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Our Products, Prototypes, and Projects

Wireless Controlled Track Recording Vehicle (W-TRV)

Wireless Controlled Track Recording Vehicle (W-TRV)

As per the survey, Pakistan bears approximately 100 railway accidents, annually. Most of these accidents are due to a lack of railway track condition monitoring caused by outdated inspection techniques and manually operated rail trollies. In order to mitigate these problems, CM lab has proposed a wirelessly controlled TRV that operates on the marked start and stop points while providing real-time railway track health analysis using Inertial Measurement Units and image processing algorithms integrated with an indigenously built mobile application.

Track Faults Tracker

The railway track fault detection is very necessary for the track health status monitoring to avoid severe accidents which we face every year. To avoid such accidents and by considering Pakistan railway needs, a Railway Track Fault Tracker is designed by using ADXL-335 Accelerometer, GPS (Global Positioning System) module, and the controller ESP-32. The designed prototype is capable of detecting Rail Dip Faults with its GPS locations. Moreover, the product is cost-effective and portable for track fault analysis with a state-of-the-art mobile application that shows real-time fault alerts with Google Maps.

Motor Condition Monitoring System

Motor Condition Monitoring System

In this research, early fault detection and identification system are developed using a tri-axial vibration sensor and three-phase current as input data to the system. The developed system is portable and upgradable. The fault diagnosis is performed using a deep learning algorithm.

QoS Improvement in High-Speed Railway Communications

The railway is the green source of transport which helps reduce the time required to travel and improves in reducing the pollution helping the society and atmosphere. As the technology is growing towards the 5G and beyond, there is a need to upgrade the current railway communication systems from GSM-R to LTE-R and 5G-R to fulfill the capacity and ultra-low latency demands of users onboarding the train on daily basis. The increase in bandwidth will eventually decrease the coverage range and hence the no. of sites would be increased.

Trackside Wheel Tread and Profile Monitoring

Wheels are payload carriers and are a crucial part of railway stock whose automated inspection is necessary. Faulty wheels not only result in discomfort of passengers it also damages the other railway infrastructure. It is also one of the leading causes of railway accidents worldwide. This research aims to develop a track side vision system for checking the wheel tread for any faults and also keep its profile parameters under predefined limits.

Onboard Adhesion Identification from Directly Measurable Parameters

Adhesion is a crucial factor to be estimated for designing and characterizing the braking and tracking force of a railway vehicle. Since it cannot be measured directly between rail wheels, estimation techniques are needed to estimate adhesion between wheel and rail. This project deals with using data-driven algorithms for the identification of adhesion exploiting the dynamic response of vehicles in various operating conditions.

FPGA Based Railway Wheelset Parameter Estimation Using Extended Kalman Filter

The main element of any study of rolling stock behavior is the wheel-track interaction patch. At the wheel-rail contact patch, a certain level of adhesion is necessary for the transfer of tractive force applied by traction and braking network in locomotives. The exerted tractive force may exceed the highest adhesion level present at the wheel-track contact, causing the occurrence of wheel slip in acceleration and skid in braking. This wheel slip/slide largely affects routine railway system operations. In this project, a novel model-based estimator will be developed to estimate the adhesion coefficient and other related parameters.

Squat Detector Stick (SDS)

It is a norm for the push trolleys to be operated nearby railway stations in order for the track inspection personals to determine the track faults using visual inspection. Which is an outdated technique and needs revision in form of developed SDS. SDS is handy, cost-effective, rugged as well as determines the track damages using the image gradient filters along with 2D Wavelet transformation. The developed instrumentation is validated along with the techniques applied by the PR and it has come out to be 87.9% more effective in the identification of the rail track faults.

Road Condition Monitoring Using Axle-Based Acceleration Method and K-Means Clustering Algorithm

Road deterioration remains a major setback if it is not considered significant which causes human casualties and massive financial losses. Hence, road condition monitoring is helpful to ensure comfort and safety to drivers on road. The aim of this project is to design an effective low-cost Axle-Based Acceleration (ABA) system for road condition monitoring to restrain road accidents and vehicle damages on roads.

Driver Attention Detector

Driving a train is a very responsible task as it involves the safety and security of the train passengers. Though the railway department assures the presence of two drivers in the main cockpit of a train, any human error could result in catastrophic fatalities. In order to ensure the attention of a rail driver, an indigenous solution is developed using a Raspberry Pi 3 B+, a webcam, and Open CV libraries for the detection of the driver’s attentiveness. The algorithm works on the basics of the Haar Cascade Classifier for capturing the eyes’ movement, which performs its operation using the binary classifier.

Handheld Track Recording Vehicle for the Identification the Railway Track Surface Faults by using Image Processing Algorithms

Hand-Held Track Recording Vehicle

In Pakistan, several railway accidents are reported due to derailment. The root cause of this derailment is a mechanical failure of tracks, such as broken rails caused by the absence of railway condition monitoring. This could have been avoided if track surface faults, such as squats could had been identified that act as a catalyst for the track to crack and ultimately break. Therefore, through this developed product, we are offering to provide the railway track inspection using a two-step process at an affordable cost.

IoT Enabled Smart Crossings

The railway transportation mode is an acceptable mode that is cherished around the world where accidents occur due to manual crossings leads to a loss of valuable lives of people. In manual crossings, to open or shut the crossing gates, human cooperation and labor are required; and failure to do so causes accidents in which human lives are at great risk. Our key motivation or criterion for creating this product is to eliminate these mishaps. The primary goal of this project is to improve the level of crossing.

Wireless Inertial Measurement Unit

Wireless Inertial Measurement Unit

This is a continuation of the track surface monitoring as discussed earlier. In this work, we have adopted Wireless Sensor Networks (WSN) to overcome problems of the safety of the structure by analyzing them precisely using structural health monitoring techniques. This emphasis on the development of an IOT based smart instrumentation for analyzing the health of the structure based on the accelerometer (ADXL320) and Node MCU. This is based on the work accepted for publication in the Journal of Wireless Personal Communication titled “Development of IOT Based Smart Instrumentation for the Real-Time Structural Health Monitoring” (2020).

Design and Development of a Fault Detection and Diagnosis System for the Rail Gearbox using Non-Invasive Testing

Currently, the functionality of transport has improved but this improvement has also brought complexity in maintenance, leading to frequent occurrences of accidents. Pakistan Railways has also been facing a lot of accidents due to the lack of a proper monitoring system. As a gearbox is one of the components providing driving power to trains, its monitoring is necessary for the maintenance to be done on time. This research aims to develop a system to monitor the operating state of the gearbox of railways using a non-intrusive way of data collection and apply that data to the system trained to identify faults related to the gearbox.

Design and Development of IoT enabled Onboard Condition Monitoring System of Railway Track

Railway is the comfortable and economical way of transportation which interlinks cities and counties around the world. Recently, we have observed the latest infrastructure and facilities for passengers in Pakistan Railway for example – online seat reservation and real-time train locations applications. Despite all this, very severe accidents are observed due to the derailment of the train all around the world and especially in Pakistan. It is noticed that due to the continuous running of Trains and frequent breaking both railway tracks and wheels are affected by heat, stress, and vibrations caused by wheel/rail interactions, leading to weakness, wear, cracks, and other deteriorations.

A Low-Cost Visual Inspection System for Rail Surface Faults Identification

Visual inspection systems for monitoring railway tracks are highly sophisticated instrumentation systems equipped with state-of-the-art hardware for condition monitoring which provide with detailed track profile and as a result are highly expensive. In developing countries where Manuel inspection is the standard method of inspection low-cost visual inspection systems are required. This project is developed to harness the power of deep learning algorithms for compensating the low-quality images acquired from less sophisticated cameras.

Auxiliary Track Testing Bed

Novel Optical Sensing Based Rail Frame for Rail Fault Diagnosis

Railway Track Condition Monitoring Using Dark Field Illumination

Railway Crossing Surveillance

Train Ride Comfort Analyzer

Deep Learning-based Traction Motor Fault Detection System Using MyRIO

A Non-invasive and Portable Motor Fault Diagnosis System

Deep Learning-based Fault Diagnosis of Wheel-rail profile

Wheel side Thread and Profile Monitoring

Gearbox Condition Monitoring Kit