Conceptual design and evaluation of an ultrasonic system for bottled beverages’ quality measurement and control

Abstract

A conceptual design of an online ultrasonic system for bottled beverages’ quality control and monitoring is presented. The design consists of being able to measure ultrasound propagation velocities of beverages in each glass bottle without needing to know its diameter and wall thickness. This was achieved using simultaneously both ultrasound pulse/echo and thru-transmission signals. The ultrasound velocity is then correlated with the beverage’s, viscosity, which is an index of quality. The design also includes: (1) an online transducer alignment technique using a mechanism of frequency shift in spectrum of an ultrasonic pulse signal according to incident angle, and (2) a signal processing method using a slide window technique suitable for automatic separation and recognition of narrowly spaced pulse signals. Experiments were conducted to evaluate the design. Results of beverage viscosity/velocity correlation, frequency shift due to transducer alignment, and ultrasound velocity measurement in real bottles are reported.

Hybrid of multi-signal processing methods for detection of small objects in containers filled with beverages using ultrasound

“…Prospective devices include water jet and water apron coupling methods (Zhao, Basir, & Mittal, 2004a). Noncontact techniques such as laser ultrasound and air coupled transducers, also provide potentials for object detection in containers.…”

Contact and non-contact ultrasonic measurement in the food industry: a review

“…Zhao et al [70] used an ultrasonic contact measurement technique to monitor the quality of tomato and orange juices in a glass bottle. They used a transmission and pulse-echo technique to find the quality of the beverages based on the ultrasonic velocity and the shift of frequency.…”

Machine Vision for Detecting Defects in Liquid Bottles: An Industrial Application for Food and Packaging Sector

“…To ensure quality, various sensors, and deep learning methods are employed to inspect these bottles for liquid level, cap defects, label placement, external objects, and other parameters, effectively classifying them as either good or defective [47][48]. These include an Ultrasonic sensor for liquid-level inspection, a photoelectric sensor for cap inspection, and an electromagnetic sensor (radio) for barcode verification [49][50][51]. According to these studies (Table 1), related research has identified specific flaws in various parts of the bottle using image processing and electronic sensor techniques.…”