Waveform Patterns Research Articles

Mouth Leak is Associated with Sleep Fragmentation During Nasal CPAP Treatment of OSA and May Be Detected by Leak Waveform Analysis.

Mouth air leak is a major cause of low adherence to nasal CPAP in patients with obstructive sleep apnea (OSA). However, CPAP reports do not distinguish mouth from mask leak. We hypothesized that mouth air leak is terminated abruptly by an arousal from sleep and mouth closing that can be detected by CPAP leak waveform analysis. Describe patterns of mouth air leak waveform during polysomnography (PSG) in patients with OSA treated with well-fitted nasal CPAP. PSG recordings with a jaw motion sensor to detect mouth opening were performed in OSA patients treated with nasal CPAP with suspected mouth air leak. Careful mask fitting and visual inspection excluded mask leak. Mouth leak episodes were characterized by an increase (≥ 20%) above the intentional leak. Leak episodes were classified as intermittent (< 5 minutes) or continuous (≥ 5 minutes). Twenty patients (80% men; age: 63±11 years; body mass index: 29.9±6 kg/m2; baseline apnea hypopnea index: 46.9±19 events/h) treated with nasal CPAP and documented mouth leak completed the study. All but one patient experienced an overlap of intermittent and continuous mouth leak. Most mouth leak episodes ended with mouth closure (97.7%) and an arousal (52.7%) or awakening (38.6%). Only 34.9% of the leak episodes were associated with respiratory events. Intermittent mouth air leak was more common in sleep stages N1+ N2 (P<0.01), while continuous leak was more common in sleep stage N3 (P<0.01). Continuous episodes of air leak were associated with a higher amplitude of mouth opening. CPAP report waveform was able to detect only 29.6% of the leak episodes detected by PSG. Only 10 patients (50%) had a high unintentional leak according to the criterion adopted by ResMed and only 2 patients (10%) presented large leak according to the Philips criterion. Intermittent and continuous mouth leak during nasal CPAP frequently co-exist and contribute to sleep fragmentation. Identification of leak waveform patterns may help detect mouth air leak which in turn is an important cause of poor CPAP adherence.

Association of pulsatile venous waveform pattern in the venous studies of lower extremities to 2d-echocardiographic parameters for right heart function and right atrial pressure

Abstract Introduction To date, the detection of pulsatile venous waveform (PVW) pattern in venous duplex scans are read as suggestive of increased central venous pressure (CVP) and/or right-sided heart failure. In the advent of point of care ultrasound, non-invasive measures can be used to determine systemic hemodynamics in emergent clinical settings. Purpose This study aims to determine the association of PVW pattern to echocardiographic parameters of right ventricular (RV) function and right atrial pressure (RAP). Methods A single center retrospective study of adult patients with venous studies of the lower extremities and 2d-echocardiogram done from January 2019 to October 2023. Logistic regression analyses were performed to determine the association of PVW pattern with RV dysfunction based on TAPSE, S’ and FAC, as well as with increased RAP. Results A total of 2086 adult patients were included with median for age of 67 years of which 1141 (55%) were females, and 728 (35%) were hypertensive. PVW pattern was noted from 163 participants (7.8%) of which a higher proportion had heart failure, kidney disease, COVID-19, pneumonia and valvular heart disease. Patients with PVW pattern had a significantly lower median TAPSE [18 (IQR 15-20) vs 20 (IQR 18-22)] and median S’ [11.1 (IQR 8.6-13.20) vs 12.3 (IQR 10.6-14.40)] with FAC 27.1 + 11.9%. Increased RAP was noted in 7% of the study population. Patients with PVW pattern had a higher median inferior vena cava (IVC) diameter [1.9 ( IQR 1.5-2.3) vs 1.5 (IQR 1.3-1.8)] and lower median IVC collapsibility [39.9 (IQR 23.5-51.4) vs 50 (IQR 38.9-58.80]. PVW pattern is significantly associated with TAPSE (crude OR 3.89; CI 2.67-5.66, p&amp;lt;0.0001), S’ (crude OR 3.26, CI 2.30-4.62, p&amp;lt;0.0001) and increased RAP (adjusted OR 6.06, CI 4.02-9.14, p&amp;lt;0.0001). Conclusion Patients with PVW pattern had about 4 times and 3 times higher odds of developing RV systolic dysfunction based on TAPSE and S’, respectively. Its presence confers about 6 times higher odds of developing increased RAP. These parameters can direct further diagnostic work-up and guide assessment of response to decongestive therapy in critical units and other areas where 2d-echocardiogram is not readily accessible.

Research on Rapid Detection Method of Cavitation State of Water jet Propulsion Pump Based on Multi-source and Multi-feature of Acoustic Emission Signal and Bayesian Network

Abstract Cavitation prevents the conversion of internal dynamic and pressure energy in a water jet propulsion pump and causes erosion of flow passage components. Acoustic emission is a non-destructive test method for instability signals. Based on the incipient mechanism and development process of cavitation, three acoustic emission signal feature parameters (ring counting rate, energy release rate, Hurst index) are proposed to define the cavitation state utilizing the waveform pattern and signal self-similarity. The multi-source and multi-feature cavitation identification model of acoustic emission signals is established through cavitation simulation, multi-monitoring point acoustic emission signal testing, and feature parameter extraction, and a large number of probabilistic trainings are carried out using Bayesian network, resulting in a fast cavitation state identification method based on acoustic emission signals. The research results have important practical engineering application significance for the prediction of cavitation resistance, real-time dynamic monitoring of cavitation phenomenon and prevention of cavitation damage.

Design and Development of Lightning Detection System Utilizing Slow Atmospheric Electric Field Waveform at Legoland Malaysia

Conventional lightning localization and detection techniques, including Magnetic Direction Finder (MDF), Time of Arrival (TOA), Interferometer (ITF), and Distance of Arrival (DOA), predominantly rely on fast atmospheric electric fields, magnetic fields, and very high frequency (VHF) signals. This paper pioneers a novel approach by delving into the analysis of the slow atmospheric electric field, aiming to develop a waveform analysis utilizing this field to estimate the distance and radius of lightning occurrences at LEGOLAND Malaysia Resort. The newly implemented lightning detection system at LEGOLAND leverages a straightforward and cost-effective setup, incorporating a capacitive antenna, slow and fast atmospheric electric field sensors, and dedicated data analysis software. The system's efficacy and accuracy have undergone a rigorous comparison with LEGOLAND's existing online lightning detection service. Achieving accurate data necessitates proper grounding and isolation from electrical noise, as signal interference from power lines, towers, or machinery can potentially trigger false signals. This research has contributed detailed documentation on the analysis of slow atmospheric electric field data, encompassing waveform patterns and key characteristics. This documentation is expected to serve as a valuable resource for future research endeavors and the continuous refinement of lightning detection systems. The comparative evaluation between the novel system and the current online service at LEGOLAND Malaysia Resort has shed light on the efficiency and capabilities of the newly introduced methodology.

Cross-Country Ski Skating Style Sub-Technique Detection and Skiing Characteristic Analysis on Snow Using High-Precision GNSS.

A comprehensive analysis of cross-country skiing races is a pivotal step in establishing effective training objectives and tactical strategies. This study aimed to develop a method of classifying sub-techniques and analyzing skiing characteristics during cross-country skiing skating style timed races on snow using high-precision kinematic GNSS devices. The study involved attaching GNSS devices to the heads of two athletes during skating style timed races on cross-country ski courses. These devices provided precise positional data and recorded vertical and horizontal head movements and velocity over ground (VOG). Based on these data, sub-techniques were classified by defining waveform patterns for G2, G3, G4, and G6P (G6 with poling action). The validity of the classification was verified by comparing the GNSS data with video analysis, a process that yielded classification accuracies ranging from 95.0% to 98.8% for G2, G3, G4, and G6P. Notably, G4 emerged as the fastest technique, with sub-technique selection varying among skiers and being influenced by skiing velocity and course inclination. The study's findings have practical implications for athletes and coaches as they demonstrate that high-precision kinematic GNSS devices can accurately classify sub-techniques and detect skiing characteristics during skating style cross-country skiing races, thereby providing valuable insights for training and strategy development.

Validity and Reliability of OpenPose-Based Motion Analysis in Measuring Knee Valgus during Drop Vertical Jump Test.

OpenPose-based motion analysis (OpenPose-MA), utilizing deep learning methods, has emerged as a compelling technique for estimating human motion. It addresses the drawbacks associated with conventional three-dimensional motion analysis (3D-MA) and human visual detection-based motion analysis (Human-MA), including costly equipment, time-consuming analysis, and restricted experimental settings. This study aims to assess the precision of OpenPose-MA in comparison to Human-MA, using 3D-MA as the reference standard. The study involved a cohort of 21 young and healthy adults. OpenPose-MA employed the OpenPose algorithm, a deep learning-based open-source two-dimensional (2D) pose estimation method. Human-MA was conducted by a skilled physiotherapist. The knee valgus angle during a drop vertical jump task was computed by OpenPose-MA and Human-MA using the same frontal-plane video image, with 3D-MA serving as the reference standard. Various metrics were utilized to assess the reproducibility, accuracy and similarity of the knee valgus angle between the different methods, including the intraclass correlation coefficient (ICC) (1, 3), mean absolute error (MAE), coefficient of multiple correlation (CMC) for waveform pattern similarity, and Pearson's correlation coefficients (OpenPose-MA vs. 3D-MA, Human-MA vs. 3D-MA). Unpaired t-tests were conducted to compare MAEs and CMCs between OpenPose-MA and Human-MA. The ICCs (1,3) for OpenPose-MA, Human-MA, and 3D-MA demonstrated excellent reproducibility in the DVJ trial. No significant difference between OpenPose-MA and Human-MA was observed in terms of the MAEs (OpenPose: 2.4° [95%CI: 1.9-3.0°], Human: 3.2° [95%CI: 2.1-4.4°]) or CMCs (OpenPose: 0.83 [range: 0.99-0.53], Human: 0.87 [range: 0.24-0.98]) of knee valgus angles. The Pearson's correlation coefficients of OpenPose-MA and Human-MA relative to that of 3D-MA were 0.97 and 0.98, respectively. This study demonstrated that OpenPose-MA achieved satisfactory reproducibility, accuracy and exhibited waveform similarity comparable to 3D-MA, similar to Human-MA. Both OpenPose-MA and Human-MA showed a strong correlation with 3D-MA in terms of knee valgus angle excursion.

A Prospective Study of Hepatic Vein Waveform, Damping Index, and Splenoportal Index in Liver Cirrhosis: Correlation with Child-Pugh Score

Background:Chronic liver disease evaluation is commonly conducted using the Child-Pugh and Model for End-Stage Liver Disease (MELD) scoring systems. While the hepatic venous pressure gradient (HVPG) is the gold standard for measuring portal hypertension in cirrhotic patients, non-invasive alternatives such as Doppler ultrasonography offer a cost-effective, rapid, and less invasive option for assessment. Objective: This study aimed to investigate the correlation between hepatic vein waveform patterns, damping index, splenoportal index, and the Child-Pugh score in patients with liver cirrhosis to evaluate the efficacy of Doppler ultrasound as a non-invasive diagnostic tool. Methods: A prospective cross-sectional study was conducted at the Radiology Department of a public teaching hospital in Rawalpindi, Pakistan, from December 2023 to June 2024. A total of 52 patients with liver cirrhosis were included after excluding those with incomplete data or confounding conditions. Doppler ultrasound was used to assess hepatic vein waveform patterns, damping index, and splenoportal index. The Child-Pugh score was calculated based on clinical and laboratory parameters. Statistical analysis was performed using SPSS version 25, with a p-value of &lt;0.05 considered significant. The chi-square test, Fisher’s exact test, ANOVA, and ROC curve analyses were utilized for data evaluation. Results: The final cohort consisted of 52 patients, with 39 males (75%) and 13 females (25%). The mean age was 55.3 years. The damping index showed a significant increase from Child-Pugh Class A (0.45 ± 0.10) to Class C (0.75 ± 0.15) (p=0.003). The splenoportal index also demonstrated a significant rise from Class A (1.4 ± 0.3) to Class C (2.0 ± 0.5) (p=0.015). The sensitivity and specificity of the damping index (&gt; 0.6) in predicting higher Child-Pugh scores (B + C) were 52.6% and 85.7%, respectively, with a positive predictive value of 90.9%. Conclusion: The study found strong correlations between the severity of liver cirrhosis, as assessed by the Child-Pugh score, and Doppler ultrasound parameters such as hepatic vein waveforms and the damping index. Doppler ultrasound, therefore, presents itself as a precise, non-invasive alternative for evaluating the severity of liver disease, potentially replacing more invasive procedures.

Differences in Systemic Pulse Waveform Between Individuals With Glaucoma, Glaucoma Suspects, and Healthy Controls.

It has been hypothesized that compromised ocular circulation in glaucoma may be concomitant of systemic changes. The purpose of this study is to test whether systemic blood flow pulse waveform patterns differ between individuals with glaucoma (GL), glaucoma suspects (GLS), and normal healthy controls (HC). The study included 35 bilateral GL, 67 bilateral GLS, 29 individuals with unilateral GL who were considered GLS in the other eye, and 44 healthy controls. Systemic pulsatile blood pressure waveforms were recorded using a finger cuff. A continuous 200Hz plethysmography recording is made to obtain a pulse waveform. Waveform parameters were extracted using custom software from an average of eight pulse cycles. These were compared between GL, GLS, and HC groups on a per-eye basis, using generalized estimating equation models to account for intereye correlations; and plotted against disease severity by visual field linearized mean deviation (MDlin) and retinal nerve fiber layer thickness (RNFLT). Averaged blood pressure was significantly lower in the HC group (mean ± standard deviation 91.7 ±11.7 mm Hg) than the GLS (102.4 ± 13.9) or GL (102.8 ± 13.7) groups, with P < 0.0001 (generalized estimating equation regression). Waveform parameters representing vascular resistance were higher in both GLS and GL groups than the HC group; and were correlated with RNFLT and MDlin (P ≤ 0.05). The shape of the systemic pulsatile waveform differs in individuals with GL/GLS suspects, compared to HC eyes. Blood pressure changes more rapidly in individuals with GL, which suggests higher arterial stiffness.

40‐3: Waveform Analysis System for GAN‐Based Anomaly Detection of Coater Pressure in Photolithography

With the advancement of manufacturing equipment and the development of sensing technology, the measurement cycle of data is becoming very short, and the characteristics of data observed at the same time are also diversifying. A Fault Detection and Classification (FDC) system is in operation to collect and analyze measurement data in real time in the display manufacturing factory. However, the anomaly detection function provided by the FDC system is based on a threshold comparison method for data in seconds, so there is a limit to accuracy in processing measurement data in milliseconds. In particular, if the process for one panel is divided into several steps and each of them shows various characteristics, it is difficult to manage because it takes a lot of airlift to set search conditions and thresholds for anomaly detection. To overcome this, a waveform analysis system is implemented to assist the FDC system. This system extracts waveforms from milliseconds of measurement data during the processing time of one panel in the equipment, and diagnoses whether the equipment processing is normal through GAN‐based waveform pattern analysis. Generative models are used in the anomaly detection process in consideration of the manufacturing environment in which the normal data is overwhelmingly larger than the abnormal data. The DCGAN‐based model that is excellent in image processing and the TadGAN‐based model that combines Auto encoder and GAN were implemented and used. In this paper, the anomaly detection performance of models is compared and evaluated for the display photo process Coater Pressure sensor using the waveform analysis system implemented in this way.

Current and flux correlation analysis for detection, location, and phase identification of stator inter-turn short-circuit fault in doubly-fed induction generator

This study proposes an innovative method for identifying and locating inter-turn short-circuit faults in doubly-fed induction generators (DFIGs), commonly used in wind-energy production. Our approach uniquely integrates data from both current and magnetic-flux monitoring, offering a complete framework for fault diagnostics. We effectively distinguish between normal and abnormal conditions in the generators by observing the patterns in current and flux waveforms. Normal conditions are marked by uniform waveforms, whereas faults create noticeable imbalances. A key feature of our research is the development of a technique to accurately determine which phase of the generator is affected by the fault, facilitating quicker and more effective repairs. To pinpoint the exact location of the fault, we use a set of four magnetic-flux sensors strategically placed around the generator. These sensors detect variations in magnetic flux, enabling the precise location of the fault. By focusing on these three essential elements—fault detection, phase identification, and exact fault localisation—our proposed algorithm significantly improves the dependability of DFIGs in wind-power applications.

Exploring soliton solutions and interesting wave-form patterns of the (1 + 1)-dimensional longitudinal wave equation in a magnetic-electro-elastic circular rod

Exploring soliton solutions and interesting wave-form patterns of the (1 + 1)-dimensional longitudinal wave equation in a magnetic-electro-elastic circular rod

The emergence and clinical significance of artificial intelligence–enhanced electrocardiography

The integration of artificial intelligence (AI) with electrocardiography (ECG), a technology known as AI-ECG, represents a transformative leap in the field of cardiovascular medicine. This innovative approach has significantly advanced the capabilities of ECG, traditionally used for diagnosing heart diseases. AI-ECG excels in detecting subtle changes and interconnected patterns in cardiac waveforms, offering a level of precision and sensitivity that was previously unattainable with conventional methods. The scope of AI-ECG extends beyond the realm of heart diseases. It has shown remarkable potential in predicting and identifying the impacts of noncardiac conditions on heart health, thereby broadening the diagnostic capabilities of ECG. This is especially valuable given the complex nature of cardiovascular diseases and their interactions with other health conditions. Despite its groundbreaking potential, AI-ECG faces several challenges. One of the primary concerns is the "black box" nature of AI algorithms, which can make the decision-making process opaque and difficult to interpret. This poses a challenge in medical settings where understanding the rationale behind a diagnosis is crucial. Additionally, the effectiveness of AI-ECG is dependent on the quality and diversity of the datasets used to train the algorithms. Limited or biased datasets can lead to inaccuracies and diminish the reliability of the technology. However, the benefits of AI-ECG are significant. It enables faster, more accurate diagnoses and has the potential to greatly enhance the efficiency of cardiovascular care. As research and technology continue to evolve, AI-ECG is poised to become an indispensable tool in the diagnosis and management of heart diseases.

Noninvasive Bolus Transit Detection in Cervical Esophagus Utilizing Ultrasound Characteristics.

This pilot study aims to identify characteristic A-mode ultrasound features relevant to noninvasive detection of esophageal bolus transit in the proximal esophagus. Ultrasound signals at a lateral neck site were obtained via a single-element ultrasonic transducer with synchronous videofluoroscopic swallowing studies images of swallows of differing viscosities in 21 adult dysphagia outpatients. Characteristic ultrasound features were extracted to differentiate a bolus-filled from a collapsed esophagus. From 21 subjects, 412 swallows exhibited 4 reproducible waveform patterns associated with bolus transit as displayed in a heatmap: (1)Strong Reflectors; (2)Echo Shifts; (3)Distal Acoustic Enhancement; and (4)Speckling: One or more of these features were observed in the swallow series for all 21 subjects. Distinct acoustic waveform features acquired by single-element ultrasonic transducers can identify bolus transit through the cervical esophagus.

312 In vivo electrophysiology sex differences in the locus coeruleus of wild type F344 rats

OBJECTIVES/GOALS: Women are twice as susceptible to ailments like anxiety, PTSD, and Alzheimer’s disease compared to men. The locus coeruleus (LC), the primary source of noradrenaline for the brain is implicated in these disorders, however physiological sex differences have never been assessed in the LC. METHODS/STUDY POPULATION: To address this gap, In vivo electrophysiology under anesthesia was used to measure single unit activity of noradrenergic LC firing patterns in 4-month-old wild-type Fischer male and female rats. Recordings measured neuronal activity under basal conditions and in response to a footshock stimulation which elicits burst firing in LC neurons. Single unit activity is sorted via automatic valley seeking scan PCA, additional manual sorting is done via line and template method. Analysis is done extracting interspike interval (ISI) and firing rate of single units, additional analysis is done to quantify properties of bursting patterns (burst duration, spikes per burst, interburst interval, etc…). RESULTS/ANTICIPATED RESULTS: This data shows that during LC burst firing, females have longer interspike intervals compared to males, supporting the inhibitory effect of E2 on LC firing. Additionally, females have significantly different waveform patterns than males, indicating possible differences in intrinsic properties, but further supporting sexually distinct physiology of the LC . Because female rats have been estrous cycle tracked via vaginal lavage, stratification into estrus groups and further analysis may uncover differences within females. These data suggest that estrogen acts as a potent neuromodulator of noradrenergic LC neurons, providing valuable insights into the physiology of this brain region. DISCUSSION/SIGNIFICANCE: This study is the first exploration of LC physiological sex differences. This work offers insights into a critical brain region implicated in many diseases, and may pave the way for future therapeutic approaches, particularly for women, who are at a higher risk of neurological disease developing.

Diagnosis of Combustion Instability Using Waveform Pattern of Dynamic Pressure Signal

Diagnosis of Combustion Instability Using Waveform Pattern of Dynamic Pressure Signal

Waveform characteristics in thoracic paravertebral space: a prospective observational study

Background With increased use of thoracic paravertebral block (TPVB) in thoracic surgery, many faced the challenge of locating the thoracic paravertebral space (TPVS) ultrasonographically. This observational study aimed to investigate the waveform characteristics and pressure value within the TPVS in anaesthetized patients with controlled ventilation. Methods 50 patients scheduled for elective lung surgery were enrolled. After conduction of anesthesia, all patients underwent TPVB at T4/5 and T6/7 using transverse, in-plane ultrasound guidance. A pressure transducer system with a desktop monitor was connected to the needle hub to measure pressure values and waveform characteristics in three locations: the paraspinal muscles, immediately behind the superior costotransverse ligament, and within the TPVS. Next, 15 mL of 0.33% bupivacaine was injected into each desired TPVS. After completion of the surgery, the extent of dermatomal blockade and the pain score was assessed in all patients. Results 98 typical regular respiratory waveforms with a mean pressure of ≤ 25 mmHg were detected in the TPVS of 50 patients. The sensitivity of the combined ultrasound and pressure waveform measurement technique to identify the TPVS was 95.45% (95% confidence interval, 84.527–99.445). Nontypical respiratory waveforms were present in two patients. Factors interfering with the TPVS waveform characteristics were previous thoracic surgery and chronic pleural inflammation. Conclusion The TPVS had low pressure and showed a smooth, regular waveform pattern corresponding to respiration.

Flashover pattern analysis for 275 kV double circuit transmission lines during direct lightning strikes

Lightning overvoltage causes outages of transmission lines (TLs) in tropical countries. Identifying and analyzing the key factors responsible for tripping the lines can improve the performance of the lines. In this work, the flashover patterns due to direct lightning strikes on 275 kV double circuit TLs and towers in Malaysia was evaluated with Electromagnetic Transient Program (EMTP-RV). Three parameters that include lightning current magnitude, power frequency angle and tower footing resistance were analyzed on the line performance during direct lightning strikes. The simulated results found that two key parameters, lightning current at 270 kA and footing resistance at 50 Ω, reveal the highest impact on the insulator flashover. This finding was also verified from multivariate analysis results which is rarely found in the previous works in this field. As a key contribution in this work and in validation to the model, the simulated fault waveform patterns and voltage magnitudes were compared with the actual site data obtained from six different locations in Peninsular Malaysia. The analyzed results show a similar waveform pattern with an overall average voltage magnitude difference of 6.0 % before and after fault. The model is useful to electric utilities for analyzing transient performance of TLs.

Lie symmetries, modulation instability, conservation laws, and the dynamic waveform patterns of several invariant solutions to a (2+1)-dimensional Hirota bilinear equation

Lie symmetries, modulation instability, conservation laws, and the dynamic waveform patterns of several invariant solutions to a (2+1)-dimensional Hirota bilinear equation

Validity of AI-Based Gait Analysis for Simultaneous Measurement of Bilateral Lower Limb Kinematics Using a Single Video Camera.

Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measures for absolute error and waveform pattern similarity in gait analysis using pose estimation AI (OpenPose). Additionally, we investigated the feasibility of simultaneous measuring both lower limbs using a single camera from one side. We compared motion analysis data from pose estimation AI using video footage that was synchronized with a three-dimensional motion analysis device. The comparisons involved mean absolute error (MAE) and the coefficient of multiple correlation (CMC) to compare the waveform pattern similarity. The MAE ranged from 2.3 to 3.1° on the camera side and from 3.1 to 4.1° on the opposite side, with slightly higher accuracy on the camera side. Moreover, the CMC ranged from 0.936 to 0.994 on the camera side and from 0.890 to 0.988 on the opposite side, indicating a "very good to excellent" waveform similarity. Gait analysis using a single camera revealed that the precision on both sides was sufficiently robust for clinical evaluation, while measurement accuracy was slightly superior on the camera side.

Simulation Test of The Aerodynamic Environment of A Missile-Borne Pulsed Laser Forward Detection System at High Flight Speed

When a missile-borne pulsed laser forward detection system flies at supersonic speed, the laser beam will be distorted by the uneven outflow field, resulting in a significant reduction in ranging accuracy. In this paper, the impact of high flight speed on a pulsed laser detection system is studied. First, a new ray tracing method with adaptive step size adjustment is proposed, which greatly improves the computational efficiency. Second, the aerodynamic environment of a munition flying at high speed is simulated by an intermittent transonic and supersonic wind tunnel to obtain the schlieren data of the flow field at various Mach numbers. The schlieren data present a shock wave structure similar to that of the simulation. In addition, the variation patterns of the pulsed laser echo waveform of the model under different aerodynamic conditions are studied to evaluate the detectability and operational stability of the laser detection system under static conditions. The test results match the simulation results well, and the two offer relatively consistent shock wave structures, which verifies the correctness and effectiveness of the flow field simulation model. The test echo waveforms are in good agreement with the simulated echo waveforms; the relative errors between the peak values of test and simulated echo waveforms at various Mach numbers do not exceed 20%, and the correlation coefficients between the test and simulated echo waveforms all exceed 0.7, indicating high correlations between the two.