Verification of algorithm for automatic detection of electronic devices mounted on waste printed circuit boards.

In this study, an algorithm for sorting waste products that is capable of automatically determining the value of raw materials during the sorting process is proposed. The algorithm automatically measures the sum of the top surface areas of integrated circuits (ICs), memory assemblies, and connectors (which account for over 80% of the resource value) from two-dimensional (2D) digital images of waste printed circuit boards. The sum of top surface areas is directly correlated with the total resource value. This algorithm continuously identifies the characteristics (e.g., color, size, and shape) of each device and performs relatively simple sequences of image processing. Tests on 46 types of waste digital-camera boards reveal the detection rates for ICs/memories and connectors to be 73% and 86%, respectively. The first measure is low because ICs/memories with long-side lengths of 2-5 mm are incorrectly identified as transistors or diodes in several cases. However, the proportion of ICs and memories with sides ≥5 mm is determined to be approximately 90% based on the sum of top surface areas, and the estimated values are 105% and 95% of the measured values, respectively. Furthermore, the sum of the top surface areas of both ICs and connectors is 101%. This reveals that the resource values can be estimated with a certain degree of accuracy. The analysis of cases of false detection and non-detection enable the identification of the major factors causing non-identification. The use of machine learning algorithms is determined to be an effective countermeasure. Furthermore, mitigation methods are specified.Implications: An automatic detection algorism of electric devices mounted on waste printed circuit boards was constructed to straightforwardly and rapidly evaluate the resource values of printed circuit boards in small waste home appliances. A program developed based on the algorithm automatically measures the sum of the top surface areas of ICs/memory and connectors, which account for over 80% of the resource value of mounted devices. Because the structure of the algorithm is simple and can be applied to multiple target devices, high-speed processing can be achieved when implementing a waste product sorter.

Constructing an automatic object-recognition algorithm using labeling information for efficient recycling of WEEE.

In an attempt to select an efficient recycling process for waste electrical and electronic equipment based on the value of individual products, we are engaged in the development of an automatic object-recognition system for discarded equipment. As part of this initiative, we developed a new object-recognition algorithm that uses the information from the labels on the bottoms of digital cameras discarded in Japan, which have a relatively high value. In addition, we created a program that can continuously process multiple two-dimensional digital images of the bottoms of the discarded cameras. The algorithm developed consists of the following: 1. Identifying the manufacturer using template matching with the manufacturer's logo on the label as a template image; 2. reading the model name located close to the logo using optical character recognition (OCR) processing; and 3. extracting the model-name candidates via a similarity calculation between the result of the OCR and the model-name list. After analyzing the information on the label of the discarded cameras, we carried out an object-recognition test using the images captured inside a photography box. The results demonstrated that on average, 48% of the total number of template images was necessary to identify all the manufacturers. This value varies from manufacturer to manufacturer; however, the template image with the "highest versatility" correctly matched 42% of the models of a certain manufacturer. The model-name identification for each manufacturer was successful 92% of the time on average, which indicated the effectiveness of this algorithm and emphasized the necessity of extracting the model-name candidates from the OCR result. Finally, assuming that a continuous process will be feasible in the future, a test was carried out using the photographed images of the discarded cameras moving on a conveyor belt at a speed of 0.5 m/s. The results demonstrated that the percentage of the number of template images required to identify the manufacturer was almost identical to that for static images. Notwithstanding the limitations of the image resolution (58% lower than that of the still images), the model-name identification rate was 81%.

Development of dispersed-type sonophotocatalytic process using piezoelectric effect caused by ultrasonic resonance.

Recently, degradation of persistent organic pollutants (POPs) with low biodegradability in the environment and in industrial and municipal wastewaters has gained importance. In this study, a dispersed-type sonophotocatalysis (SP) process, which is a combination of sonolysis and photocatalysis with dispersed light sources, has been proposed for the effective and energy-efficient degradation of POPs. In this method, the piezoelectric effect caused by ultrasonic resonance in a piezoelectric element is used for producing luminescence in a LED. A luminescent device composed of eight UV-LEDs and a piezoelectric element was designed for dispersion of UV light in water; this device was confirmed to show luminescence under ultrasonic irradiation. Sonophotocatalytic degradation experiments were carried out using several such devices, and the results were compared with those obtained in sonolysis, photocatalysis, and fixed-type SP. The comparison showed that the degradation rate constants in fixed-type and dispersed-type SP were larger than the sum of the rate constants obtained for sonolysis and photocatalysis; further, the synergetic effect caused by the combination of sonolysis and photocatalysis was 7.5% and 18% in fixed-type and dispersed-type SP, respectively.

Improvement in sonochemical degradation of 4-chlorophenol by combined use of Fenton-like reagents.

Studies on the sonolysis of a wide range of organic compounds have demonstrated that ultrasonic irradiation has potential for decomposition of organic pollutants in hazardous wastewater. However, the ultrasonic irradiation alone cannot provide high enough rate of decomposition to be used practically. One of the solutions to increase the degradation efficiency is to combine the ultrasound application with other advanced chemical oxidation processes (AOPs). In this study, in order to increase the efficiency of ultrasonically assisted degradation of organic pollutants in water, we examined effects of three kinds of solid Fe-containing catalysts, namely iron powder, basic oxygen furnace (BOF) slag and mill scale on the degradation rate of 4-CP (4-chlorophenol) in aqueous solutions containing hydrogen peroxide. In the experiments, 4-CP was considered as a model organic compound. All three Fe-containing matters when react with hydrogen peroxide are involved in the Fenton-like reaction system, which is one of the promising AOPs. The results showed that both the iron powder and mill scale additions can accelerate the degradation of 4-CP, although the effect is dependent on the solution pH. All 4-CP could be decomposed for 2 min at pH=3 and for 1h at pH=5.6. On the other hand, the BOF slag had no catalysis effect on the 4-CP degradation because of higher concentration of calcium and lower concentration of iron.