Fatigue remaining life estimation for remanufacturing truck crane Jib structure based on random load spectrum

Abstract

For remanufacturing truck cranes with the characteristic of single piece production, the coupling effect of multi‐physical fields and the correlation of multi‐defect modes are also faced in service. This causes that the safety of crane jib structures has great volatility and uncertainty and is difficult to be judged by fatigue test and damage test. To solve the above problems, an approach of fatigue remaining life evaluation based on random load spectrum is presented. By collecting operating cycle times corresponding to characteristic parameter values during the given time period, the small‐sample measured load spectrum is acquired. Six probability distribution models are used to fit the lifting weight sample in characteristic parameters and the optimal distribution model based on Akaike's information criterion (AIC) is obtained. With the Latin hypercube sampling (LHS) method, a random sample of lifting weight is determined within the fixed inspection cycle. In addition, combining with the rated lifting weight table of truck crane, the corresponding jib length and working range are confirmed. Through defining random values of character parameters and matched operating cycle times, a random load spectrum is gained, thus enabling the extension of measured load spectrum. Depending on the remanufacturing information database, the remanufacturing information of truck crane are retrieved to determine fatigue dangerous cross sections and critical points of jib structures. In order to reflect the variation of structure stress level, the equivalent cross sections of dangerous cross sections are constructed. The first principal stress–time history simulation model for critical points is established, and the rain‐flow counting technology is adopted to extract the two‐dimensional stress spectrum from simulation results. Using the Paris formula combined with the greatest risk principle, the fatigue residual life of jib structure is estimated. Furthermore, the fatigue remaining life evaluation system for jib structure of remanufacturing truck crane is developed for easier application of the proposed method. Finally, as an illustrative example, jib structures of ZLJ5551JQZ110V remanufacturing truck crane are provided to demonstrate the validity and feasibility of this method and system.

A new frequency domain method for random fatigue life estimation in a wide‐band stationary Gaussian random process

“…According to Kihl and Sarkani, the Goodman equation [28][29][30] can provide a reasonable and conservative prediction of the fatigue life, whether the mean stress is tensile or compressive. According to Kihl and Sarkani, the Goodman equation [28][29][30] can provide a reasonable and conservative prediction of the fatigue life, whether the mean stress is tensile or compressive.…”

Nonlinear Vibration of Ladle Crane due to a Moving Trolley

“…Xin et al [18] constructed a nine-degree-of-freedom mathematical model of a "human-crane-rail" system and an annoyance rate model for use in the optimization of the structural parameters of overhead traveling cranes and used the particle swarm optimization algorithm to optimize the structural design of overhead cranes. Some scholars predicted crane fatigue life by analyzing dynamics of vibration system [19,20].…”

“…The dynamic responseq Δt ,q Δt , and q Δt of (16) at moment Δ is calculated by (17)- (20). (2) The results obtained in step (1) are substituted into (14) and (15).…”

“…(2) The results obtained in step (1) are substituted into (14) and (15). The payload swing angle responses̈Δ , Δ , and Δ are calculated according to (17)- (20). The cabin vibration responsëΔ ,̇Δ , and Δ is the same.…”

Fatigue life prediction of mechanical structures under stochastic loading

“…The general procedure of life prediction from point of view of fatigue damage was based:  determination of the most significant working regimes and factors of typical working conditions from point of view of structure loads and their following activities [5][6][7],  identification of carrying structure critical parts and determination of their working loads,  analysis of choice material properties and estimate of effects of different types of notches, connections and nonlinearities in examined points of structure [8,9] and  application of suitable hypothesis of fatigue damage cumulation and quantification of predicted fatigue life of selected parts of carrying structure [10,11].…”