IVM INNOVATIVE VIBRATION MONITORING DIAGNOSTIC SYSTEMS FOR RAILWAY AND TRAIN MAINTENANCE Wh e e l / R a il I n te ra c tio n 1 W E IGHT D IS TRIBU TIO N WHE E L C OND ITION RAIL S MO NITO RING PO W E RVE Portable s cale for trai n s WAY S ID E W h eels ets defect ev alu ati on O N BO ARD W h eel/rai l defects ev alu ati on
WHAT WE SOLVE We analyze Vibrations using Accelerometers and identify Defects There is a lot of knowledge to extract. DEFECTS DEGRADATION SCALABILITY LOCALIZATION PREDICTABILITY From effects to causes Trend analysis, comparison Any train can be a Sensor Accuracy, act on small sections Golden data for Trains and Rails 2
THE PROBLEMS WE ARE SOLVING DATA COLLECTION GET DATA YOU CAN TRUST DATA TRANSFER EFFICIENCY AND SECURITY DATA COMPARISON IN SPACE AND TIME Advanced synchronous network of accelerometers Move the data from on board to the processing Cloud Compare the data from different Trains and several Transits 3
POWER FOCUS ON THE WHY? 4 POWERVE POrtable WEigher for Railway VEhicles
PORTABLE WEIGHER FOR RAILWAY VEHICLES Why weighing? TOTAL WEIGHT WHEEL WEIGHT Mostly for FREIGHT Maintenance Safety Extending Life Testing Packing Suspensions Compliance Improving Running Dynamics Homologation Reducing Wheel Slip (Locomotives) 5
Who is interested? Producers Locomotives Passengers EMU/DMU and HS On Track Machines (OTM) Freight Maintenance Workshops Authorities for railway SAFETY Homologation bodies Testing and Commissioning bodies 6
Where should we measure? CRANES + LOAD CELLS Simple! WHEEL RAIL CONTACT PATCH @ Reference Point 7 DO NOT LIFT! The suspensions will extend and the distribution of weights may change DO NOT APPLY EXTERNAL FORCES TO STOP THE ROLLING STOCK ON MEASURING AREA WHEEL FLANGE SYSTEMS FIXED SYSTEMS POWERVE
POWERVE It is PORTABLE and overcomes all these issues! SIMPLE POSITIONING AUTOMATICALLY ALIGNS UNDER THE WHEELS 8
POW2X Bogie Kit Position Ramps (n. 4) Acquisition Boards - ABC (n. 4) Load cells (n. 2/ABC) Positioning Ramp Spacer (n.1) Tablet (n.1) Router (n.1) 9
THE POSITIONING RAMPS LAY ON THE RAILS AND ENSURE A STABLE EQUILIBRIUM CONDITION WITHOUT EXTERNAL FORCES THE TRAIN RAISES EASILY THE SLOPE IS LESS THAN 5% 10
POWERVE MEASURMENT QUALITY 11 1. Correct point of measurement 2. Does not depend on the installation 3. High repeatability of measured values 4. No external forces 5. Easy and quick installation 6. Handling of the train below 1 meter 7. Statistical checks of the measures (automatic) 8. User friendly and guided user interface (Tablet App) 9. Multiple electronic and printable formats 10.Management and archive in Cloud
12 POW2X Kit
13 POW3X Kit
14 POW4X Kit
15 POW6X Kit
POWER FOCUS ON THE WHY? 16 Monitoring Systems
Monitoring Systems FOCUS ON THE ON BOARD & WAYSIDE SYSTEMS Increasingly development of high performance signalling systems More intensive use of existing railway routes Reduction of time degradation values of th e various components subject to wear European Directive 91/440/EEC (separationbetween Network Manager and Operation Manager Need for innovative monitoring systems Increased sustainable mobility needs 17 Maintaining safety standards and control of servicing
Causes for railway degradation Wheel-rail interaction Problem: Evaluation the quality of the wheels and tracks 18 High impact on regular exercise and high cost of maintenance
Wheel/Rail Interaction Diagnostics Railway Diagnostics Methodologicalapproach to the Wheel/Rail interaction evaluation Geometrical parameters monitoring Effect Monitoring 19 Wayside On Board Geometric Measurements Wayside (SWAN-T) On Board (IQM-WTI) Vibration Measurements
SWAN-T (Smart Wayside Accelerometric Network Track) Wayside equipment Primary components of the system: 24 triaxial accelerometers based on MEMS technology; 2 Inductive proximity sensors for the detection of axles in the measurement zone; acquisition board, synchronization and data processing MEMS Accelerometers 20 Proximity Sensors Self-powered with photovoltaic system
SWAN-T Working scheme 12 in 1 Virtual sensor measurement Result (covering the whole wheel circle tyre) Variables Running surface in wheel/rail contact Data acquisition Validation Vertical acceleration's analisys Normalization QWI Syntehetic Output L0 L1 L2 21 Remote output (WEB)
Data elaboration Calibration q How to evaluate the significance of a defect? q Simulation of some defects on non-degraded wheels of a test train Sf -A-2 Sf -B-2 q Evaluation of the outputs collected during the passages of this test train at a controlled speed q Check the repeatability and the intensity of the responses as a function of defects and speed q Calibration curves plotted on the speed that indicate the limits of the three levels: L0, L1, L2 1.8 1.6 1.4 1.2 S 1 M R 0.8 0.6 0.4 0.2 0 Andamento RMS con la velocità y = 0.0519x - 0.1986 R² = 0.9704 0 10 20 30 40 Velocità (km/h) Tutti ico P 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 Andamento Picco con la velocità y = 0.0976x + 0.6717 R² = 0.6826 0 10 20 30 40 Velocità (km/h) Tutti 22
Data elaboration Output q Synthetic representation: graph where the QWI value is associated with a color scale for each axle of the detected train. The levels of color: red, yellow and green. q Extended representation, performance in a diagram where the sectors involved from defects are also highlighted. 23
Detected and recognized trains Repeatable results-train with no faulty wheel Visual repeatability check q Synthetic Output (QWI levels) Case 1: Train with no faulty wheel Wheels on Level 2 (mean): 0 Passages: 8 24
Detected and recognized trains Repeatable results-train with faulty wheels Visual repeatabilitycheck q Synthetic Output (QWI levels) Case 2: Train with faulty wheels Wheels on Level 2 (mean): 15 Passages: 8 High repeatability of synthetic output 25
Recognized trains Wheels classification q Parameter used for the calculation of the QWI to the reference speed (25 km / h) q Mean on the n passages validated q Classification of the 896 wheels as a function of the parameter q Threshold values that indicate 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 Valore medio Quality parametro Wheel Index Indice (QWI) di Qualità mean della value Ruota IQR 26 the assignment of the level to the data set examined Wheel N ruota Numbers
SWAN-T Conclusions q The wheel-rail interaction generate vibrations on the rolling surface as a function of geometrical defects qthe analysis of the accelerograms detail, in combination with the wheel data transit provided by the proximity sensors, is effective for the assessment of the effects induced by the wheel-rail interaction. qthe SWAN-T system is able to detect trains with wheels in a state of decay qthe synthetic representation of the output is a valuable diagnostic tool qthe identification through the photographic images allows to assess both the repeatability of the results of the system is any of variability phenomena in a time period qin a time interval of three months they have identified both train with consistent results over time, both train with significant 27 changes. qthe system may provide useful guidance in support of maintenance operations.
IQM-WTI (INNOVATIVE QUALITY MONITOR OF WHEELSETS/TRACK INTERACTION) On-Board equipment Prototype and Validation 28 01 HARD W ARE 02 KNOWL E D GE 03 FRO NTE ND In field test validation of the acquisition system Understood there is more than just defects Localization, Continuous Feature Extraction. Map presentation GOVERNAMENT FINANCING ACCE LE RATIO N PROGRAM ~2 million in 3 years We are here!
IQM-WTI Diagnostic system Instrumentation characteristics Characteristics: 2 instrumented bogies. 4 accelerometric sensors for each bogie, installed on the axle-box. 3 directions of measurement (X, Y, Z) where X stands for the direction of travel, Y and Z, respectively, stand for transverse and vertical direction to the upper surface of the rail. GPS information related to speed, coordinates and altitude. Continuous recordings when train is switched on. Data storage in blocks of specified 29 time. RFI diagnostic train Y1 operational on all HS lines On average 1-2 passages per week Recorded data: September 2015- September 2016 About 75.000 km run by Y1 and recorded by the system.
IQM-WTI Diagnostic system Acquired data Y1 plant output: Acceleration (g) in the 3 directions. (On the right, some examples of 2 generic outputs of 1 accelerometer in the three directions XYZ) GPS Info (geographic coordinates, running speed). Acquisition: Dedicated system 1 simultaneous acquisition module for 4 sensors of a bogie Sampling frequency 640 Hz Possible relation to GPS signal. Accelerometers features: MEMS technology Digital output Triaxle 30 Full scale: 6 g Resolution:1 mg Minimum encumbrance
IQM-WTI Diagnostic system Repeatability Passage 1 9 December Two extracts of the same route of track (5 km) are compared here. The route has been run in days at close range (9 22 December 2016), more or less at the same running conditions. Here are shown two sensors on different axles. It is noted that: The «time lag» between the different accelerometers is always present and compatible with the running speed information. The acceleration profiles show a similar distribution of the amplitude levels. 31 The weldings identification is unique. Passage 2 22 December
IQM-WTI Diagnostic system Source irregularities Extraction of the signal between two spikes related to track irregularities. UF3 acceleration is extracted. Evidence of signal patterns in the accelerations which are repeated periodically, not related to track irregularities (to the wheel running circles). IQM-W/TI SWAN-T By zooming on the signal, we highlight phenomena with minor intensity amplitudes but cyclically recurring with a timestep of 0.075 seconds that, at 135 km/h 32 speed, corresponds to 2.8 meters, that is exactly the linear length of the wheel. It can occur that the amplitudes and the patterns are characteristic of each sensor, therefore it is assumed that these effects are related to the rolling of the wheel on the rail and, hence, related to the defectiveness of the wheel itself.
IQM-WTI Diagnostic system Running dynamics Hunting oscillations Straight-line route at constant speed Effects related to running dynamics: Straight-line route at constant speed. Analysis of the transverse accelerations to the upper surface of the rail. In transverse direction, there is evidence of short-duration oscillations at low frequency. These phenomena can be related to Hunting oscillations. Through an appropriate analysis, it is possible to trace the contribution in terms of movement, highlighting the intervals characterized by greater amplitudes. Transverse acceleration Original data Low frequency acceleration input Movement with evidence of damped oscillations inputs Hunting oscillations 33
IQM-WTI Diagnostic system Correspondence with geometric data IQM/WTI Geometry Comparison with geometric parameters obtained by a diagnostic system through direct detection (optical / inertial). By correlating the positioning information, GPS, you can align the data and express the acceleration in function to the run mileage (Pk). Consider (in purple) an extract of the geometric parameter of vertical alignment (ZRD1); the points which cross the red line, indicate that a quality threshold has been exceeded, that is, the presence of a defect. The corresponding graph of the accelerations in Z direction (appropriately processed), similarly, shows increments in the vicinity of the samezones. 34 The accelerations measured on-board the train show increments in correspondence of the irregularities found in the geometric parameters used for the track quality diagnostics by direct detection systems.
IQM-WTI Diagnostic system Conclusions The verification of the measuring system of the accelerations on the axle-box, installed on the RFI diagnostic train Y1, has allowed to highlight a high degree of consistency of the outputs both in terms of accelerations and of GPS. In the period of operation from September 2015 to September 2016, it is estimated that Y1 has run approximately 75.000 km, appropriately stored by the system. From the preliminary analysis carried out on the acquired data, it was found that the type of selected sensitive elements and the chosen recording mode appear to be able to provide usable results in all running conditions. The audits carried out has allowed to verify, in particular: ü The repeatability of the outputs, when the train runs the same route several times in the same identical running condition (and at the same track wear conditions and rolling stock wear conditions). ü The high level of synchrony, guaranteed on all sensors regardless of the running speed and of the disturbances from the context of implementation. Ultimately, the acquired data, if adequately supported by background information related to the track and the rolling stock conditions on 35 which it is installed, seems to be well suitable for a process to identify phenomena related to track defectiveness and an estimate of their variation over time.
IVM Innovative Vibration Monitoring Knowledge to Safety ivmtech.it 36