Low speed diesel engine fault diagnosis system

Abstract

The invention discloses a low speed diesel engine fault diagnosis system. The system comprises an HMI client, an intelligent remote communication module, a real-time simulation machine, a database storage server, a data processing server, a field communication module, a data acquisition module and a third-party module; the real-time simulation machine, the database storage server, the field communication module, the data acquisition module and the third-party module are all connected to the data processing server; the data processing server is connected to the HMI client; the HMI client is connected to the intelligent remote communication module. The system adopts algorithms such as big data, machine learning, pattern recognition and the like, analyzes real-time operating parameters of a diesel engine on the basis of a calibrated diesel engine fault characteristic parameter model, a mathematical model of a main system and performance parameter big data, accurately diagnoses and positioning faults, provides troubleshooting suggestions and measures, and can perform health management and fault prediction for the diesel engine throughout an entire life cycle.

Description

technical field [0001] The invention relates to the field of fault diagnosis of equipment, in particular to a low-speed diesel engine fault diagnosis system. Background technique [0002] Low-speed diesel engine usually refers to two-stroke low-speed diesel engine. As the core of large ship power system, its reliability, safety and economy are extremely important. How to improve its reliability, economy and safety through fault diagnosis and reduce the direct or indirect economic loss caused by diesel engine failure has always been an important topic in the diesel engine industry. The current mainstream diagnostic methods include vibration detection, thermal parameter detection, speed detection, spectrum detection, ferrography detection, etc. However, based on the above detection methods, only the specific faults of diesel engines can be detected and judged, and it is impossible to carry out overall and systematic diagnosis of diesel engines. Judgment and prediction of heal...

AI Technical Summary

Problems solved by technology

The current mainstream diagnostic methods include vibration detection, thermal parameter detection, speed detection, spectrum detection, ferrography detection, etc. However, based on the above detection methods, only the specific faults of diesel engines can be detected and judged, and it is impossible to carry out overall and systematic diagnosis of diesel engines. Judgment and prediction of health status, and does not have the function of interacting with technicians on how to solve the fault. Technicians can only deal with the cause of diesel engine faults through experience

At the same time, this kind of equipment cannot provide corresponding spare parts information support for technicians, and it is difficult to quickly deal with some host failures in a short time

Images