Development and engineering application of integratedsafety monitoring systems for China’s high-speed trains

With the improvement of the running speed of China’s high-speed trains,the demands for running status monitoring and security assurance of High-speed Electric Multiple Units(EMU)have increased significantly.However,the current safety monitoring systems are independent,which is not conducive to the comprehensive monitoring and information sharing of the whole vehicle.The temperature monitoring of running gear is insensitive to early failures.How to develop a train operation safety monitoring system with strong engineering implementation and high integration is a key problem to be solved.For the monitoring of running stationarity,frame stability and running gear health of China’s high-speed trains,an integrated safety monitoring system framework is designed,and the logic and algorithm for the diagnosis of stationarity,stability and health states of rotating parts are constructed.Monitoring software which fused the temperature,high and low frequency vibration data is developed,and the design and installation of the vibration temperature composite sensors are completed.The research results have realized the integration and comprehensive processing of multiple monitoring systems,completed the improvement from single component and vehicle-level safety monitoring to multi-system,train-level and interactive monitoring.In the process of real vehicle application,the developed monitoring system acquires the vehicle operation status data accurately and in real time.The constructed diagnosis algorithm and logic evaluates the vehicle operation status accurately and in a timely manner,and avoids the progression from fault to accident.The research results show that the integrated safety monitoring system can provide technical support for train operation safety.

Probing multi-physical process and deformation mechanism of a largescale landslide using integrated dual-source monitoring

The implementation of isolated heterologous monitoring systems for spatially distant borehole deployments often comes with substantial equipment costs,which can limit the effectiveness of geohazard mitigation and georisk management efforts.To address this,we have developed a novel monitoring system that integrates fiber Bragg grating(FBG)and microelectromechanical system(MEMS)techniques to capture soil moisture,temperature,sliding resistance,strain,surface tilt,and deep-seated inclination.This system enables real-time,simultaneous data acquisition and cross-validation analyses,offering a costeffective solution for monitoring critical parameters in geohazard-prone areas.We successfully applied this integrated monitoring system to the Xinpu landslide,an active super-large landslide located in the Three Gorges Reservoir Area(TGRA)of China.The resulting strain profile confirmed the presence of two shallow secondary sliding surfaces at depths of approximately 7 m and 12 m,respectively,in addition to the deep-seated sliding surface at a depth of28 m.The lower secondary sliding surface was activated by extreme precipitation,while the upper one was primarily driven by significant changes in reservoir water levels and secondarily triggered by concentrated rainfalls.Anti-slide piles have remarkably reinforced the upper moving masses but failed to control the lower ones.The gap between the pile heads and the soil amplified the rainwater erosion effect,creating a preferential channel for rainwater infiltration.Multi-physical measurements revealed a mixture of seepage-driven and buoyancy-driven behaviors within the landslide.This study offers an integrated dual-source multi-physical monitoring paradigm that enables collaborative management of multiple crucial boreholes on a large-scale landslide,and contributes to the evaluation and improvement of engineering measures in similar geological settings.

Disaster reduction stick equipment: A method for monitoring and early warning of pipeline-landslide hazards

Oil and gas pipelines are of great importance in China,and pipeline security problems pose a serious threat to society and the environment.Pipeline safety has therefore become an integral part of the entire national economy.Landslides are the most harmful type of pipeline accident,and have directed increasing public attention to safety issues.Although some useful results have been obtained in the investigation and prevention of pipeline-landslide hazards,there remains a need for effective monitoring and early warning methods,especially when the complexity of pipeline-landslides is considered.Because oil and gas pipeline-landslides typically occur in the superficial soil layers,monitoring instruments must be easy to install and must cause minimal disturbance to the surrounding soil and pipeline.To address the particular characteristics of pipelinelandslides,we developed a multi-parameter integrated monitoring system called disaster reduction stick equipment.In this paper,we detail this monitoring and early warning system for pipeline-landslide hazards based on an on-site monitoring network and early warning algorithms.The functionality of our system was verified by its successful application to the Chongqing Loujiazhuang pipeline-landslide in China.The results presented here provide guidelines for the monitoring,early warning,and prevention of pipeline geological hazards.

GPS Vector Tracking Receivers with Rate Detector for Integrity Monitoring

In this paper,the integrity monitoring algorithm based on a Kalman filter(KF)based rate detector is employed in the vector tracking loop(VTL)of the Global Positioning System(GPS)receiver.In the VTL approach,the extended Kalman filter(EKF)simultaneously tracks the received signals and estimates the receiver’s position,velocity,etc.In contrast to the scalar tracking loop(STL)that uses the independent parallel tracking loop approach,the VTL technique uses the correlation of each satellite signal and user dynamics and thus reduces the risk of loss lock of signals.Although the VTL scheme provides several important advantages,the failure of tracking in one channel may affect the entire system and lead to loss of lock on all satellites.The integrity monitoring algorithm can be adopted for robustness enhancement.In general,the standard integrity monitoring algorithm can timely detect the step type erroneous signals.However,in the presence of ramp type slowly growing erroneous signals,detection of such type of error takes much more time since the error cannot be detected until the cumulative exceeds the specified threshold.The integrity monitoring based on the rate detector possesses good potential for resolving such problem.The test statistic based on the pseudorange residual in association with the EKF is applied for determination of whether the test statistic exceeds the allowable threshold values.The fault detection and exclusion(FDE)mechanism can then be employed to exclude the hazardous erroneous signals for the abnormal satellites to assure normal operation of GPS receivers.Feasibility of the integrity monitoring algorithm based on the EKF based rate detector will be demonstrated.Performance assessment and evaluation will be presented.

Concealed Integrity Monitoring for Wireless Sensor Networks

Nowadays, sensor networks are widely installed around the world. Typical sensors provide data for healthcare, energy management, environmental monitoring, etc. In the future sensors will become a part of critical infrastructures. In such a scenario the network operator has to monitor the integrity of the network devices, otherwise the trustworthiness of the whole system is questionable. The problem is that every integrity protocol needs a secure channel between the devices. Therefore, we will introduce a covert channel for hidden transportation of integrity monitoring messages. The covert channel enables us to hide integrity check messages embedded into regular traffic without giving potential attackers a hint on the used integrity protocol.

Development of an integrated structural health monitoring system for bridge structures in operational conditions

This paper presents an overview of development of an integrated structural health monitoring system.The integrated system includes vibration and guided-wave based structural health monitoring.It integrates the real-time heterogeneous sensor data acquiring system,data analysis and interpretation,physical-based numerical simulation of complex structural system under operational conditions and structural evaluation.The study is mainly focused on developing:integrated sensor technology,integrated structural damage identification with operational loads monitoring,and integrated structural evaluation with results from system identification.Numerical simulation and its implementation in laboratory show that the system is effective and reliable to detect local damage and global conditions of bridge structures.

Real-time integrity monitoring for a wide area precise positioning system

The wide area precise positioning system(WAPPS)is a high-precision positioning system based on a global navigation satellite system.Using a GEO satellite or a communication network,it provides users,in its service area,with real-time satellite orbit,clock,and other corrections.Users can achieve centimeter-level static positioning or decimeter-level kinematic positioning by precise point positioning.With the demands for applications of both high-precision and safety of life in real time,WAPPS is facing urgent needs to improve its service integrity.This study presents a real-time integrity monitoring approach for WAPPS.Using dual-frequency ionosphere-free corrections of GPS and BDS,along with monitor station data,related error models are established and the integrity monitoring is achieved,based on the analysis of satellite corrected residuals.In addition,satellite faults are simulated for performance verification.The results show that the algorithm can monitor both step and drift faults effectively and alert users in time.

Integrity monitoring scheme for single-epoch GNSS PPP-RTK positioning

Integrity monitoring for precise point positioning is critical for safety-related applications.With the increasing demands of high-accuracy autonomous navigation for unmanned ground and aerial vehicles,the integrity monitoring method of high-precision positioning has become an essential requirement.While high precision Global Navigation Satellite Systems(GNSS)positioning is widely used in such applications,there are still many difculties in the integrity monitoring method for the multi-frequency multi-GNSS undiferenced and uncombined Precise Point Positioning(PPP).The main difculties are caused by using the measurements of multiple epochs in PPP.Based on the baseline Multiple Hypothesis Solution Separation(MHSS)Advanced Receiver Autonomous Integrity Monitoring(ARAIM)algorithm,this paper discusses the feasibility of the pseudorange-based baseline ARAIM method on the single-epoch PPP based on Real-Time Kinematic(RTK)networks(PPP-RTK)framework to overcome these difculties.In addition,a new scheme is proposed to transfer the conventional PPP process into the single-epoch PPP-RTK framework.The simulation results using the proposed model are analyzed in this study.The Protection Levels(PLs)estimated by PPP Wide-lane Ambiguity Resolution(PPP-WAR)model with regional corrections can reach the meter level and the PLs estimated by PPP Ambiguity Resolution(PPP-AR)and PPP-RTK models are usually the sub-meter level.Given a horizontal Alert Limit(AL)of 1.5 m,the global coverage of availability above 99.9%for PPP-WAR,PPP-AR,and PPP-RTK can reach 92.6%,99.4%,and 99.7%respectively.The results using real kinematic data also show that tight PLs can be achieved when the observation conditions are good.

Multi‑level autonomous integrity monitoring method for multi‑source PNT resilient fusion navigation

For the integrity monitoring of a multi-source PNT(Positioning,Navigation,and Timing)resilient fusion navigation system,a theoretical framework of multi-level autonomous integrity monitoring is proposed.According to the mode of multi-source fusion navigation,the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level.For isolated non-redundant navigation sources,the system level recovery verification model is used.For the isolated multi-redundant navigation sources,the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors,and the isolated fault sensors are verified in real-time.Finally,according to the fault detection and verification results at each level,the observed information in the fusion navigation solution is dynamically adjusted.On this basis,the integrity risk dynamic monitoring tree is established to calculate the Protection Level(PL)and evaluate the integrity of the multi-source integrated navigation system.The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),Long Baseline Location(LBL),and Ultra Short Baseline Location(USBL).The test results show that the proposed method can effectively isolate the fault source within 5 s,and can quickly detect multiple faulty sensors,ensuring that the positioning accuracy of the fusion navigation system is within 5 m,effectively improving the resilience and reliability of the multi-source fusion navigation system.

Receiver Autonomous Integrity Monitoring Availability and Fault Detection Capability Comparison Between BeiDou and GPS

This paper used the statistical methods of quality control to assess receiver autonomous integrity monitoring(RAIM) availability and fault detection(FD) capability of BeiDou14(Phase II with 14 satellites),BeiDou(Phase III with 35 satellites) and GPS(with 31 satellites) for the first time. The three constellations are simulated and their RAIM performances are quantified by the global, Asia-Pacific region and temporal variations respectively. RAIM availability must be determined before RAIM detection. It is proposed that RAIM availability performances from satellites and constellation geometry configuration are evaluated by the number of visible satellites(NVS, NVS > 5) and geometric dilution of precision(GDOP, GDOP < 6) together. The minimal detectable bias(MDB) and minimal detectable effect(MDE) are considered as a measure of the minimum FD capability of RAIM in the measurement level and navigation position level respectively. The analyses of simulation results testify that the average global RAIM performances for BeiDou are better than that for GPS except global RAIM holes proportion. Moreover, the Asia-Pacific RAIM performances for BeiDou are much better than that for GPS in all indexes. RAIM availability from constellation geometry configuration and RAIM minimum FD capability for BeiDou14 are better than that for GPS in Asia-Pacific region in all cases, but the BeiDou14 RAIM availability from satellites are worse than GPS's. The methods and conclusions can be used for RAIM prediction and real-time assessment of all kinds of Global Navigation Satellite Systems(GNSS) constellation.

New methods for dual constellation single receiver positioning and integrity monitoring

Navigation system integrity monitoring is crucial for mission(e.g.safety)critical applications.Receiver autonomous integrity monitoring(RAIM)based on consistency checking of redundant measurements is widely used for many applications.However,there are many challenges to the use of RAIM associated with multiple constellations and applications with very stringent requirements.This paper discusses two positioning techniques and corresponding integrity monitoring methods.The first is the use of single frequency pseudorange-based dual constellations.It employs a new cross constellation single difference scheme to benefit from the similarities while addressing the differences between the constellations.The second technique uses dual frequency carrier phase measurements from GLONASS and the global positioning system for precise point positioning.The results show significant improvements both in positioning accuracy and integrity monitoring as a result of the use of two constellations.The dual constellation positioning and integrity monitoring algorithms have the potential to be extended to multiple constellations.

Vulnerabilities and integrity of precise point positioning for intelligent transport systems:overview and analysis

The implementation of Intelligent Transport System (ITS) technology is expected to significantly improve road safety and traffic efficiency. One of the key components of ITS is precise vehicle positioning. Positioning with decimetre to sub-metre accuracy is a fundamental capability for self-driving, and other automated applications. Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) is an attractive positioning approach for ITS due to its relatively low-cost and flexibility. However, GNSS PPP is vulnerable to several effects, especially those caused by the challenging urban environments, where the ITS technology is most likely needed. To meet the high integrity requirements of ITS applications, it is necessary to carefully analyse potential faults and failures of PPP and to study relevant integrity monitoring methods. In this paper an overview of vulnerabilities of GNSS PPP is presented to identify the faults that need to be monitored when developing PPP integrity monitoring methods. These vulnerabilities are categorised into different groups according to their impact and error sources to assist integrity fault analysis, which is demonstrated with Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) methods. The main vulnerabilities are discussed in detail, along with their causes, characteristics, impact on users, and related mitigation methods. In addition, research on integrity monitoring methods used for accounting for the threats and faults in PPP for ITS applications is briefly reviewed. Both system-level (network-end) and user-level (user-end) integrity monitoring approaches for PPP are briefly discussed, focusing on their development and the challenges in urban scenarios. Some open issues, on which further efforts should focus, are also identified.

Correlation-weighted least squares residual algorithm for RAIM

The Least Squares Residual(LSR)algorithm,one of the classical Receiver Autonomous Integrity Monitoring(RAIM)algorithms for Global Navigation Satellite System(GNSS),presents a high Missed Detection Risk(MDR)for a large-slope faulty satellite and a high False Alarm Risk(FAR)for a small-slope faulty satellite.From the theoretical analysis of the high MDR and FAR cause,the optimal slope is determined,and thereby the optimal test statistic for fault detection is conceived,which can minimize the FAR with the MDR not exceeding its allowable value.To construct a test statistic approximate to the optimal one,the CorrelationWeighted LSR(CW-LSR)algorithm is proposed.The CW-LSR test statistic remains the sum of pseudorange residual squares,but the square for the most potentially faulty satellite,judged by correlation analysis between the pseudorange residual and observation error,is weighted with an optimal-slope-based factor.It does not obey the same distribution but has the same noncentral parameter with the optimal test statistic.The superior performance of the CW-LSR algorithm is verified via simulation,both reducing the FAR for a small-slope faulty satellite with the MDR not exceeding its allowable value and reducing the MDR for a large-slope faulty satellite at the expense of FAR addition.

An enhanced least squares residual RAIM algorithm based on optimal decentralized factor

The Least Squares Residual(LSR)algorithm is commonly used in the Receiver Autonomous Integrity Monitoring(RAIM).However,LSR algorithm presents high Missed Detection Risk(MDR)caused by a large-slope faulty satellite and high False Alert Risk(FAR)caused by a small-slope faulty satellite.In this paper,the LSR algorithm is improved to reduce the MDR for a large-slope faulty satellite and the FAR for a small-slope faulty satellite.Based on the analysis of the vertical critical slope,the optimal decentralized factor is defined and the optimal test statistic is conceived,which can minimize the FAR with the premise that the MDR does not exceed its allowable value of all three directions.To construct a new test statistic approximating to the optimal test statistic,the Optimal Decentralized Factor weighted LSR(ODF-LSR)algorithm is proposed.The new test statistic maintains the sum of pseudo-range residual squares,but the specific pseudo-range residual is weighted with a parameter related to the optimal decentralized factor.The new test statistic has the same decentralized parameter with the optimal test statistic when single faulty satellite exists,and the difference between the expectation of the new test statistic and the optimal test statistic is the minimum when no faulty satellite exists.The performance of the ODFLSR algorithm is demonstrated by simulation experiments.

A GNSS Anti-Spoofing Technique Based on the Spatial Distribution Characteristic of the Residual Vectors

Anti-spoofing is becoming a crucial technique for applications with high navigation accuracy and reliability requirements.Anti-spoofing technique based on Receiver Autonomous Integrity Monitoring(RAIM)is a good choice for most Global Navigation Satellite System(GNSS)receivers because it does not require any change to the hardware of the receiver.However,the conventional RAIM method can only detect and mitigate a single spoofing signal.Some improved RAIM methods can deal with more spoofing signals,but the computational complexity increases dramatically when the number of satellites in view increase or need additional information.This paper proposes a new RAIM method,called the SRV-RAIM method,which has a very low computation complexity regardless of the number of satellites in view and can deal with any number of spoofing signals.The key to the new method is the spatial distribution characteristic of the Satellites'Residual Vectors(SRV).In replay or generative spoofing scenarios,the pseudorange measurements of spoofing signals are consistent,the residual vectors of real satellites and those of spoofing satellites have good separation characteristics in spatial distribution.Based on this characteristic,the SRV-RAIM method is proposed,and the simulation results show that the method can separate the real signals and the spoofing signals with an average probability of 86.55%in the case of 12 visible satellites,regardless of the number of spoofing signals.Compared to the conventional traversal-RAIM method,the performance is only reduced by 3.59%,but the computational cost is reduced by 98.3%,so most of the GNSS receivers can run the SRV-RAIM algorithm in time.