Equipment predictive maintenance system and method for underground reclaimed water plant

Abstract

The invention provides an equipment predictive maintenance system and method for an underground reclaimed water plant, which implements equipment predictive maintenance through data collection, standardized processing, data drive, and generation schemes, and collects monitoring data, paper data, and empirical data. Data sorting to generate standardized data; process the standardized data to establish a database of equipment operation failures; based on the equipment operation failure database, through data-driven recursive neural network machine learning, the data in the equipment operation failure database is continuously trained to form equipment predictions The predictive maintenance model; the standardized data is used as the input parameter of the equipment predictive maintenance model, and the predictive maintenance plan is output. The invention standardizes the operation data of the equipment in the reclaimed water plant, reduces the dependence on professionals, improves the safe operation time of the equipment, reduces the downtime maintenance cost caused by equipment failure, and improves the operating efficiency of the equipment in the whole plant, which is of great significance to the safe and stable operation of the reclaimed water plant.

Description

technical field [0001] The invention relates to the technical field of reclaimed water treatment equipment management, in particular to an equipment predictive maintenance system and method for underground reclaimed water plants. Background technique [0002] The underground reclaimed water plant is located in a relatively closed space, the humidity in the space is high, and the gas components in the water plant are more. At the same time, the influent water source of the reclaimed water plant contains relatively more sediment and other substances, which will cause more erosion to the production and operation equipment of the reclaimed water plant. More serious, it is more likely to cause equipment loss or even failure. At present, the equipment maintenance of the underground reclaimed water plant relies on the production and operation experience of professionals. After the vibration and other abnormalities of the equipment are observed with the naked eye during the inspecti...

AI Technical Summary

Problems solved by technology

Since the equipment has broken down at this time, it is often necessary to shut down for maintenance, which affects the normal production and operation of the reclaimed water plant

[0003] For underground reclaimed water plants, the coverage of the basic network is generally not high. The main water treatment equipment is usually not equipped with sensors to monitor the operation status data of the equipment. Data collection and analysis

At the same time, there is a lack of monitoring, collection and analysis of environmental data that affects equipment operation

Without the monitoring and analysis of these data, it is impossible to accurately grasp the real-time operating status of the equipment, let alone make decisions on the predictive maintenance of the equipment

Since the operating status of the equipment is unknown, once the equipment fails, it will take a long time to stop for maintenance, which will have an adverse impact on the normal production and operation of the reclaimed water plant.

[0004] Traditional equipment maintenance systems rely more on probabilistic and statistical tools, focusing on historical data of equipment, and less consideration is given to predictive maintenance of equipment

At the same time, the degree of quantification of the safety inventory of spare parts for equipment is not high, and it is difficult to improve the control effect on the overall operating cost of the water plant

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