Non-contact Measurement Technology Research Articles

Advances in the application of non-contact temperature measurement technology for aero-engine blade.

The advancement of the aviation sector has made the temperature measurement technology for aero-engine turbine blades essential for maintaining the engine's safe and steady performance. The non-contact temperature measurement technology is a trending research focus in turbine blade temperature measurement due to its benefits of not requiring direct touch with the object being measured and its suitability for high-temperature and high-speed conditions. This paper provides a concise overview of various key non-contact temperature measurement methods for aero-engines, such as fluorescence temperature measurement, fiber-optic temperature measurement, and radiation temperature measurement. It discusses the temperature measurement principle, technical characteristics, and the current research status both domestically and internationally. Based on this, this Review further discusses the main challenges faced by the non-contact temperature measurement technology and the development trend of the future.

Parameter identification based on iterative signal space in blade tip timing

Blade tip timing (BTT), as an effective non-contact measurement technology, is widely used for health monitoring of rotating blades. Due to the installed number of probes is limited by the engine structure, the requirement of BTT sampling frequency is difficult to meet the Nyquist sampling theorem, which leads the BTT signal is severely under-sampled. Therefore, it is difficult to extract vibration parameters, such as frequency, amplitude. Many algorithms was proposed to solve the undersampling problem. In this paper, a new BTT signal processing algorithm is proposed based iterative signal space, which expands individual data into subspace level data geometrically. Compared to some previous methods, the iterative signal space algorithm can identify the blade vibration parameters more accurately, which is verified in both numerical simulation and experiment. Furthermore, different degrees of noise is used to show the feasibility and robustness. The results are very significant for online blade fault diagnosis and health monitoring of turbines.

Enhancing measurement precision through noise analysis and fringe optimization in white light interferometry

White light interferometry is a highly precise non-contact measurement technology. However, in practical applications, certain noise sources such as thermal noise, shot noise, and redundant intensity noise, can introduce signal distortion. In this paper, we propose a mathematical formulation for the key metric, Quality Factor, which serves as an evaluation criterion for the quality of interference signals. The influence of different factors on the measurement is quantitatively analyzed using the signal-to-noise ratio, and various filtering methods are employed to address different types of noise. Finally, experimental results highlight the primary factors and optimization techniques that significantly impact the quality of interference signals, thereby verifing the effectiveness of the method on measurement results.

A target spatial location method for fuze detonation point based on deep learning and sensor fusion

The spatial location of fuze detonation point is crucial for evaluating the working condition and improving the performance of fuze. Considering the observation safety, the non-contact long-distance accurate measurement technology is essential. In this paper, we propose a method that takes the sensor data of optics, spatial attitude and GPS as input and outputs the spatial position of the fuze detonation point. The proposed method consists of two steps. First, an object detection algorithm with post-processing algorithm is proposed to obtain rich information of the target. The algorithm achieves high-accuracy detection by introducing powerful backbone, attention mechanism, group convolution, and improved multi-scale feature fusion. Second, a Variational Auto-Encoder (VAE) algorithm model improved by dense connection structure and multiple source heterogeneous sensor information fusion structure is proposed as the position regression algorithm. It receives the status information of the observer camera and the output of the object detection algorithm, and then outputs the three-dimensional coordinates of the explosion point. Finally, method validation and performance analysis are realized through virtual scene simulation. Experiment results show the superiority of the proposed object detection algorithm over other typical algorithms on explosion flare detection, with its Average Precision (AP) of 0.889. The positioning error of the spatial location method is 0.896 m, while that of the binocular stereo vision method is 2.863 m. Therefore, the proposed target spatial location method is proved to be effective and accurate.

Non-contact voltage measurement of residential cables based on internal parameter conversion and centering probe assistance

Existing non-contact voltage measurement technology cannot be applied to residential cables containing neutral wire and earth wire in addition to live wire. A non-contact voltage measurement method of residential cables is introduced in this article. First, an equivalent circuit model of the residential cable measurement based on capacitive coupling is established. In order to solve the problem of uncertain coupling capacitance, which leading to the inability to accurately obtain the voltage amplitude, a calibration method based on internal parameter conversion and centering probe assistance is proposed. This method calibrates the cable voltage through different transfer relationships and sensor outputs, and no known reference excitation is required during calibration. Subsequently, the impact of internal parameters on measurement accuracy are analyzed and selection principles are provided. Through finite element simulation, the influence of metal spring for centering on voltage measurement is analyzed, and the measurement error of non-ideal cables (with eccentricity or ovality) is quantified. A prototype probe and internal parameter conversion circuit have been developed, and parasitic capacitance compensation have been completed. The measurement accuracy of 50 Hz voltage in a certain range (100–300 V) was tested in the laboratory, the maximum relative error of amplitude is −0.89%, and the relative error of phase is 0.68%. Four specifications of residential cables testing were completed, with a maximum relative error of −1.35%. Long- term testing was conducted on the actual field (output voltage of the distribution box), the test results showed that the output was linear, and the relative error were kept around 0.65% after primary calibration.

Bridge-bearing disengagement identification based on flexibility matrix diagonal matrix change rate: an indoor physical simulation experiment

The disengagement of bridge bearings is a pervasive issue encountered in the realm of bridges, which can potentially lead to changes in operational circumstances, diminished longevity, and compromised traffic safety. The current methods employed for detecting such disconnections primarily rely on force sensors, cameras, and acceleration sensors. However, their practical implementation on-site and effectiveness in accurately identifying disengagement require enhancement. To address the challenges associated with the installation and layout of conventional contact sensors, as well as the potential introduction of additional mass, a sophisticated “bridge-bearing disconnection detection system” has been devised. This innovative system is based on laser Doppler vibrometer technology, which eliminates the need for physical contact. The feasibility of employing non-contact laser Doppler vibration measurement technology in the detection of bridge-bearing disconnection has been successfully verified within the framework of this study. Furthermore, a comprehensive analysis of the sensitivity of key dynamic parameters, specifically natural frequencies and vibration modes, to bridge-bearing disengagement has been conducted. The verification process included evaluating the identification effectiveness of regularized combined absolute changes in vibration modes and flexibility matrix diagonal matrix change rate (FDMCR) under diverse working conditions simulating complete disconnection. This assessment involved using both finite element analysis and empirical measurements. The findings unequivocally demonstrate that the disconnection of bridge bearings results in a reduction in the natural frequencies for each mode order, with an observed cumulative effect. In addition, it is noteworthy that the vibration mode indices typically exhibit greater sensitivity toward the disconnection of outer bearings. By contrast, FDMCR demonstrates commendable positioning capabilities and exceptional noise resistance in identifying bridge-bearing disengagement. The empirical insights gleaned from these research findings hold significant value in terms of on-site identification of bridge-bearing disengagement, ultimately contributing to the preservation of bridges’ long-term operational integrity.

A Review of Non-Contact Water Level Measurement Based on Computer Vision and Radar Technology

As pioneering non-contact water level measurement technologies, both computer vision and radar have effectively addressed challenges posed by traditional water level sensors in terms of maintenance cost, real-time responsiveness, and operational complexity. Moreover, they ensure high-precision measurements in appropriate conditions. These techniques can be seamlessly integrated into unmanned aerial vehicle (UAV) systems, significantly enhancing the spatiotemporal granularity of water level data. However, computer-vision-based water level measurement methods face the core problems of accurately identifying water level lines and elevation calculations, which can lead to measurement errors due to lighting variations and camera position offsets. Although deep learning has received much attention in improving the generation, the effectiveness of the models is limited by the diversity of the datasets. For the radar water level sensor, the hardware structure and signal processing algorithms have to be further improved. In the future, by constructing more comprehensive datasets, developing fast calibration algorithms, and implementing multi-sensor data fusion, it is expected that the robustness, accuracy, and computational efficiency of water level monitoring will be significantly improved, laying a solid foundation for further innovations and developments of hydrological monitoring.

회전 중 블레이드 진동 비접촉 측정기술 기반 저압터빈 블레이드 진동특성 분석

회전 중 블레이드 진동 비접촉 측정기술 기반 저압터빈 블레이드 진동특성 분석

Characterization of crack on the outer edge of the disk based on blade tip timing technology

The structural performance failure of the rotating blade disk with disk crack is one of the major causes of aero-engine failures and even serious accidents. The blade tip timing (BTT) is a non-contact measurement technology that obtains the rotor operation status by detecting the blade. This paper has proposed a crack characterization method for the disk’s outer edge based on the BTT technique. In this process, the influence of crack state parameters (length and position) on the circumferential displacement signal of the blade tip is determined by using the crack tip displacement, the relative position of the blade tip motion during the rotation of the outer edge crack-containing disk and the actual blade tip measuring points, and the critical value of the crack state parameters affecting the blade tip offset is analyzed. The finite element simulation results verify the effectiveness and accuracy of the proposed method. The study of this article can provide a theoretical basis for the measurement of cracks on the disk’s outer edge by the BTT technique, which is of great significance for the accurate identification of the operating condition of the rotating blade disk structure.

Design and development of a multifunctional moxibustion treatment machine based on heat-sensitive moxibustion therapy

A multifunctional moxibustion treatment machine is designed and developed to assist the heat-sensitive moxibustion therapy. Through the motion control of the stepping motor by programmable logic controller (PLC), the automatic control is obtained for the acupoint detection of heat-sensitive moxibustion therapy and the manual operation of moxibustion. The skin temperature is monitored in real-time, using infrared non-contact temperature measurement technology. Based on the deviation of the temperature set value and the monitoring one, the distance between the moxibustion device and the exerted region is adjusted automatically by PLC so that the temperature is controlled practically. The multifunctional moxibustion treatment machine based on the heat-sensitive moxibustion therapy is capable of the operation control of mild moxibustion, circling moxibustion, sparrow-pecking moxibustion and along-meridian moxibustion techniques, as well as real-time monitoring of skin temperature. The temperature change curve of this machine is coincident with that obtained by the manual operation of heat-sensitive moxibustion. This multifunctional moxibustion treatment machine assists the delivery of heat-sensitive moxibustion therapy and it is satisfactory in temperature control and precise in operation.

Parameter Identification of Ice Drift toward Cross-River Bridges in Cold Regions

Ice load is one of the main loads that needs to be considered in the design and construction of wading bridges (bridges whose piers are submerged in water) in cold regions, and ice velocity, area, and thickness are the main parameters that affect ice load. A noncontact measurement technology based on the “ scale method” was proposed to realize small-range monitoring of river ice by laying calibration grids on the ice surface. The “bounding rectangle method” and Harris corner detection were used to accurately identify the area and velocity of a single ice drift. Also, the thickness of ice drift was estimated by statistical analysis. Considering the Huma River basin in the Daxing’an Mountains as the research object, field tests were performed to determine the flow ice parameters. The results indicate that noncontact measurement technology can accurately identify the velocity and area of ice drift and has wide application prospects, thereby providing a reference for the structural design and safety evaluation of wading bridges in cold areas.

Characterization of the Nozzle Ablation Rate Based on 3D Laser Scanning System

The nozzle of solid rocket motor (SRM) is easily ablated by high temperature, high pressure, high speed, and corrosive particles, which affects the stability of rocket flight. Therefore, the measurement and characterization of the nozzle ablation rate are helpful in providing some guidance for the design of nozzle material and structure. However, due to the high surface roughness of the composite nozzle after ablation, it is difficult to obtain an accurate ablation rate by contact measurement methods. The 3D laser scanning system is a 3D non-contact measurement technology using structured light technology, phase measurement technology, and computer vision technology. It has the advantages of non-contact, large scanning size, flexibility, and portability. In this paper, a 3D reconstruction of the ablation nozzle is carried out based on the 3D laser scanning system. Additionally, the ablation rate of the nozzle is measured without cutting the actual specimen. Furthermore, the pressure, temperature, and surface convective heat transfer coefficient trends are numerically calculated and compared with the ablation rate. Additionally, the empirical formula between ablation rate and pressure, temperature, convective heat transfer coefficient is obtained empirically by the inversion analysis method. The empirical formula can provide theoretical guidance for nozzle size design and optimization. The results show that the non-contact 3D laser scanning system is a valuable method for reconstructing the model of the ablated nozzle, and the empirical formula of ablation rate can accurately predict the ablation rate of the nozzle.

Non-Contact Measurement and Identification Method of Large Flexible Space Structures in Low Characteristic Scenes.

The end-operation accuracy of the satellite-borne robotic arm is closely related to the satellite attitude control accuracy, and the influence of the vibration of the satellite's flexural structure on the satellite attitude control is not negligible. Therefore, a stable and reliable vibration frequency identification method of the satellite flexural structure is needed. Different from the traditional non-contact measurement and identification methods of large flexible space structures based on marker points or edge corner points, the condition of non-marker points relying on texture features can identify more feature points, but there are problems such as low recognition and poor matching of features. Given this, the concept of 'the comprehensive matching parameter' of scenes is proposed to describe the scene characteristics of non-contact optical measurement from the two dimensions of recognition and matching. The basic connotation and evaluation index of the concept are also given in the paper. Guided by this theory, the recognition accuracy and matching uniqueness of features can be improved by means of equivalent spatial transformation and novel relative position relationship descriptor. The above problems in non-contact measurement technology can be solved only through algorithm improvement without adding hardware devices. On this basis, the Eigensystem Realization Algorithm (ERA) method is used to obtain the modal parameters of the large flexible space structure. Finally, the effectiveness and superiority of the proposed method are verified by mathematical simulation and ground testing.

Non-Contact Crack Visual Measurement System Combining Improved U-Net Algorithm and Canny Edge Detection Method with Laser Rangefinder and Camera

Cracks are the main damages of concrete structures. Since cracks may occur in areas that are difficult to reach, non-contact measurement technology is required to accurately measure the width of cracks. This study presents an innovative computer vision system combining a camera and laser rangefinder to measure crack width from any angle and at a long distance. To solve the problem of pixel distortion caused by non-vertical photographing, geometric transformation formulas that can calculate the unit pixel length of the image captured at any angle are proposed. The complexity of crack edge calculation and the imbalance of data in the image are other problems that affect measurement accuracy, and a combination of the improved U-net convolutional networks algorithm and Canny edge detection method is adopted to accurately extract the cracks. The measurement results on the different concrete wall indicate that the proposed system can measure the crack in a non-vertical position, and the proposed algorithm can extract the crack from different background images. Although the proposed system cannot achieve fully automated measurement, the results also confirm the ability to obtain the crack width accurately and conveniently.

Performance and Measurement Devices for Membrane Buildings in Civil Engineering: A Review

Lightweight and flexible membranes offer different façades for buildings (suitability, competitive costs, durability, and other benefits) compared to traditional building materials. Increasing attention is being paid to membrane structures in the civil and industrial sectors. Acquiring response data or environmental characteristics directly from a model or building is the most straightforward approach to analyzing the properties of membrane structures, which also contributes to the development of theoretical studies and simulation methods along with the enactment of specifications. This paper provides a comprehensive overview of membrane structure performance, including mechanical, thermal, and energetic aspects, alongside the deployment and deflation of inflatable types. Furthermore, the devices used to monitor the structural response are summarized. The constitution of the structure is the most critical factor affecting its performance. A proper design would offer enhanced mechanical properties and thermal environments with a reduction in energy consumption. Non-contact measurement technology has the advantage of causing no structural disturbance and is low cost, but it lacks practical application in membrane buildings. The achievements and limitations of previous studies are also discussed. Finally, some potential directions for future work are suggested.

Quantitative Inversion Model Design of Mine Water Characteristic Ions Based on Hyperspectral Technology

In view of the problems of low measurement accuracy and repeated calibration during the use of coal mine water quality analysis, the hyperspectral reflection noncontact measurement technology was proposed to solve the existing problems. KCl, NaCl, pH, NaHCO3, and CaCl2were used to indicate the characteristic ion information of Na+, K+, Ca2+, Cl−, HCO3−, and pH mine water in the laboratory, and 2220 spectral data were obtained by spectral determination. Savitzky–Golay convolution smoothing was used to smooth and denoise the original spectral data of each ion, and the relationship between the spectrum and the concentration of each reagent was obvious after smoothing and denoising pretreatment. The principal component regression method was used to build the inversion model of each ion content, and through the modeling study, the prediction set of KCl was found: the coefficient R∧2 reaches 0.907, RPD is up to 2.7; the prediction set of NaCl was found: the coefficient R∧2 reaches 0.957, RPD is up to 3.1; the PH prediction set was found: the coefficient R∧2 reaches 0.785, RPD is up to 2.1; the prediction set of NaHCO3 was found: the coefficient R∧2 reaches 0.137, RPD is up to 1.2; the prediction set of CaCl2 was found: the coefficient R∧2 reaches 0.622, and RPD is up to 1.7. The results show that the hyperspectral method can play a better role in the extraction of K+, Cl−, Na+, Ca2+, and pH. It is difficult to extract HCO3− ions.

A spectrum reconstruction method for blade vibration measurement based on probe waveform analysis

Blade tip timing (BTT) is regarded as a promising noncontact measurement technology for rotating blade health monitoring. However, the number and layout of probes, required by BTT, hinder the application of BTT. To overcome these shortcomings, a probe waveform spectral reconstruction method (PWSR) is proposed, which combines the advantages of waveform analysis method and wideband signal interpolation method. PWSR can be summarized in two steps: obtaining more displacement information from the output waveform of probes and identifying vibration parameters of blades. Simulations are conducted to investigate the effectiveness of PWSR for single-harmonic and multi-harmonic blade vibration parameters identification. Its sensitivity and robustness are also studied. An experiment to validate the proposed method is performed on a rotating blade test bench, and compared with strain gauge test data. Experimental results show that the proposed method can identify the amplitude, frequency and phase of the blade vibration accurately via one probe.

Self-feature-based point cloud registration method with a novel convolutional Siamese point net for optical measurement of blade profile

Currently, non-contact optical measurement technologies have shown prominent power in measuring blade profiles. One of the critical issues is how to align measured point clouds in different viewpoints into an entire profile. However, extracting efficient features for registration is difficult due to the thin-walled and twisted spatial freeform surfaces of blades. Besides, various densities and small overlaps between two adjacent point cloud data also increase the difficulty of registration. To overcome these issues, in this paper, laying on the foundation of a developed multi-axis motion system, we present a novel and general framework titled convolutional Siamese point net (CSPN) for partial-to-partial point cloud registration. Our network mainly consists of three parts: feature extraction, matching matrix computation and singular value decomposition (SVD). To make a balance between low-level and high-level semantics, we design a pyramidal architecture to learn the multiscale features of each point. In matching matrix computation, both feature space and coordinate space are utilized. Also, a novel attention mechanism is proposed to deal with the conflicts between matching matrices obtained by feature space and coordinate space. Experimental results demonstrate the feasibility and good practical application prospect of this method.

Mechanical properties of PVC geomembrane based on non-contact measurement

The mechanical properties of polyvinyl chloride (PVC) geomembrane (GM), particularly its elastic modulus, are of the utmost importance in engineering design and evaluation of performance. The existing test methods make it difficult to provide an accurate elastic modulus of PVC GM. This research presents the establishment of an improved method for analysing the true stress–strain by non-contact measurement technology to determine the elastic modulus. Digital image correlation (DIC) was used to measure the axial and transverse strain, and it was found to give measurements of strain with a high degree of accuracy. The variation of Poisson's ratio is discussed and the true cross-sectional area is determined, allowing the true stress to be calculated theoretically. In accordance with the true stress–strain curve, the elastic modulus and linear range are established, which can provide designers with the tools to evaluate the true performance of GM and help them to select anti-seepage materials in design.

Research and Demonstration of Intelligent Multi-Physical Quantity Integration Sensor for Transmission Lines

The digital grid requires sensors to be widely deployed, safe, and reliable. At present, the single functional sensors suffered from redundant sensing system, repeated construction and low utilization rate. Therefore, this paper researched the multi-physical quantity integration sensor for a quad-bundle spacer on 500kV transmission lines. The sensor was composed of self-supplying rings and the monitoring host. Based on the non-contact current measurement technology, energy supply technology, intelligent sensing technology, low power consumption technology, reliability design technology, and other advanced technologies, this paper designed the hardware, software, and protective structure of the sensor, which can monitor the current and temperature of bubbles, channel side image and infrared image on transmission lines, ambient temperature, humidity, and air pressure. Finally, the multi-physical quantity integration sensors have been used on transmission lines in China Southern Power Grid, and the functions were verified. The sensors promote the automation, information, and digitization of monitoring transmission lines.