This research focuses on the analysis of vibration of a compression ignition engine (CIE), specifically examining potential failures in the Fuel Rail Pressure (FRP) and Mass Air Flow (MAF) sensors, which are critical to combustion control. In line with current trends in mechanical system condition monitoring, we are incorporating information from these sensors to monitor engine health. This research proposes a method to validate the correct functioning of these sensors by analysing vibration signals from the engine. The effectiveness of the proposal is confirmed using real data from a Common Rail Direct Injection (CRDi) engine. Simulations using a GT 508 pressure simulator mimic FRP sensor failures and an adjustable potentiometer manipulates the MAF sensor signal. Vibration data from the engine are processed in MATLAB using frequency domain techniques to investigate the vibration response. The results show that the proposal provides a basis for an efficient predictive maintenance strategy for the MEC engine. The early detection of FRP and MAF sensor problems through a vibration analysis improves engine performance and reliability, minimizing downtime and repair costs. This research contributes to the advancement of monitoring and diagnostic techniques in mechanical engines, thereby improving their efficiency and durability.

The objective of this work is to use the autonomous learning methodology as a tool in vehicle maintenance management. In obtaining data, faults in the fuel supply system have been simulated, causing anomalies in the combustion process that are easily detectable by vibrations obtained from a sensor in the engine of an agricultural tractor. To train the classification algorithm, 4 engine states were used: BE (optimal state), MEF1, MEF2, MEF3 (simulated failures). The applied autonomous learning is of the supervised type, where the samples were initially characterized and labeled to create a database for the execution of the training. The results show that the training carried out within the classification algorithm has an efficiency greater than 90%, which indicates that the method used is applicable in the management of vehicle maintenance to predict failures in engine operation.

Biodiesel is one of the best renewable fuels to reduce dependence on petroleum derivatives. The objective of this work is to evaluate the mechanical and environmental performance in compression ignition engines with the use of biodiesel in proportions of 5 % (B5), 15 % (B15), and mixtures with additive B5A and B15A, through the experimentation and use of automotive measuring equipment, for mass application in automotive vehicles. The methodology applied is based on the development of two stages; the first is the preparation of the mixtures to be used in the research with the corresponding diesel/biodiesel percentage for each, and the second is the analysis of mechanical and environmental behavior through the use of properly calibrated and updated diagnostic equipment. The results show that the B5 mixture shows the best values, managing to maintain power and torque with non-significant decreases compared to diesel, with averages of 1.1 % and 0.3 %, respectively. As the percentage of biodiesel increases, the opacity value decreases from 44.8 % with B15 and 59.3 % with B15A. In relation to exhaust gases, additive mixtures show the most significant reduction in CO2, CO, and HC emissions, while NOx emissions rise slightly as biodiesel concentration increases, but statistically, it is not significant.

The present study has the purpose of determining the levels of opacity with the use of diesel and biodiesel based on castor oil at 15\% (B15). For the determination of the opacity an electronic diesel engine test bench was used, the opacity measurements were made using a duly calibrated opacimeter. The Opacimeter consists of a probe which is installed at the end of the exhaust pipe, capturing the gases and yielding their own values for each test, considering the types of fossil fuel or biofuel and engine speed, subjecting several RPMs that go from 1200 to 3000 for each fuel. At the end of the tests, the opacimeter allowed to obtain an opacity of 11.1\% with fossil diesel and 0.386 with B15, obtaining a 96\% reduction in opacity. At the same time, an average opacity of the tests was obtained for each type of fuel, this value being compared with the national standards concerning this study. With these results, it contributes to the conservation of the environment since it emits less amount of soot, in the same way, the respiratory and heart diseases of people are reduced according to the world health organization.

La presencia de hollín en el ambiente ha ido aumentando considerablemente en los últimos tiempos según la Organización Mundial de la Salud (OMG). Uno de los causantes de esta problemática son los motores diesel. El objetivo del presente estudio es evaluar la presencia de hollín en un motor a diesel utilizando biodiesel de Higuerilla y diesel fósil. Las pruebas se realizaron en un banco de motores diésel Mazda BT 50 con sistema CRDi. Para realizar las mediciones se utilizó el opacímetro de marca Braen Bee (modelo opa 100) del laboratorio de Ingeniería Automotriz de la Universidad Técnica del Norte (UTN). El opacímetro está conectado a una sonda que se coloca en el tubo de escape, la cual transporta los gases al equipo. La pruebaconsiste en someter al motor a varias aceleraciones como son 1200, 1500, 2000, 2500 y 3000 [RPM] con el biodiesel de Higuerilla y con el diesel fósil. Una vez completado todas las aceleraciones, se obtiene la diferencia de opacidad, que básicamente sirve para realizar un análisis comparativo de la opacidad mayor con la menor, resultando un promedio porcentual de opacidad, que es el que se debe regular según las normas establecidas. Se ha notado la reducción del 60% en la opacidad de motores diésel con el uso de biodiesel a partir de aceite de Higuerilla en relación al diesel fósil.Palabras claves: Biodiesel, motor diésel,