Multi-channel piezoelectric 3D printing nozzle fault identification and status monitoring system and method

Abstract

Disclosed are a fault identification and state monitoring system and method for a multi-channel piezoelectric 3D printing spray head. The system comprises a spray head driving circuit, a multi-channel gating circuit, a piezoelectric signal acquisition circuit and a monitoring unit. The spray head driving circuit is used for providing a driving signal to enable a piezoelectric spray head to perform spraying; the multi-channel gating circuit is used for providing a multi-channel in-turn gating signal to realize in-turn monitoring of a plurality of spray holes of the piezoelectric spray head; the piezoelectric signal acquisition circuit uses a self-sensing detection method to acquire a residual vibration signal in a runner cavity of the piezoelectric spray head; and the monitoring unit comprises a driving voltage monitoring module, a liquid viscosity monitoring module, an ink supply pressure monitoring module and a liquid drop spray speed calculation module, and is used for monitoring the working state of the piezoelectric spray head. The system and method can effectively identify the type and cause of a fault, improve monitoring accuracy and facilitate a user in taking effective measures; no external sensor is required; in-turn monitoring reduces the hardware cost; and monitoring can be performed during a working process of a spray head, and the monitoring flexibility is improved.

Description

technical field [0001] The invention belongs to the field of advanced manufacturing technology, and in particular relates to a multi-channel piezoelectric 3D printing nozzle fault identification and state monitoring system and method. Background technique [0002] 3D printing is a revolutionary manufacturing method that has been developed since the mid-1990s. Based on the principle of material accumulation molding, starting from the 3D CAD model of the part, the model is discretized, sliced ​​and layered, and then the 2D data is manufactured layer by layer and finally accumulated into a 3D entity to realize the workpiece molding manufacturing. Droplet jetting technology is widely used in 3D printing. However, because the nozzle is a precision device, it is very easy to cause jetting failures such as driving voltage overrun, high-viscosity plugging, and ink supply pressure imbalance. Currently, such failures can only be detected under ink viewing equipment. It was found that...

AI Technical Summary

Problems solved by technology

[0004] (1) Suncheonhyang University in South Korea uses the self-induction method of the piezoelectric nozzle to extract the residual vibration signal in the nozzle flow channel cavity for analysis, and uses the variance algorithm to detect the nozzle injection state. This method realizes injection failure through a single algorithm characteristic parameter Monitoring, for the overlap and aliasing of characteristic parameters under some injection faults, the fault type cannot be effectively identified, and the droplet velocity cannot be monitored;

[0005] (2) Hangzhou Dianzi University uses a CCD high-speed camera to collect images of ink droplet ejection, and uses the region growth method to extract the ink droplet shape and calculate the speed and volume of the ink droplet. This method can only detect the nozzle at a specific position. The process is cumbersome

[0006] The above methods have the following problems: the specific fault type cannot be effectively identified, which is not conducive to taking corresponding measures; the detection can only be performed at a fixed position, which affects the detection efficiency

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