Identification of Wear Condition in IC Engine by Wear Debris Monitoring

*Mohit Kumar, R.B. Sharma, Kuldeep Chaudhary and Ranjeet Singh* 

### **Abstract**

 The objective of the present work is to develop a simple technique to predict and quantify the presence of wear condition in an IC engine based on wear debris monitoring. Wear debris are formed in the engine oil mostly due to friction between two parts of engine and/or extraction of material from the various parts of the engine. A test rig has been developed based on the Ferrography principle to perform the experimental investigation for engine oil analysis. A series of engine oil samples from an IC engine during different time intervals were considered and the wear debris analysis was performed based on total particle concentration of different material (ferrous material and non-ferrous material), size of wear debris and visual inspection of particles. The results demonstrate that the concentration, size and visual inspection of ferrous and non-ferrous debris, which was present in the oil correlated well with the severity of the condition of the IC engine. This is also useful to diagnosis the fault present in the engine.

**Keywords:** wear monitoring, IC engine, engine oil, ferrography, wear debris analysis

#### **1. Introduction**

 IC engines are mostly used in the automotive sector due to their better fuel economy and low maintenance. Condition monitoring of the IC engine or its various components is very important for its appropriate functioning. The various studies that are available in the literature for condition monitoring of the machine components use different techniques such as vibration analysis, acoustic emission, wear debris analysis, and thermography. Some studies are also available regarding the modeling of acoustic emission, which are significant to comprehend the concrete mechanism of the generation of acoustic emission during the operating condition of the gear pair as well as rolling element bearing [1–3]. IC engines suffer from several problems such as wear debris, high levels of exhaust NO*x*, particulate matter and black smoke [4]. These problems are generated due to improper combustion, oil burning and friction between two parts of engine. The lubrication system used in IC engines is splash lubrication system, which is used to lubricate all parts of the engine. In the lubrication system, the oil flows through the splash system in which the crankshaft rotates which in turn splashes the oil on the various parts of the engine. The oil first lubricates the crankshaft then goes into the main gallery and

proceeds by connecting rod to piston and then cylinder. The oil then lubricates the camshaft proceed by rocker arm and then the valves. After lubricating the parts of engine, the oil flows back to the sump through the oil gallery [5]. The oil lubricating the engine parts carries the wear debris back into the sump.

The wear debris analysis technique is extensively used in monitoring the condition of an IC engine, machine and gearbox. Many researchers use oil-monitoring techniques for condition monitoring such as the ferrography technique [6], grey system theory [7, 8], FTIR [9], rotary particle depositor (RPD), particle quantifier (PQ ) and spectrometric oil analysis. Ferrography is used to quantify the amount of wear particles within a given oil sample and to conduct microscopic analysis of that debris in order to identify its size and shape [10]. Spectrometric oil analysis can determine the residual life of IC engines and gearboxes by performing tests on the engine oil at regular intervals. The tests performed on the engine oil reveal the chemical composition of any metal particles suspended in the oil samples, any pre-time wear of engine parts can be identified and preventive maintenance can be done [11]. The relationship between oil monitoring information and the residual life is established, which states that the predicted residual life may be proportional to the wear increment measured by the oil analysis. In spectrometric analysis, the metal concentration found includes many variables such as Fe, Cu and Al etcetera [12]. Color plays an important role in wear debris analysis [13, 14]. Wear can also be identified using their color features.
