Cloudmounter 3.4 crack
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In addition, the application of fault diagnosis in petroleum field is too few, the main research results are also mainly focused on fault diagnosis and analysis under fixed working conditions.
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But as the amount of data storage increases, the amount of data to be processed and the corresponding feature dimension increase, these factors will make the fault database rich, but also weaken the information redundancy, data processing, and computing capacity. With the development of diagnosis technology, this simple diagnosis method cannot meet the development needs, and then more reliable and accurate modern signal processing and feature extraction methods are derived. In the process of fault diagnosis of mechanical equipment, after obtaining equipment information, equipment fault is judged by simple time domain signal in the early stage. At the same time, predicting the future operation trend and remaining service life of the equipment and carrying out equipment maintenance in advance can save maintenance costs, improve economic benefits of enterprises, avoid accidents, and ensure personnel safety. Monitor the condition of large-scale key gear transmission equipment in the petroleum industry, timely handle the faults in the operation of petroleum equipment, and ensure the safe operation of the equipment. At least, it will lead to the decline of product or service quality and even cause huge economic losses and casualties. However, affected by the bad working environment, heavy load, high speed, and other working conditions, some typical parts of petroleum drilling and production equipment, such as gears and rolling bearings, are prone to various types of failures, which will affect the safety and reliability of the whole petroleum drilling system. The key transmission equipment of petroleum drilling equipment is the key part to ensure the normal operation and power transmission of the whole equipment system. Fault diagnosis technology plays an important role in ensuring the reliability, safety, and maintainability of equipment operation.
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Therefore, higher requirements have been put forward for the safety, reliability, and maintainability of the equipment in the operation process. At the same time, the structure of equipment has become more complex. With the manufacturing industry entering the “industry 4.0” era, modern mechanical equipment has absorbed the new technology of modern science and technology development, and the degree of automation of mechanical equipment has become higher. The results show that the accuracy of the SOM model for fault diagnosis is high, and the bearing in gearbox can be replaced or repaired in advance according to the residual life curve, so as to achieve the purpose of predictive maintenance. The state index of life prediction is determined, and the remaining service life prediction of gear transmission system is predicted based on exponential degradation model. Based on the SOM neural network algorithm, an intelligent diagnosis model of gear fault is proposed, and the PCA method is used to reduce data dimension and fuse features. In order to solve the problem that variable working conditions and fault types cannot be diagnosed in gear fault diagnosis of petroleum drilling equipment, four kinds of faults, namely, gear broken tooth, gear crack, gear pitting, and gear wear, are studied in this paper.