The purpose of this paper is to design a multi-sensor-based overload storage test system for evaluating, monitoring and diagnosing the performance of propellant charges in solid rocket motors during operation.
First, the authors used KFEL-2-120 strain gauges (KYOWA, Japan) and JF-2050 ICP accelerometers (LN, China) as sensors and designed the overall system architecture using an FPGA controller. They implemented key modules within the system, including strain signal conditioning circuits, acceleration signal conditioning circuits, A/D conversion modules, data storage modules and the mechanical housing structure. Next, they tested the core functionalities of the system, specifically the signal conditioning modules and data storage modules. Finally, the authors validated the system’s reliability and accuracy through static strain calibration and air cannon overload testing.
The system reliably conditions, acquires, stores and outputs significant strain and overload acceleration signals. It achieves linearized output within a strain range of 2% to 35%, with a relative error of less than 1%. During air cannon overload testing, the system successfully captured overload accelerations up to 53 g, with a response time of approximately 6 ms and a signal duration of about 10 ms. The measurement results closely matched the theoretical analysis, meeting all measurement requirements.
This paper presents a design methodology for a multi-sensor-based overload storage test system. It demonstrates the system’s capability to reliably output both dynamic strain and acceleration signals under overload conditions, enabling real-time monitoring of solid propellant charge performance within solid rocket motors. Compared to traditional non-dynamic strain testing methods or single-sensor monitoring approaches, this integrated multi-sensor storage test system provides a novel solution for capturing transient, high-g acceleration synchronous with dynamic strain, which is critical for assessing propellant integrity under launch overloads. This research fills a gap in China’s domestic capabilities for real-time dynamic strain detection in this field.
