{'fraction_non_alphanumeric': 0.018355359765051395, 'fraction_numerical': 0.0, 'mean_word_length': 5.584541062801932, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Aero-Engine Lubricating Oil Metal Content Prediction Using Non-stationary Time Series ARIMA Model

Aero-engine lubricating oil metal content is a reflection of abrasion and fracture of aero-engine key components. By predicting the metal elements concentration, it is possible to detect the mechanical faults of the corresponding parts in advance, to guarantee flight safety and to reduce the maintenance cost of the aero-engine. The metal element concentration of the aero-engine lubricating oil is influenced by many complicated factors and its change tendency is difficult to be predicted. To solve this problem, an aero-engine lubricating oil metal element concentration prediction method based on the non-stationary time series ARIMA (Autoregressive Integrated Moving Average) model was proposed, the corresponding algorithm model and modeling process of the ARIMA were introduced in detail, and the prediction results are satisfying. The application of ARIMA model in forecasting the aero-engine lubricating oil metal elements concentration was analyzed by examples. To compare with the result of moving average and exponential smoothing method, the proposed method has better fitting and forecasting precision, the research result shows the accuracy and feasibility of aero-engine lubricating oil metal elements concentration forecasting using ARIMA model.