英文原文： Fatigue life prediction of the metalwork of a travelling gantry crane V.A. Kopnov Abstract Intrinsic fatigue curves are applied to a fatigue life prediction problem of the metalwork of a traveling gantry crane. A crane, used in the forest industry, was studied in working conditions at a log yard, an strain measurements were made. For the calculations of the number of loading cycles, the rain flow cycle counting technique is used. The operations of a sample of such cranes were observed for a year for the average number of operation cycles to be obtained. The fatigue failure analysis has shown that failures some elements are systematic in nature and cannot be explained by random causes.卯1999 Elsevier Science Ltd. All rights reserved. Key words: Cranes; Fatigue assessment; Strain gauging 1. Introduction Fatigue failures of elements of the metalwork of traveling gantry cranes LT62B are observed frequently in operation. Failures as fatigue cracks initiate and propagate in welded joints of the crane bridge and supports in three-four years. Such cranes are used in the forest industry at log yards for transferring full-length and sawn logs to road trains, having a load-fitting capacity of 32 tons. More than 1000 cranes of this type work at the enterprises of the Russian forest industry. The problem was stated to find the weakest elements limiting the cranes' fives, predict their fatigue behavior, and give recommendations to the manufacturers for enhancing the fives of the cranes. 2. Analysis of the crane operation For the analysis, a traveling gantry crane LT62B installed at log yard in the Yekaterinburg region was chosen. The crane serves two saw mills, creates a log store, and transfers logs to or out of road trains. A road passes along the log store. The saw mills are installed so that the reception sites are under the crane span. A schematic view of the crane is shown in Fig. 1. 1350-6307/99/$一see front matter 1999 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 0一6307(98) 00041一7 A series of assumptions may be made after examining the work of cranes: ·if the monthly removal of logs from the forest exceeds the processing rate, i.e. there is a creation of a log store, the crane expects work, being above the centre of a formed pile with the grab lowered on the pile stack; ·when processing exceeds the log removal from the forest, the crane expects work above an operational pile close to the saw mill with the grab lowered on the pile; ·the store of logs varies; the height of the piles is considered to be a maximum; ·the store variation takes place from the side opposite to the saw mill; ·the total volume of a processed load is on the average k=1.4 times more than the total volume of removal because of additional transfers. 2.1. Removal intensity It is known that the removal intensity for one year is irregular and cannot be considered as a stationary process. The study of the character of non-stationary flow of road trains at 23 enterprises Sverdlesprom for five years has shown that the monthly removal intensity even for one enterprise essentially varies from year to year. This is explained by the complex of various systematic and random effects which exert an influence on removal: weather conditions, conditions of roads and lorry fleet, etc. All wood brought to the log store should, however, be processed within one year. Therefore, the less possibility of removing wood in the season between spring and autumn, the more intensively the wood removal should be performed in winter. While in winter the removal intensity exceeds the processing considerably, in summer, in most cases, the more full-length logs are processed than are taken out. From the analysis of 118 realizations of removal values observed for one year, it is possible to evaluate the relative removal intensity g(t) as percentages of the annual load turnover. The removal data fisted in Table 1 is considered as expected values for any crane, which can be applied to the estimation of fatigue life, and, particularly, for an inspected crane with which strain measurement was carried out (see later). It would be possible for each crane to take advantage of its load turnover per one month, but to establish these data without special statistical investigation is difficult. Besides, to solve the problem of life prediction a knowledge of future loads is required, which we take as expected values on cranes with similar operation conditions. The distribution of removal value Q(t) per month performed by the relative intensity q(t) is written as where Q is the annual load turnover of a log store, A is the maximal designed store of logs in percent of Q. Substituting the value Q, which for the inspected crane equals 400,000 m3 per year, and A=10%, the volumes of loads transferred by the crane are obtained, which are listed in Table 2, with the total volume being 560,000 m3 for one year using K,. 2.2. Number of loading blocks The set of operations such as clamping, hoisting, transferring, lowering, and getting rid of a load can be considered as one operation cycle (loading block) of the crane. As a result to investigations, the operation time of a cycle can be modeled by the normal variable with mean equal to 11.5 min and standard deviation to 1.5 min. unfortunately, this characteristic cannot be simply used for the definition of the number of operation cycles for any work period as the local processing is extremely irregular. Using a total operation time of the crane and evaluations of cycle durations, it is easy to make large errors and increase the number of cycles compared with the real one. Therefore, it is preferred to act as follows. The volume of a unit load can be modeled by a random variable with a distribution function(t) having mean22 m3 and standard deviation 6;一3 m3, with the nominal volume of one pack being 25 m3. Then, knowing the total volume of a processed load for a month or year, it is possible to determine distribution parameters of the number of operation cycles for these periods to take advantage of the methods of renewal theory [1]. According to these methods, a random renewal process as shown in Fig. 2 is considered, where the random volume of loads forms a flow of renewals: In renewal theory, realizations of random:，，，having a distribution function F-(t), are understood as moments of recovery of failed units or request receipts. The value of a processed load:，，after }th operation is adopted here as the renewal moment. Let F(t)=P﹛?n＜t﹜. The function F-(t) is defined recurrently, Let v(t) be the number of operation cycles for a transferred volume t. In practice, the total volume of a transferred load t is essentially greater than a unit load, and it is useful therefore totake advantage of asymptotic properties of the renewal process. As follows from an appropriate limit renewal theorem, the random number of cycles v required to transfer the large volume t has the normal distribution asymptotically with mean and variance. without dependence on the form of the distribution function月t) of a unit load (the restriction is imposed only on nonlattice of the distribution). Equation (4) using Table 2 for each averaged operation month,function of number of load cycles with parameters m,. and 6,., which normal distribution in Table 3. Figure 3 shows the average numbers of cycles with 95 % confidence intervals. The values of these parameters for a year are accordingly 12,719 and 420 cycles.
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