Abstract:

Objective The evenness of combed sliver is an important indicator of combing quality, and its precise detection is an important foundation for achieving process optimization. Conventional detection methods mainly rely on manual sampling and offline analysis, which have problems such as serious detection lag. With the development of intelligent manufacturing technology, real-time dynamic detection and data analysis can be achieved through online detection, which provide real-time data support for process control. Therefore, conducting research on online detection technology for the uniformity of combed slivers is an important development direction for improving the intelligence level of combing machines.

Method A relationship model between sliver density and resonant cavity frequency was established based on the theory of microwave resonant cavity perturbation, before determining the key parameters of the resonant cavity of the microwave sensor and designing the appearance of the sensor. Subsequently, the sampling frequency was calculated and determined, and the theoretical correctness of the online detection system for combed slivers was preliminarily verified by simulating the changes in the dielectric constant inside the resonant cavity and comparing the theoretical values with the simulation values. An online testing platform for on-site testing was eventually established.

Results The simulation results showed that, at a resonant frequency of 10.4 GHz, the deviation between the simulated density and the theoretical density for different dielectric-constant inputs remained below 3%, confirming the accuracy of the proposed theoretical model. In order to further validate the method under practical production conditions, on-site experiments were conducted on a running combing machine. Data were repeatedly collected at 10.438, 10.440, 10.442 GHz and at combing speeds of 300, 350, 400 nips/min. Each data-collection run lasted at least 2 h, and an additional 24 h long-term stability test was performed to evaluate the robustness of the sensing system. The experimental results showed that the sliver CV values measured by the microwave sensor at different frequencies were within 3% of the corresponding values obtained using the Uster evenness tester. In addition, the density-variation trend derived from the microwave sensor closely matched the actual fluctuation pattern of the sliver during operation. This consistency indicates that the proposed system can accurately capture real-time sliver-density changes and provides reliable performance across different speeds and operating conditions. Overall, both simulation and experimental results demonstrate the feasibility and effectiveness of the microwave sensing system for online detection of sliver unevenness.

Conclusion A comprehensive model linking resonant frequency, output voltage, and sliver density was established based on resonant-cavity perturbation theory, forming a solid theoretical basis for the development of microwave-based sliver detection technologies. Both simulation analysis and on-site experiments demonstrated that the proposed system can achieve accurate real-time monitoring of sliver unevenness without altering the combing process or affecting machine operation, with measurement errors consistently maintained within 3%. The microwave sensor adopts a non-contact design that minimizes vibration-induced interference, making it well-suited for installation in high-speed textile machinery. In addition, the system features simple operation and modest hardware requirements for the data platform, thereby reducing overall implementation cost and facilitating large-scale industrial deployment.

Key words: combed sliver, evenness quality, online detection, microwave sensor, resonant cavity perturbation theory