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Inspired by the basic theory of Fruit Fly Optimization Algorithm, in this paper, cat mapping was added to the original algorithm, and the individual distribution and evolution mechanism of fruit fly population were improved in order to increase the search speed and accuracy. The flowchart of the improved algorithm was drawn to show its procedure. Using classical test functions, simulation optimization results show that the improved algorithm has faster and more reliable optimization ability. The algorithm was then combined with sparse decomposition theory and used in processing fouling detection ultrasonic signals to verify the validity and practicability of the improved algorithm.

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Carbon monoxide (CO), as a dangerous emission gas, is easy to accumulate in the complex underground environment and poses a serious threat to the safety of miners. In this paper, a sensor using a quantum cascade laser with an excitation wavelength of 4.65 μm as the light source, and a compact multiple reflection cell with a light path length of 12 m is introduced to detect trace CO gas. The sensor adopts the long optical path differential absorption spectroscopy technique (LOP-DAST) and obtains minimum detection limit (MDL) of 108 ppbv by comparing the residual difference between the measured spectrum and the Voigt theoretical spectrum. As a comparison, the MDL of the proposed sensor was also estimated by Allan deviation; the minimum value of 61 ppbv is achieved while integration time is 40 s. The stability of the sensor can reach 2.1 × 10−3 during the 2 h experimental test and stability of 1.7 × 10−2 can still be achieved in a longer 12 h experimental test.

Oxidation-reduction potential (ORP) sensors would constitute a robust surveillance and control solution for aeration and external carbon dosing in wastewater biological treatment processes if a clear correlation exists between the ORP values and process variables (e.g., dissolved oxygen (DO), nitrate, and chemical oxygen demand (COD). In this study, ORP values and other water quality variables were analyzed, and principal component analysis (PCA) and analysis of variance were used to study the relationships between ORP and main reactive substances under anoxic conditions. Mathematical models were then established using multiple regression analysis. The results showed that under anoxic conditions, ORP was positively correlated with nitrate, DO, and COD and negatively correlated with ammonia nitrogen, phosphate, and pH. COD had a low correlation with the ORP value change. PCA showed that the mathematical model of ORP can be established by using DO, nitrate, and phosphate, for which the adjusted R² value was 0.7195. The numeric relationships among ORP, COD, and nitrate were clearly established and applied to control external carbon dosing. A precise and clear relationship between ORP and COD offers the possibility to substitute COD monitoring for process control.