Automatic ammunition feeding and ramming failure on-line monitoring and prediction method

Abstract

The invention relates to an automatic ammunition feeding and ramming failure on-line monitoring and prediction method. Sensors are mounted at key parts, namely, an ammunition feeding machine, a coordinator and an ammunition ramming machine of a cannon ammunition feeding and ramming system and correspondingly monitor abrasion losses of a driving chain wheel and a driven chain wheel, a rotation angle of a coordination arm, pressure of a small balancing machine and displacement of a cartridge. Measured parameters are reflected to a computer system; parameter state monitoring is carried out; thresholds are set for the abrasion losses of the driving chain wheel and the driven chain wheel; according to angles of the coordination arm and the small balancing machine and a gas-liquid quantity relation, an alarm device is arranged to implement failure early warning; a threshold is set for the displacement of the cartridge on the ammunition ramming machine; and alarming is conducted and corresponding maintenance measures are taken. Data are guided into a failure prediction platform through a monitoring system, and a grey prediction model method is adopted to predict variations of the abrasionlosses and the displacement of the cartridge, so that the effects that a failure is found in advance and the failures of clamping stagnation and poor ammunition feeding and ramming are solved in advance are realized.

Description

technical field [0001] The invention belongs to the fault monitoring and prediction technology of a bomb feeding system, and relates to a fault monitoring and predicting method for wear amount of a sprocket and a roller of a bomb feeding device of a certain type of large-caliber artillery and a gas-liquid amount of a coordinator balancer. Background technique [0002] The automatic ammunition feeding and feeding system of the artillery is a subsystem with a high failure rate on the artillery. Due to its complex process, multiple mechanisms are required to match each other to achieve an accurate feeding and feeding process. Any failure of any mechanism will cause the ammunition feeding system to fail. Abnormal bomb feed. Therefore, it is very important for the normal operation and maintenance of the ammunition supply system to accurately study the cause of the failure of the ammunition delivery system, monitor and suppress potential failures from the root cause to achieve con...

AI Technical Summary

Problems solved by technology

[0003] In order to study the health status of the bomb supply system, vibration signal measurement is currently used to monitor and evaluate the health status of the bomb supply system. The vibration parameters of the elastic system can be comprehensively monitored, but accurate prediction cannot be achieved in terms of fault diagnosis and prediction, and the vibration signal has large noise interference, which needs to be denoised by signal processing methods such as wavelet transform, resulting in large errors in results. , it is difficult to establish the relationship between the vibration signal and the specific fault based on the vibration signal, so the real-time diagnosis and prediction effect of the fault is not obvious

Images