equipment failures
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With the completion of the State Grid Corporation’s maintenance system, the number of substations has increased dramatically, the grid structure has become increasingly complex, and there have been internal and external reasons such as the contingency of emergencies, and equipment failures have occurred from time to time. This paper aims to explore the potential value of massive data, show the laws of business data, and further give full play to the comprehensive support of data for enterprise operation and production management, and promote the realization of intelligent and lean power grid core business. This paper uses power system data to provide reliable data support for equipment defect full cycle management and equipment state analysis through ANOVA and neural network statistical analysis. At the same time, we use Term Frequency-Inverse Document Frequency(TF-IDF)Algorithm to calculate the importance of keywords and construct the power keyword library. By constructing Bayesian text classification model, we can classify the defect parts, defect categories and defect causes automatically. This method can be applied to the construction of power grid production work order text analysis system, improve the data quality and system automation level, help the business department to improve work efficiency and provide the basis for power grid business analysis. This method is applied to the data cleaning of the primary production equipment of power grid enterprises, and the accuracy of data error correction for equipment defects with voltages above 110kV is between 93% and 95%, and good results have been achieved.

Abstract Many oil producing wells, globally, experience sand production problems when reservoir rock consists of unconsolidated sand. Several wells in the Dzheitune oil field are experiencing a similar challenge. Production of formation fines and sand has caused accumulation of fill and wellbore equipment failures and has necessitated periodical and costly coiled tubing-assisted wellbore cleanout operations. A novel chemical treatment tested in the oil field to tackle the challenge led to positive results. A well with a relatively short target perforation interval was selected as a candidate for the trial sand conglomeration treatment to avoid any uncertainties related to zone coverage. Pre-requisite sand agglomeration and chemical-crude oil compatibility laboratory studies were carried out to optimize the main system and preflush fluid formulations. Once the laboratory testing was complete, a step-rate test was performed to determine the maximum injection rate below formation fracturing pressure. The chemical systems were prepared using standard blending equipment. The preflush fluid was injected to prepare the treated zone. The main fluid was then injected into the reservoir in several cycles at matrix rate by a bullheading process. Upon completion of the treatment, the well was shut in for several days for optimal agglomeration (conglomeration) before the well was slowly put on production. A long-term increase in the productivity index and sand-free flow rate with no damage to the wellbore or the reservoir were observed. The technology demonstrated its efficiency in preventing and controlling sand production; avoiding frequent, time-consuming, costly wellbore cleanout operations; and producing hydrocarbons at reduced drawdown pressure.

Abstract The systems that monitor individual components of machines and devices are under constant development. The ability to detect damages at an early stage allows failures to be prevented, so any uncontrolled downtime can be predicted in a controlled manner. Continuous monitoring of technical condition is an activity that also helps to reduce the losses due to equipment failures. However, not all areas can be monitored continuously. Such areas include lift guides where wear and tear can occur naturally, i.e. through abrasion of the material layer due to interaction with moving guide shoes or after emergency braking. Emergency braking causes local damages to the guide through plastic deformation of its surface resulting from indentation of the knurled roller of the brake. Such places are cleaned mechanically, which results in local reduction of the cross-sectional area. In such a case, it is difficult to continuously assess the technical condition of guides due to the prevailing operating conditions. Therefore, a concept of a head enabling assessment of the technical condition of guides at every stage of their operation has been developed. This article presents the novel concept of a magnetic head used for assessing the technical condition of lift guide rails that are the running track of lifting equipment. The initial tests were performed on the original test setup. The concept of the developed measuring head was verified for correct operation on specially prepared flat bars with holes. The results obtained in the form of laboratory tests proved that the proposed measuring head concept can be applied to the measurements under real conditions.

Based on the number of 519 tunnel risk incidents that occurred in the two tunnels of the Qifu Tunnel and the Zhongcun Tunnel during the period from 2018 to 2019 of Guangming Expressway, this paper studies the temporal and spatial characteristics and the risk distribution of the sunken continuous tunnel during the operation period of the expressway. Type of risk event. The results show that January, May, June and September of the year, as well as 14:00–16:00 and 16:00–18:00 during the day are periods of high tunnel risk; at the entrance section of continuous tunnels, Compared with other locations, the number of risk events in the transition section and the open section with sudden environmental changes and gradient changes is more; the types of risk events include safety hazards, roadblocks, vehicle failures, rear-end collisions, and equipment failures. The main types are vehicle failures. There are certain differences in the east-west direction. There are more vehicle breakdowns in the east-bound direction, more roadblocks in the west-bound direction, and more rear-end collisions in the east-bound direction. The main types of risk events are cars and trucks. Both cars and trucks have major risk event types. It is a vehicle failure. In rear-end collisions, small cars account for 65% of the risk models; risk identification methods include gun patrol discovery, road administration reporting, etc., of which gun patrol discovery is the most important identification method, accounting for 65% of the total. Through the analysis of the risk event characteristics of the sunken continuous tunnel of the expressway, it provides reference opinions for perfecting the research deficiencies in related fields in our country.

The first book on a promising new direction — methodology for equipment failure management for technical managers and specialists of industrial enterprises, as well as for all those whose field of expertise includes the need to deal with equipment failures — has been developed and published under the auspices of the Association for Effective Enterprise Asset Management (EAM Association).

Failure Mode and Effect Analysis (FMEA) techniques were originally developed by the US Military and have been used as techniques for assessing the reliability and effects of equipment failures. However, the first notable applications of FMEA techniques are related to the impressive development of the aerospace industry in the mid-1960s. FMEA is a methodology for systematically analyzing the failure modes of a project, product or process, prioritizing their importance, identifying system failure mechanisms, analyzing potential failure modes and the effects of these failures, followed by corrective actions, which are applied in the stage of conceptual and detailed design of the product. All approaches to FMEA methods in the scientific literature converge to achieve three goals, namely: the ability to predict the type of failure that may occur, the ability to predict the effects of the failure on system operation, and the establishment of the steps to prevent failure and its effects on the system operation. The FMEA for the project of a nose landing gear analyzes the failure modes of the product and their effects in operation, as a consequence of project deficiencies and identifies or confirms critical functions. To apply the FMEA method to the project of the nose landing gear of a military training aircraft, the following steps need to be accomplished: product description and identification of components; identification of functions; identification of potential ways of failure; estimating the frequency of causes of failure; appreciation of the severity of effects; assessment of difficulties in detecting defects; calculation of the Risk Priority Number (RPN); establishing the measures and corrective actions for the analyzed project.

Despite the industrial revolutions, optimization of production processes, the use of robotics and other advances of science and technology, the share of machine-tool equipment in the execution of the plan at industrial enterprises is large. Human-machine interaction is also invariable. In this regard, the injury rate of machine operators from year to year remains above average. To manage the employee occupational risks, it is required to carefully analyze the source of the risk — the machine-tool equipment used. To manage the professional risks of a machine operator, it is required to assess the following parameters of the machine-tool complex: traumatic factors in accordance with the current legal requirements, and the data obtained as a result of the equipment practical application; completeness and content of the technical documentation for the machine-tool equipment; equipment life cycle stage, equipment operation period; fulfillment of the scheduled preventive maintenance schedule; the number and nature of emergency equipment failures; ergonomic indicators of the machine. The analysis carried out according to the specified parameters can be presented visually in the form of a diagram reflecting the condition of machine equipment on six elements and on three levels using generally accepted signal colors: green - corresponds, yellow — partially corresponds, red — does not correspond. Thus, the results of the conducted analysis are visualized on a color chart, and mathematically evaluated as a percentage. Comprehensive assessment of the state of machine-tool equipment makes it possible to more efficiently determine the risks for those working on the machine-tool equipment, as well as develop measures for the modernization or replacement of the machine-tool park.

Abstract The paper analyses the causes of emergency outages on electric networks according to the data of the Pravoberezhny district of Irkutsk for 2008-2017, according to which 82% of failures of elements of the electric network are caused by breakdowns and equipment failure; 9% are due to the influence of external factors; 5% occurred due to natural and climatic reasons, 4% – due to other circumstances. The largest number of outages due to operational reasons occurs due to damage to cable and overhead lines. Accidents caused by the influence of external factors are mainly associated with the negative impact of people, animals and birds. Equipment failures related to natural and climatic factors are mainly due to wind or thunderstorms. Other circumstances, as a rule, include staff errors and unidentified reasons. Calculations of undersupply of electricity and economic losses caused by interruptions in power supply were made. It should be noted that in order to reduce the number of equipment failures, it is necessary to carry out timely maintenance and reconstruction of various elements of electrical networks.