefore, college students' labor education has become a compulsory course for the major of measurement and control technology and instrument. The course is divided into two parts: theoretical study and practical study. In view of the increasing emphasis of the society on college students' labor quality education and the key role of mapping in solving complex engineering problems, the traditional "passing through" theoretical teaching methods and "visiting" practical teaching methods are no longer suitable for the new teaching needs in the contemporary background. Therefore, in order to improve the teaching quality and students' learning effect on this malleable and open knowledge, Changzhou Institute of Technology invited technical directors of representative enterprises in the industry to conduct classroom case analysis and field visits of relevant knowledge, so as to realize the teaching reform of production-education integration in school-enterprise joint teaching. The latest industry status and development trend of measurement and control technology and instrument technology will be brought into the classroom teaching, effectively improve the teaching quality, and deeply cultivate students' labor consciousness.