This article presents an active acoustic excitation method for leak detection of buried gas pipelines based on cavity resonance reflection. The principles of gas leakage in pipelines are analyzed, including the gas passage model and the gas cavity model. The principle of Helmholtz resonator is employed to establish the cavity model. For the cavity model, the relationships between cavity resonance frequency, acoustic impedance, sound pressure amplification, and leakage damage size are derived. The resonant effect of the gas cavity on the acoustic signal is considered in this study to solve the problem that the echo signal after long distance propagation and reflection becomes very weak. Numerical simulations are conducted to demonstrate the relationships between acoustic reflection coefficient of the leak hole size, cavity volume, and pipe wall thickness. In order to verify the effectiveness of the proposed method, a pipeline experimental rig with a length of 100 m is constructed. Sound waves are generated by a speaker and reflected echoes are received by a microphone. The cavity resonance reflection and echo characteristics of different leak hole size, different transmitting acoustic frequency, and different cavity volume are analyzed. The empirical mode decomposition (EMD) algorithm is used to decompose and reconstruct the echo signals to eliminate the noise interference in the pipeline system. An echo time-distance conversion method is used to visualize the locations of the leak hole and welds. Experimental results show that the proposed method can effectively detect the leak holes and welds in the pipeline.

Spodoptera frugiperda (J.E. Smith), fall armyworm (FAW), a polyphagous Noctuid pest, was first reported in Uganda in 2016. Farmers were trained to identify and manage the pest, but there was a lack of information on farmer knowledge, perceptions and practices deployed to control it. Therefore, we conducted a survey to assess maize farmers' knowledge, perceptions and management of the pest during the invasion. We interviewed 1,289 maize farmers from 10 maize-growing agro-ecological zones (AEZ) of Uganda using well-structured questionnaires. The data were analyzed using R version 4.2.3. The respondents faced many constraints, including pests, drought, poor soils and labor constraints. Among the pests, FAW was ranked by most (85%) of the respondents as the number one pest problem in maize, and some farmers reported having noticed it way back in 2014. By 2018, more than 90% of the farmers had seen or heard about FAW, and about 80% saw FAW in their fields. The most common FAW symptoms reported by maize farmers were windowing, near tunnel damage, and holes on the cobs. The developmental stages of FAW identified by farmers included eggs (10%), young larvae (78.7%), mature larvae (73.5%) and adult moths (6.7%). Insecticides were the major control tactic, although some farmers used plant extracts, hand-picking, sand, and ash. Farmers sourced information on FAW from various sources, including fellow farmers, radio/TV, extension agents, input dealers, print media, research and NGO extension. There is a need to package clear and uniform information for the farmers and to develop and promote a sustainable solution for FAW management, including harnessing biological control and cultural practices.