One way to keep the train service flow runs safely, maintenance of railroad geometry is required. Maintenance of railroad tracks uses the Track Quality Index assessment to determine which railroad ...compartments or corridors are prioritized for repair. The research method used is a quantitative research method. The calculation of the TQI of railroad tracks includes force, height, spoor width and lining. The results of the calculation of the TQI value (manual) give the cumulative total number of standard deviation index is 21.6. While the TQI calculation (mechanical) total cumulative number index standard deviation is 21.2. Based on the results of the TQI calculation, the condition of the railroad tracks can be classified into the criteria for the TQI level II (standard deviation of 20 - 35), namely that the railroad can be passed by trains at speeds of 80-100 km/hour. The railroad maintenance based on the TQI is the repairs to rail compartments or corridors that experience leveling damage in segment 9, lining damage in segment 7, wide damage spoor (gauge) in segments 5,7 and 10 and elevation damage (cant) in segment 3.
•Track geometry data dimension reduction and low rank assumptions validation.•Principal components sufficiently summarize track geometry features in 3D.•Machine learning offered great potential in ...rail exception and defects monitoring.•Some existing artificial TQIs may not actually measure ride quality as intended.•Findings offer insights into predictive maintenance based on geometry degradation.
Track geometry data exhibits classical big data attributes: value, volume, velocity, veracity and variety. Track Quality Indices-TQI are used to obtain average-based assessment of track segments and schedule track maintenance. TQI is expressed in terms of track parameters like gage, cross-level, etc. Though each of these parameters is objectively important but understanding what they collectively convey for a given track segment often becomes challenging. Several railways including passenger and freight have developed single indices that combines different track parameters to assess overall track quality. Some of these railways have selected certain parameters whilst dropping others. Using track geometry data from a sample mile track, we demonstrate how to combine track geometry parameters into a low dimensional form (TQI) that simplifies the track properties without losing much variability in the data. This led us to principal components. To validate the use of principal components as TQI, we employed a two-phase approach. First phase was to identify a classic machine learning technique that works well with track geometry data. The second step was to train the identified machine learning technique on the sample mile-track data using combined TQIs and principal components as defect predictors. The performance of the predictors were compared using true and false positive rates. The results show that three principal components were better at predicting defects and revealing salient characteristics in track geometry data than combined TQIs even though there were some correlations that are potentially useful for track maintenance.
The data fusion of radar and automatic dependent surveillance-broadcast(ADS-B) is the effective method to surveille the 'black flights' and flying birds. However, the tracking performance of the two ...sensors has large differences and is easy to be fluctuated, which will bring a decline in fusion accuracy. A data fusion method of radar and ADS-B based on track quality assessment is proposed. Firstly, the effects of local track accuracy, data update times and sensor measurement errors on local track quality on corresponding assessment factors are analyzed and quantified. And then, these assessment factors are combined to calculate the quality weighting factors of the local track, and the asynchronous track fusion processing of radar and ADS-B is completed based on the distributed fusion structure. Finally, the feasibility and effectiveness of the proposed method is verified with simulation experiment and application. The results show that the proposed fusion method can effectively improve the fusion accuracy, an
Dalam analisis regresi, salah satu asumsi yang harus dipenuhi adalah tidak adanya hubungan antar variabel independen. Hubungan yang kuat antar variabel independen disebut dengan multikolinieritas. ...Berbagai metode dapat menanggulangi kasus multikolinieritas, semua itu bergantung pada tujuan dari penelitian. Beberapa metode tersebut adalah ridge regression, principal component regression, regresi robust dan pemilihan model terbaik. Pada penelitian ini, metode pemilihan model terbaik dipilih untuk digunakan karena bertujuan untuk menentukan variabel independen yang signifikan dengan mempertimbangkan korelasi parsial pada data track quality index (TQI) kereta api Indonesia. Untuk mengukur besarnya TQI diperlukan empat indikator yang kemudian menjadi variabel dalam penelitian ini, yaitu lebar jalur, angkatan, listringan dan pertinggian. Hasil analisis menunjukkan variabel pertinggian, angkatan dan listringan berpengaruh besarnya nilai TQI dengan variasi data yang dapat dijelaskan model sebesar 99,7%.
Selective Laser Melting (SLM) is a manufacturing process that involves layer-by-layer fusion of metal powder material using a laser beam. AlSi10Mg alloy, a hypoeutectic aluminum-silicon alloy, is ...known for its favorable mechanical properties, low density, and corrosion resistance, making it widely used in various industries. While traditionally used for casting, the unique properties of AlSi10Mg alloy have opened up opportunities for additive manufacturing, including SLM technology. This paper explores the tracks quality and preferable parameter interval for production via SLM. SLM products exhibit unique microstructures with distinct advantages and limitations. This study underscores the importance of careful parameter selection during SLM and the need for effective quality control in achieving desired mechanical properties.
•The CIV and the DIV are innovatively proposed for index calculation.•This paper proposed the QCI based on EWM-FAHP and calibrated by FEM.•Damage correction function was used to measure the more ...deteriorating effect.•Suggestions can be put forward for the maintenance and repair of ballastless track by QCI.
This paper aims to guide the maintenance and repair of ballastless track quality by determining a set of comprehensive evaluation indices. We take the China Railway Track System (CRTS) III slab track as an example and mainly look at two typical types of damage, namely, cracking and interlayer debonding. Based on the entropy weight method-fuzzy analytic hierarchy process (EWM-FAHP), cracking interspace volume (CIV) and debonding interspace volume (DIV) and subsequent weights were proposed to measure the damage degree. In addition, a model containing cracking and debonding was established using the ABAQUS finite element software, and these weights were modified based on the models' calculated results. Then, the quality condition index (QCI) was determined to assess the quality state of the slab track in a comprehensive manner. This index was further used in a case study to evaluate the quality of the slab tracks in real-scenario cases and thereby bring forward appropriate O&M suggestions.
Transportation is still a significant problem in Indonesia. Indonesians prefer to use private vehicles for daily mobility purposes because public transportation lacks safety and comfort and has a ...longer trip duration. This issue causes congestion and air pollution problems. Hence, sustainable railbased public transportation is recommended. Light Rail Transit (LRT) tends to be congestion-free and has a relatively shorter travel time with a large passenger capacity. Most LRT track constructions use the ballastless track. However, this track construction is still new in Indonesia. The research aimed to determine the most important factors in improving ballastless track construction performance on LRT. The research referred to the existing LRT construction in Indonesia using Lean Construction (LC) and Project Quality Management (PQM) approaches. Statistical science approach with SmartPLS software was also used in data processing and modeling the relationship between variables. The research was conducted by distributing questionnaires to determine the most important factors in improving the quality of ballastless tracks with variables and indicators extracted from LC and PQM methods. From five tested hypotheses, only one hypothesis is accepted. Quality control has a positive effect on track quality. It is also found that quality control becomes the most important variable in improving ballastless track quality.
This study concerns track quality assessment of standard-gauge railways in the context of the Hungarian railway system. Data gathered by multipurpose track recording vehicles matched the EN 13,848 ...requirements. Track Quality Index (TQI) measurement systems (The Federal Railroad Administration (FRA), the Netherlands’, and the Chinese TQI) are considered where three types of predetermined segment techniques: separate, moving, and Zero-crossings segmentation are employed. The importance of track segmentation in quality assessment, which affects maintenance planning, is shown by key findings. For heterogeneous data, the TQIs might be deceptive, highlighting the need for alternatives. The robustness of the Zero-crossings method makes it possible to analyze deterioration factors in great detail and in some efficient way. Longer analytical segments and smoothing of the data improved precision. Based on empirical data, we advise considering a Zero-crossings strategy for precise and efficient track-quality evaluations. With the help of this study, track quality can be better evaluated for train systems.
As the requirements for reduced vibration of URT viaduct lines continue to increase, low-stiffness structures have been used extensively. When the TSI are adversely affected by low-stiffness ...structures, the TGI maintenance workload increases sharply. Therefore, it is necessary to predict and evaluate the TDGS of low-stiffness URT viaduct to resolve the conflict between vibration-reduction design and track maintenance. First, the train-steel spring floating slab track-U-beam viaduct model is established. Second, virtual track inspection method is used to obtain the virtual dynamic irregularities. After comparing with actual measurement results, we investigated the influence of linetype, bridge span, and static irregularities on the security indexes and the TDGS. The results showed that for curved viaduct, in addition to vertical dynamic irregularities, alignment/horizontal dynamic irregularities also have characteristic wavelengths at 1/n times bridge span. The time-domain peak values were larger than those of the straight viaduct. Moreover, as the bridge span increased, the TDGS degradation of the curve viaduct was more significant than straight viaduct. The vehicle security indexes of the low-stiffness viaduct lines have large safety margin, while TDGS indexes are close or even exceed the limit when structures are improperly designed. This could bring insurmountable difficulties to the track maintenance.
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