Abstract: An inspection system for inspecting optical assemblies of a LiDAR which includes a transmitting optical assembly at a transmitting end and a receiving optical assembly at a receiving end. The inspection system includes: a detection laser and a detection probe. The detection laser is configured to emit a detection laser beam that passes through the transmitting optical assembly and/or the receiving optical assembly, and exits the LiDAR or is incident to the detection probe. The detection probe is configured to receive the detection laser beam or an echo of the detection laser beam after being reflected off an object, and convert it into an electrical detection signal. The inspection system further includes a signal processing unit that communicates with the detection probe to receive the electrical detection signal, and is configured to determine an operation state of the optical assemblies based on the electrical detection signal.

Abstract: Provided is a sensory quality evaluation method for tobacco and tobacco products using an electronic nose instrument. The electronic nose instrument includes a gas sensor array module, an automatic smoke sampling system, a computer control and data analysis system, and an automatic ignition device. These components are integrated in a test box to make the instrument be structure miniaturization and work automation. The large tobacco data is established, in which the relationship between the responses of gas sensor array and the brand labels and sensory quality index scores by testing a large number of standard cigarette samples. A cascade type of modular neural networks is proposed with revised activation function and new decision-making and quantification rules to simulate the smoking and evaluating process of the professional panel. The electronic nose instrument and method realize on-site detection, discrimination and quality score estimation of a large number of tobacco and tobacco products.

Abstract: Provided is a sensory quality evaluation method for tobacco and tobacco products using an electronic nose instrument. The electronic nose instrument includes a gas sensor array module, an automatic smoke sampling system, a computer control and data analysis system, and an automatic ignition device. These components are integrated in a test box to make the instrument be structure miniaturization and work automation. The large tobacco data is established, in which the relationship between the responses of gas sensor array and the brand labels and sensory quality index scores by testing a large number of standard cigarette samples. A cascade type of modular neural networks is proposed with revised activation function and new decision-making and quantification rules to simulate the smoking and evaluating process of the professional panel. The electronic nose instrument and method realize on-site detection, discrimination and quality score estimation of a large number of tobacco and tobacco products.