Shock and Vibration

Volume 2017, Article ID 7150472, 10 pages

https://doi.org/10.1155/2017/7150472

## Research on the Field Dynamic Balance Technologies for Large Diesel Engine Crankshaft System

College of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China

Correspondence should be addressed to Shihai Zhang; moc.361@77ykhsz

Received 15 June 2017; Revised 29 August 2017; Accepted 18 September 2017; Published 18 October 2017

Academic Editor: Mahmoud Bayat

Copyright © 2017 Shihai Zhang and Zimiao Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

In order to reduce the unbalancing mass and the accompanying unbalancing vibration of diesel engine crankshaft system, the field dynamic balancing method and its key technologies are presented in the paper. In order to separate the unbalancing vibration signal from the total vibration signal of crankshaft system, the fundamental frequency signal fitting principle based on the least square method was introduced firstly, and then wavelet noise reduction method was applied to improve the signal fitting precision of least square method. Based on the unbalancing vibration signal analysis and assessment of crankshaft system, the influence coefficient method was applied to calculate the value and phase of the equivalent unbalancing mass in flywheel. To easily correct the unbalancing condition of crankshaft system, the unbalancing adjustment equipment was designed based on the flywheel structure. The balancing effect of field dynamic balancing system designed for the large diesel engine has been verified by field experiments.

#### 1. Introduction

The large diesel engine is the important generating and power equipment of ships. In practice, the unbalancing mass of crankshaft system may be generated and beyond the allowable range affected by the factors of machining precision, installation precision, wear and deformation, and so forth. The huge unbalancing vibration of crankshaft system may be aroused by the unbalance mass of crankshaft system, which can destroy the running stability of diesel engine and then deteriorate the wear condition among the movement units. So the suitable balancing method should be applied to reduce the unbalancing mass and unbalancing vibration of crankshaft system.

The balancing object of diesel engine crankshaft system includes the reciprocating inertia force and rotation inertia force. In general, the special balancing mechanism is installed in diesel engine to balance the reciprocating inertia force. In 1911, the double-shaft balance technology was invented by Lanchester [1]. In 2002, a world class balance shaft system for the 2AZ-FE engine was achieved by Ishikawa et al. using resin gears for the first time ever. Reliability was achieved by developing the high-strength resin optimal impact absorption characteristics [2]. In 2007, the new concept of “thick-thin double-shaft” balancing method for 4-cylinder diesel engine was proposed by Fan et al. [3]. In 2009, Solferino proposed an internal combustion engine with a crankshaft and first and second balance shafts, which were gear driven from one to the other, as a unilateral tensioning system applied to a flexible drive extending between the engine’s crankshaft and the first one of the balance shafts [4]. In 2015, Sajdowitz et al. described a balance system for a single-cylinder engine, for which the balance shaft included a primary balance shaft for the first type of forces and at least one secondary balance shaft for the second type of forces [5].

The counterweights are usually used to balance the rotation inertia force, and the layout methods of counterweights include sectioning balancing method, integral balancing method, and irregular balancing method. In 2000, the mass center displacement method was applied to study the balancing performance of internal combustion engine by Sun and Fang [6]. In 2007, the slipper type balancing mechanism was applied to study and analyze the balancing performance of single-cylinder diesel engine by Sun et al. [7]. In 2009, the effects of counterweight mass and position on main bearing load and crankshaft bending stress of an in-line six-cylinder diesel engine were investigated using multibody system simulation program, ADAMS, by Yilmaz and Anlas [8]. In 2009, the model consisting of crankshaft, connecting rod, and piston was introduced by Yang et al. to separate the reciprocating mass and rotating mass of connecting rod assembly based on the multibody dynamics simulation [9]. In 2011, Liu and Huston presented a set of formulae for determining the ring weights needed for balancing crankshafts of six-cylinder V60 degree engines [10]. In 2012, an optimal conceptual design of a balance shaft was presented by Kim et al. through determining locations of both unbalance and supporting bearing [11]. In 2012, Karabulut devised a three-degree-of-freedom dynamic model for a two-cylinder four-stroke engine, which enabled the simultaneous treatment of the piston-crankshaft mechanism and engine block. A simple relation had been obtained to determine the position and mass of counterweights used for eliminating the vertical vibration of the block [12]. In 2015, Huo et al. built a counterweight theoretical model of transmission mechanism to obtain the values of counterweight and counter-balanced phase angle on crankshaft and output shaft [13]. In 2016, Ipci and Karabulut conducted the conjugate thermodynamic and dynamic modeling of a single-cylinder four-stroke diesel engine, of which the counterweight mass and its radial distance were optimized [14]. In order to study the balance of offset crankshaft engine, a new equation was derived from the traditional one for the kinematics analysis of piston-crank system by Tang et al. in 2016, which was performed on a 3-cylinder engine with single crankshaft and excessive counterweight to calculate the phase relationship between the balance shaft and the counterweight [15].

In practice, the unbalancing condition of crankshaft system may be changed when the diesel engine runs for a long time. In order to adapt the unbalancing condition variation of crankshaft system, the field balancing was proposed by Keizai Seminar et al. in the 1990s. Based on the field balancing method, the unbalance of crankshaft system could be measured and corrected in field, and the balancing precision and its timeliness could be ensured [16, 17].

#### 2. The Separating Method of Unbalancing Vibration Signal

In practice, a lot of harmonic and noise signals are included in the vibration signal of crankshaft system. Different harmonic signals represent different exciting factors, and the unbalancing vibration signal belongs to the fundamental frequency component confused in the total vibration signal of crankshaft system. In order to analyze the unbalancing condition of crankshaft system, the unbalancing vibration signal should be separated from the total vibration signal firstly. The traditional methods concentrated on the filtering and noise reduction based on the Fourier transform. It has been found that the fundamental frequency components of other signals may be confused in the separated fundamental frequency signal based on the traditional methods, and these fundamental frequency components cannot be corrected by the dynamic balancing method [18]. In order to reduce the fundamental frequency components interference of other signals, the least square method was applied to fit the fundamental frequency signal of unbalancing vibration [18].

According to the Fourier series principle, we express the vibration signal of the crankshaft system as the following:

In (1), represents the vibration signal, represents the constant term of the vibration signal, the amplitude and phase of the th order frequency component are, respectively, expressed as and , represents the frequency of the fundamental frequency signal. According to the trigonometric function calculation, we get

We linearize (2) as

The relationship of the parameters in (2) and (3) can be acquired in (4) and (5).

We assume as the sample frequency and as the sample length; then we can get the discrete equation of (5) as the following:

According to the principle of the least square method, we establish the target function as

In function (7), represents the discrete value of the sample signal. To take, respectively, function (7) partial derivative with respect to , which is equal to zero, we get the partial derivative equations as the following:

Equation (8) is the order linear normal equations and can be solved through the Gauss PCA elimination method. We can calculate the values of the parameters , and then gain the values and by solving

To test the precision of the method, we design the signal simulation and fitting programs by Labview language. The equation of the simulation signal is expressed as the following:

In (10), is the noise signal. In order to analyze the signal fitting effect, the uniform white noise signal and periodic random noise signal are added, respectively, in simulation signal. The amplitude of noise signals is set as 0.4 for comparison purposes. The simulation signals are shown in Figure 1.