Real-time Displacement Measurement Research Articles

LAVOLUTION: Tunable structured light for bridge displacement measurement

Assessing bridge conditions is critical, but field measurements often face challenges like sensor installation and accuracy requirements. This paper introduces a novel approach using structured light (SL) for non-target-based measurements, eliminating the need for physical markers. A tunable SL system, featuring four laser pointers aligned with a commercial camera, was developed to estimate the relative angle between the camera and the target structure, and to accurately calculate the scale factor. The proposed method involves three main processes: (1) laser alignment, (2) angle estimation, and (3) real-time displacement measurement. By precisely aligning the SL system and minimizing discrepancies between projected SL points and an ideal numerical model, the method achieves accurate results. Validation through numerical simulations, lab-scale tests, and full-scale bridge tests demonstrated a maximum error of 2.69% in scale and 2.53% in displacement, confirming the method’s effectiveness and applicability.

Investigation on the bending performance of sandwich beams with re-entrant diamond auxetic core

ABSTRACT Auxetic metamaterials, characterised by a negative Poisson’s ratio (NPR), exhibit unique mechanical properties where they expand under tension and contract under compression. These structures hold significant potential with applications spanning various industries such as biomedical, construction, sports, aerospace and defence. The re-entrant diamond auxetic metamaterial represents a modified unit cell structure designed to mitigate the bending-dominated failure observed in conventional re-entrant structures. Notably, this modification demonstrates advantages, particularly in uni-axial compression scenarios. However, its performance concerning energy absorption under bending loads has not been explored until now. This study examines the bending behaviour of a re-entrant diamond auxetic metamaterial, both as a core and in sandwich configurations. The samples are fabricated using additive manufacturing (3D printing) and compression moulded glass-epoxy composite skins are added to these cores. Experimental assessments are conducted to evaluate bending performance, facilitated by advanced digital image correlation (DIC) techniques for real-time displacement measurement on the sample surface. The results reveal remarkable 14, 11 and 4-times improvement in energy absorption, specific energy absorption and failure displacement in the sandwich construction compared to the core configuration. Additionally, the study investigates the impact of eccentric loading on the flexural performance of the re-entrant diamond auxetic metamaterial.

Correction of Misalignment Errors in the Integrated GNSS and Accelerometer System for Structural Displacement Monitoring

Structural health monitoring (SHM) systems are widely deployed to monitor the dynamic behaviors of large civil infrastructures such as bridges and tall buildings. Global Navigation Satellite System- (GNSS-) based technologies are often a key component in such an SHM system considering the unique capability of GNSS in determining real-time displacements. GNSS often integrates with an accelerometer to achieve complementary advantages. However, due to the various error sources in GNSS measurements and accelerometer, accuracies of GNSS and accelerometer fusion results often cannot meet the requirements of SHM. We propose to integrate a multi-antenna GNSS and an accelerometer with an unscented multi-rate Kalman filter (UMRKF-MA) to correct the system misalignment errors between the sensors, aiming to produce a much more accurate real-time displacement measurement technology for monitoring large civil infrastructures. Extensive experiments with datasets gathered using a shaking table have indicated that the proposed method was able to improve the accuracy of real-time displacement measurements by up to about 40–65% compared to some existing approaches, and that a 1 mm level of real-time monitoring of displacements could be achieved with the method. The method has also been applied to process a dataset from a real-world long-span bridge when heavy vehicles passed through the bridge in a loading test and significantly improved results were obtained.

Sensing Mechanism and Real-Time Bridge Displacement Monitoring for a Laboratory Truss Bridge Using Hybrid Data Fusion

Remote and real-time displacement measurements are crucial for a successful bridge health monitoring program. Researchers have attempted to monitor the deformation of bridges using remote sensing techniques such as an accelerometer when a static reference frame is not available. However, errors accumulate throughout the double-integration process, significantly reducing the reliability and accuracy of the displacement measurements. To obtain accurate reference-free bridge displacement measurements, this paper aims to develop a real-time computing algorithm based on hybrid sensor data fusion and implement the algorithm via smart sensing technology. By combining the accelerometer and strain gauge measurements in real time, the proposed algorithm can overcome the limitations of the existing methods (such as integration errors, sensor drifts, and environmental disturbances) and provide real-time pseud-static and dynamic displacement measurements of bridges under loads. A wireless sensor, SmartRock, containing multiple sensing units (i.e., triaxial accelerometer and strain gauges) and a Micro Controlling Unit (MCU) were utilized for remote data acquisition and signal processing. A remote sensing system (with SmartRocks, an antenna, an industrial computer, a Wi-Fi hotspot, etc.) was deployed, and a laboratory truss bridge experiment was conducted to demonstrate the implementation of the algorithm. The results show that the proposed algorithm can estimate a bridge displacement with sufficient accuracy, and the remote system is capable of the real-time monitoring of bridge deformations compared to using only one type of sensor. This research represents a significant advancement in the field of bridge displacement monitoring, offering a reliable and reference-free approach for remote and real-time measurements.

Measurement of Fatigue Crack Growth in Compact Tension Specimen Using an Optical Extensometer

Abstract In this investigation, fatigue crack growth (FCG) tests are performed on transformation induced plasticity steels to characterize the relevance of stress intensity and crack growth rates with standard compact tension (CT) specimens. An optical extensometer that can achieve real-time displacement measurement is developed based on digital image correlation. Instead of a displacement gauge, the optical extensometer is adopted in FCG tests to measure CT specimen crack opening displacement (COD). Compared with stress intensity, it is difficult to calculate crack growth rates with COD. Therefore, the compliance equation and incremental polynomial method are programmed with C++ languages to obtain the steady crack growth curve directly. The proposed method is verified with experimental results obtained by the displacement extensometer. In addition, the precision of the displacement measurement is assessed, and the error induced by displacement output rates is discussed.

Thrust Control Method and Technology of Variable-Thrust Liquid Engine for Reusable Launch Rocket

A high-precision variable-thrust control method based on real-time measurement of pintle displacement and closed-loop feedback control is proposed to solve the technical problems of deep throttling variable-thrust regulation and control of pintle liquid rocket engines (LRE). By optimizing the system structure and control parameters, the closed-loop control of displacement with high precision and a fast response under a wide range of variable thrust can be realized, and thus the large-range, fast-response, and high-precision control of the chamber pressure, equivalent to thrust, can be indirectly realized. The chamber pressure response time is not more than 0.3 s, the overshoot is not more than ±3%, and the pulsation amplitude is not more than ±5%, which can meet the technical requirements of the large-range thrust adjustment and control of variable-thrust LRE of reusable launch rockets. The proposed variable-thrust LRE thrust control system is simple, reliable, and easy to use and maintain, which solves the problem of the large range, high precision, and fast response of thrust adjustment and control. The proposed system can provide important technical support for carrier rocket recycling and launch cost reduction. This is the first time a closed-loop control method of displacement of an integrated gas generator/flow regulator to achieve a 5:1 large-range continuous-variable-thrust control for the LRE of a reusable launch rocket has been proposed.

Development of a low-cost vision-based real-time displacement system using Raspberry Pi

Vision-based real-time displacement measurement systems can measure the structural displacements without contact and output the results immediately, overcoming some drawbacks of traditional contact-type sensors and off-line vision sensors in field applications. However, high cost and complexity of installation restrict the widespread application of the off-the-shelf vision-based real-time displacement systems. In this work, a fast image processing software is developed for operation in single board computers (SBC), firstly, based which a low-cost and portable vision-based real-time displacement measurement system using Raspberry Pi is constructed for civil structural health monitoring. To evaluate the performance of the system in field applications, a new method for validation of on-site measurement accuracy is proposed. The experimental results show that the constructed system accurately measured multipoint structural displacements of a long-span suspension bridge in real-time, with at least 1/17 pixel accuracy, providing a cost-efficient, convenient, high-precision, and contactless approach to obtain the displacement responses of infrastructures in the field.

Quadrature phase detection based on a laser self-mixing interferometer with a wedge for displacement measurement

We report a novel and simple method to generate a pair of self-mixing signals with quadrature phase difference in He-Ne laser by introducing a wedge into the external cavity. A wedge phase-shift laser self-mixing effect theory is developed to explain the phase-shift phenomenon, and the relationship between the phase difference and the distance from the center of the iris diaphragm to the center of the spot is given. Then a simple and effective wedge-quadrature laser self-mixing interferometer is established for displacement measurement by the quadrature phase detection method. Experimental results show that the max error is 182 nm for a target displacement of 20 μm. This structure provides a useful exploration for phase-shift signal generation and simplifies the self-mixing signal demodulation process with only a single four-quadrant inverse tangent operation, which has potential application in real-time displacement measurement.

Real-time plasma horizontal displacement estimator based on the neural network

Plasma displacement diagnostics is one of the basic diagnostics for evaluating the plasma operating state in tokamak devices. It is related to the plasma current centroid and generally obtained by integrating and calculating the induced voltage in the displacement coils. This induced voltage is derived from the magnetic field generated by the plasma. If the induced voltage is not solely due to the plasma magnetic field, there will be an unreal deviation in the plasma displacement. In J-TEXT, this phenomenon usually occurs when the Resonant Magnetic Perturbation (RMP) coils close to the displacement coils are energized. For long pulse tokamak devices, the source of the unreal deviation may be drifting integrators or radiation-induced voltages in the magnetic pickup coils, not only the RMP coils. To solve this problem, this paper proposes a real-time non-magnetic plasma horizontal displacement measurement method using a deep fully connected neural network. The soft-X ray (SXR) diagnostic data and the plasma displacement diagnostic data are used as the training data for the network. The training and testing results show that the network obtains a satisfactory fitting effect. On the other hand, to deploy this network for real-time diagnostics, this paper has designed and developed a plasma horizontal displacement estimator based on J-TEXT real-time framework (JRTF) in J-TEXT. The experimental results show that the real-time estimator is sufficient for real-time plasma displacement diagnostics. The feasibility of establishing real-time plasma displacement diagnostics based on the SXR diagnostic system has been verified.

LARGE SIZED PRODUCT SHELLS DISPLACEMENT MEASUREMENT UNDER STATIC LOADING USING LASER TRACKERS

In the aerospace industry the accuracy of product geometry and the aerodynamic contour provided traditionally, by the mould loft template method. The assembly accuracy control is carried out using optical measuring instruments, such as a level and a theodolit in combination with leveling rulers came to the aircraft industry from geodesy. Measurements are carried out according to reference points pre-embedded in the product at the design stage.
 The introduction of modern high precision coordinate measuring machines (CMM) into the production cycle is promising and actively developing direction to improve the quality of manufactured aircraft. To control the geometry of parts and assemblies, stationary portal-type CMMs and mobile CMMs of the "hand" type replace traditional rod tools and templates, and in the assembly and control operations of the product, traditional optical devices are replaced by a laser tracker. 
 The aim of this paper is the use of laser trackers for non-contact real-time large-sized product shell displacement measurement under static loading, which makes it possible to reduce the complexity and duration of tests, and ensure high measurement accuracy.

Real-time panoramic-deformation measurement of cabin structure of launch vehicle based on camera network

<p indent="0mm">To satisfy the requirement of real-time panoramic-deformation measurement of a cabin structure in a large-diameter launch vehicle, a camera-network deformation-measurement system composed of 24 cameras and real-time three-dimensional (3D) deformation-measurement software based on CPU parallel computing was developed. The 360° full-circle deformation measurement of the inner surface of a cylindrical coordinate system and real-time measurement of the local deformation of a local Cartesian coordinate system were successfully realized. The camera-network measurement system consisted of 12 sets of binocular systems. The field of view of a single set of binocular systems was 3.6 m×3.6 m, and a certain overlap area was set between two adjacent binocular systems to ensure continuity of measurements. Photogrammetry and binocular stereo vision were used to reconstruct the 3D coordinates of the coded points, and coordinate transformation between the local and global coordinate systems was realized using the coded points. Finally, coordinate unification of the 12 sets of binocular systems was performed. A single set of binocular systems could be connected to a computer. By implementing the seed-point-based parallel algorithm and initial guess-estimation-algorithm-based deformation-transfer scheme, real-time 3D displacement and surface-strain measurements at 70000 points per second were successfully realized. On the basis of the 360° full-circle deformation-measurement results in the cylindrical coordinate system, high-precision calculation of the diffusion angle was successfully realized. The standard deviation of the static noise in the three directions was less than 0.01 mm, and the standard deviation of the static noise in the strain was less than 50 microstrains.

Deep learning based virtual point tracking for real-time target-less dynamic displacement measurement in railway applications

In the application of computer-vision-based displacement measurement, an optical target is usually required to prove the reference. If the optical target cannot be attached to the measuring objective, edge detection and template matching are the most common approaches in target-less photogrammetry. However, their performance significantly relies on parameter settings. This becomes problematic in dynamic scenes where complicated background texture exists and varies over time. We propose virtual point tracking for real-time target-less dynamic displacement measurement, incorporating deep learning techniques and domain knowledge to tackle this issue. Our approach consists of three steps: 1) automatic calibration for detection of region of interest; 2) virtual point detection for each video frame using deep convolutional neural network; 3) domain-knowledge based rule engine for point tracking in adjacent frames. The proposed approach can be executed on an edge computer in a real-time manner (i.e. over 30 frames per second). We demonstrate our approach for a railway application, where the lateral displacement of the wheel on the rail is measured during operation. The numerical experiments have been performed to evaluate our approach’s performance and latency in a harsh railway environment with dynamic complex backgrounds. We make our code and data available at https://github.com/quickhdsdc/Point-Tracking-for-Displacement-Measurement-in-Railway-Applications.

Quadrature phase detection based on phase shift of self-mixing interferometer for real-time displacement measurement

A real-time displacement reconstruction technique based on a phase retardation method is proposed. By introducing a waveplate and a polarization beam splitter into the external cavity, two self-mixing signals with a phase shift of π∕2 can be obtained. Then the displacement of the external object can be reconstructed by a quadrature demodulation algorithm, which significantly simplifies the data processing and meets the requirements of real-time displacement reconstruction techniques. The results show that the absolute errors of the reconstructed displacements are less than 75 nm.

Computer vision-based displacement measurement with m-sequence target

The development of image sensors enables the application of vision-based techniques to the non-contact displacement measurement of large-scale structures. The features of the physical targets are critical to the accuracy, stability and anti-interference of the displacement measurement results. In this study, a novel m-sequence target and the associated circular correlation processing technique are developed for real-time displacement measurement. The properties of the m-sequence as a pseudo-random sequence are introduced. The vision-based displacement calculation method is then derived from the correlation property of the m-sequence. The algorithms and measurement systems are integrated in the LabVIEW environment. To verify the anti-interference performance of the developed system, static and dynamic experimental tests are carried out with various forms of interference, such as partial occlusion, uneven illumination, out of focus and smoke effect. Experimental results indicate that the developed system cannot only accurately measure structural displacement, but also has outstanding antiinterference performance, even if 30% of the target is masked.

A new displacement demodulation algorithm for the phase-modulated self-mixing interferometer based on FPGA

Abstract This paper introduces a design of the phase demodulation system based on FPGA for the phase-modulated self-mixing interferometer. By the processing that the modulation SIN signal and the doubling frequency modulation COS signal are respectively multiplied by the phase-modulated self-mixing signal(PSMI) and then low-pass filtered and shaped in the electrical domain, two orthogonal square wave signals sensitive to the object’s movement direction are obtained for displacement reconstruction. The FPGA signal processing system controls the generation of a highly stable and accurate sinusoidal signal source for the modulation of the electro-optic crystal(EOM). At the same time, the two orthogonal square wave signals obtained after the demodulation processing are subdivided for the high-precision measurement of a uniformly moving object’s displacement. The high-frequency amplifier circuit amplifying the self-mixing interference signal, multiplier & frequency doubler circuits based on MLT04 and low-pass filter circuits are designed. FPGA-based counting programs, DAC circuits and programs used for generating sine waves are also designed. In the experiment, comparison tests for displacement measurement are performed using the PI company’s two-dimensional precision electronically-controlled translation stage, and high-precision displacement measurement can be achieved. The demodulation system does not rely on a PC and a high-precision acquisition card, and can realize real-time measurement of displacement, greatly improving the practicability of the system.

PSO-SVM-based deep displacement prediction of Majiagou landslide considering the deformation hysteresis effect

The accuracy of landslide displacement prediction can effectively prevent casualties and economic losses. To achieve accurate prediction of the Majiagou landslide displacement in the Three Gorges Reservoir (TGR), China, a hybrid machine learning prediction model considering the deformation hysteresis effect is proposed. The real-time deep displacement measurements were captured by using in-place inclinometers with Fiber Bragg grating (FBG) sensors. The time series method was adopted to divide the total displacement into a trend term and periodic term. Trend displacement was determined by the geological condition and predicted by the fitting method. Periodic displacement was controlled by external factors such as rainfall and fluctuation of reservoir water level. Before making the prediction, the grey correlation analysis was adopted to confirm that the fluctuation of the reservoir water level was the main influence factor. In view of the deficiency that current prediction methods could not quantitatively determine the lag time of landslide deformation and thus select the influencing factors empirically, the dynamic analysis of the correlation between periodic influence factors and periodic displacement was carried out in this paper, and the deformation lag time was identified to be 18 days by using set pair analysis (SPA) method. Finally, the optimal influence factors were selected and the prediction model of Majiagou landslide based on support vector machine optimized by particle swarm optimization (SPA-PSO-SVM) was established. Results showed that the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of the proposed SPA-PSO-SVM prediction model are 0.28 and 12.8, respectively. Compared with the PSO-SVM model, the prediction accuracy of the proposed model had been improved significantly. The reliability and effectiveness of the SPA-PSO-SVM prediction model is verified and it has apparent advantages while predicting landslide displacement with deformation hysteresis effect involved.

Experimental investigation of out-of-plane buckling of circular arches under a central radial point load

Abstract An arch under a central in-plane point load may lose its stability in an out-of-plane buckling mode when the load attends a certain value. This paper presents a theoretical study for the out-of-plane buckling of elastic circular arches under a central radial point load using an energy method and an experimental study for the out of-plane buckling load of elastic circular aluminium arches under a central radial point load. Six circular aluminium arches of doubly symmetric I-sections having different rise-to-span ratios, different load heights and different boundary conditions are tested by applying a radial point load to the crown of the arch. With specially designed supports that can simulate different in-plane boundary conditions, an ingenious loading device and high-precision real-time displacement measurement, the elastic out-of-plane buckling loads of tested arches are accurately recorded. Comparisons show that agreements of test results against theoretical solutions are very good. The influences of the slenderness ratio, in-plane boundary conditions and the load height on the out-of-plane buckling are also investigated and it is found that they influence the out-of-plane buckling load of circular arches significantly.

A novel digital phase detection method for frequency-modulated continuous-wave interferometric fiber-optic displacement sensor

A novel digital phase detection method is proposed for the high accuracy and large dynamic range interrogation of frequency-modulated continuous-wave (FMCW) interferometric fiber-optic displacement sensors. Firstly, a peak of beat signal is found coarsely, and the range of the peak is obtained. Then golden section is used to find the peak accurately, in which cross-correlation filtering is used to calculate the value of golden section points. The simulation in the MATLAB environment show that the phase discrimination error is 0.073 rad, and displacement error is 9 nm, when the signal-to-noise ratio is 20 dB. In the real-time interrogation of a FMCW fiber-optic displacement sensor, we realized a repeatability error of 3.5 nm, a standard error of 4.5 nm and a linearity of 0.9999. The experimental results show that the method can achieve real-time displacement measurement with high accuracy and large dynamic range.

Real-Time and Long-Distance Measurement of Displacement Based on Optoelectronic Oscillator

A frequency-encoded real-time and long-distance displacement measurement method based on two cross-referencing optoelectronic oscillators (OEOs) is proposed and experimentally demonstrated. In the system, one OEO is used for reference, and the other is used for measurement. The initial distance is evaluated by the oscillation frequency and free spectral range of the OEO for reference. The small displacement is calculated by using the frequency of the intermediate frequency (IF) signal generated by mixing the two OEOs. The two OEOs with the same characters are placed in the same environment. This protects the displacement measurement from the influence of the variation of ambient temperature. A high measurement sensitivity, which improves the precision of the displacement measurement, is also implemented due to the accumulative magnification effect at high-order resonant frequency modes. In addition, the low frequency of the IF signal, which is far smaller than the oscillation frequency of the two OEOs, allows a cost-effective and real-time measurement by a frequency counter. The proposed displacement measurement method is demonstrated experimentally. When the sampling time is 1 ms, displacement measurement errors less than ±3.71 and $\pm 11.14~\mu \text{m}$ are realized at emulated distances of around 800m and 6 km, respectively. The real-time velocity and acceleration measurements are also implemented owing to the introduction of a time signal in the measurement process.

Real-time measurement of microcantilever displacement based on Linnik microscopic speckle interferometer

Nowadays, the application of MEMS is more and more important. With the development of microstructure technology, higher requirements are also placed on measurement methods. However, the current measurement methods cannot meet these requirements due to their own limitations. We developed a method based on the temporal microscopic speckle interferometry, which has advantages of real-time, full field, high-precision, and nondestructive. The interferometer based on Linnik microscopic structure is built up. The corresponding displacement measuring experiments have been performed, and the measurement errors are <0.05 μm. The experimental results demonstrate the validity of our homemade device.