This paper analyses the wear mechanisms occurring in connecting rod bearings, which are exposed to various mechanical failures, such as incorrect assembly, high loads, extreme temperatures, unsuitable operating conditions, or loss of lubrication. The investigation was conducted on previously collected post-service samples, each evaluated for factors contributing to their wear or damage. The samples came from eight engines belonging to two groups – four- and six-cylinder BMW units installed in vehicles produced during the same time period. Advanced research techniques, such as optical microscopy, surface profilometry, and hardness measurements, were employed for the bearing analysis. Several wear mechanisms were identified, including sliding wear, fatigue wear (characterised by visible cracks and material pull-out), surface discolouration, as well as two-body and three-body abrasive wear (evidenced by friction marks). The research enabled a detailed characterisation of bearing wear mechanisms and improved understanding of the factors influencing their durability under various operating conditions.

This article presents research concerning the recognition of road traffic lights. Initially, vision algorithms were analysed regarding their suitability for implementation in vehicle control systems dedicated to individuals with specific communication needs. The paper presents the results of experimental studies on a vision system for recognising traffic lights, conducted using convolutional neural networks (CNNs). For the experiment, a custom database of traffic light images was prepared. This database was utilised to train a selected Xception CNN model and for processing by a classic algorithm based on colour analysis in the HSV colour space. The obtained classification accuracy results, reaching 98.75%, could serve as a 'green light' for implementing the developed technology to assist driving. The research findings may also find application in driver assistance systems, with particular attention given to the mobility of people with specific needs, such as those with visual impairments.

This article presents a study on popular algorithms for building 2D and 3D environmental maps using unmanned ground vehicles (UGVs). The research was conducted using a mobile robot integrated with the ROS Noetic platform and equipped with LiDAR, Kinect, and odometry sensors. The robot’s control system implements advanced map generation algorithms based on fusing data from these sensors. The paper first investigates three CPU cooling system configurations for the robot’s onboard computer, analysing their performance under the computational load imposed by the mapping algorithms. Subsequently, the accuracy of specific mapping algorithms (Hector SLAM, GMapping, and RTAB-Map) was evaluated.

This work aims to present the design and development process of a voice-controlled chessboard equipped with a mechanism for moving chess pieces. The article explores different chessboard games that can be automated, incorporating various control methods such as voice commands and autonomous robotic systems. The authors implemented a mechanism located beneath the chessboard to move the pieces, which they deemed more practical and safer for the user. This approach also enables a more natural movement of the pieces, which appeals to players. The system’s key components include the Arduino Mega microcontroller, stepper motors, and a voice recognition module. The movements are controlled through voice commands. In constructing the mechanism, elements made using additive techniques, along with linear guides and bearings were utilised. All moves are controlled by an algorithm that calculates the positions and checks whether they comply with the rules of chess. The key design considerations were lightweight construction, accurate piece movement, quiet operation, and voice recognition. The main goal was a device that could be easily replicated by those with the necessary technical expertise. The result is a voice-controlled chessboard, capable of captivating both novice and experienced chess players alike.

Nowadays, nanotechnology has become very popular, and life without it is difficult to imagine. This technology concerns nanomaterials and has wide applications in science, engineering, medicine, defence, and industrial sectors. Nanotechnology is a term coined by Norio Taniguchi in 1974. Usually, it is used to describe processes in semiconductors, such as thin-film deposition. It deals with phenomena on the scale of nanometres. The processes central to nanotechnology, such as separation, deformation, and consolidation, can be performed on a single atom or molecule. Compared to bulk materials, matter at the nanoscale exhibits unusual properties and is highly reactive. This affects the electrical properties and strength of these materials. The primary purpose of using this technology in various applications is to fabricate novel products, formulated with new materials and chemicals, and replace currently available equipment with systems offering improved performance levels. Carbon nanotubes play a role in enhancing the strength of materials, body armour, radar-absorbing structures, smart textiles, detection/neutralisation of warfare agents, wearable thermoelectric devices, water purification, sensors, and flat-panel displays. One significant strategy for sustainable development is the invention of lighter materials. These lighter materials are at the top of the list of innovative engineering materials that may be used in any technological or engineering sector. The content of this research paper is entirely based on an oration delivered by an author on ‘Technology Day’ that is celebrated every year. The author collected information through various research papers and internet those are available in the open access.

This research aimed to determine the bearing strength of quasi-isotropic composites, considering their application in aircraft airframe repairs, and to investigate the influence of joint geometry on this strength. The research focused on a CFRP composite produced from a carbon prepreg. Specimens cut from the composite underwent static tensile testing to determine their tensile strength and modulus of elasticity. The effect of drilling a hole for a mechanical fastener on the composite material’s strength was examined. The influence of the hole’s distance from the specimen edge on the bearing stress and the maximum failure loads was investigated. The surface bearing stress in the composite under bolt load was determined, and tomographic tests were performed. Experimental studies were supplemented by numerical analysis, yielding stress distributions within the composite under fastener load. It was demonstrated that the failure load increases as the hole’s distance from the specimen edge increases. Furthermore, the reduction in composite material strength due to drilling was estimated at approximately 30%. The results highlight the importance of considering this strength reduction and maintaining appropriate rivet or bolt joint dimensions during the design of mechanical joints in composites.

The article discusses various aspects related to determining the composition of exhaust gases (i.e. nitrogen oxides) generated by a turbine aircraft engine. The paper highlights the problem of ozone depletion caused by toxic components of aircraft engine exhaust gases. The study is concerned with an engine used on the F-16 aircraft, i.e. F100-PW-229. GasTurb 12 software was used to calculate the engine’s operating parameters and to determine nitrogen oxides emission levels. The calculations were also performed analytically. The calculated thrust value was compared with data published in scientific articles (thrust of the engine). Characteristics of NOx emissions were obtained as a function of high-pressure rotor speed, temperature at the combustion chamber outlet, temperature downstream of the compressor, and engine thrust. The results obtained seem to correlate closely with data available in the literature.

The article describes a proprietary method for designing a specialized multi-sensor optoelectronic head for unmanned aerial vehicles, capable of surveying war zones as well as detecting and locating injured soldiers. The first section of the article defines the assumptions made in relation to the structural characteristics of the designed head and compares the parameters and capabilities of heads available on the market. The subsequent section of the article describes structural solutions used in the head and discusses selected aspects related to its construction.

Drones are capable of carrying objects of various types. However, their landing pad detection systems did not consistently perform as intended to environmental conditions, such as inclement weather or inadequate illumination. This article presents a simplified precision landing algorithm for unmanned aerial vehicles (UAV) with the objective of enhancing accuracy of the landing procedure. The proposed system relies on integrating a GPS module, an ultrasonic distance sensor and a proximity sensor. The GPS is responsible for navigating the drone to the designated Target location, the ultrasonic sensor assists in decreasing the drone’s altitude, and the proximity sensor ensures an accurate detection of the landing pad. The UAV is required to execute landings in open environments, where fluctuating environmental conditions and mobile landing pads represent principal challenges. Therefore, the model takes into account has such difficulties as reduced stability, caused by wind or non-permanent placement of the landing pad over time. The study included simulations performed in the Python environment, which allowed to test the algorithm’s effectiveness in different scenarios, such as variable weather conditions and landing pads moving at different speeds. Simulation results show that the simplified model allows to limit the landing error to a few centimeters, which proves its effectiveness during a safe UAV precision landing procedure. Future testing performed by the authors will encompass the development of a dynamic algorithm, physical modifications to the UAV and a comparative of simulation results.

The following article presents an analysis concerned with the potential use of vision and machine learning solutions implemented at automated workstations with industrial robots. Aspects related to various elements of such stations and theoretical foundations have been analyzed, and examples of equipment and program components have been given to open up new options related to industrial robotics, trajectory planning, collision avoidance, and safety.