Tunnel cracks are the main factors that cause damage and collapse of tunnel structures. How to detect tunnel cracks efficiently and avoid safety accidents caused by tunnel cracks effectively is a research hotspot at present. In order to meet the need for efficient detection of tunnel cracks, the tunnel crack detection method based on improved Retinex and deep learning is proposed in this paper. The tunnel crack images collected by optical imaging equipment are used to improve the contrast information of tunnel crack images using the image enhancement algorithm, and this image enhancement algorithm has the function of multi-scale Retinex decomposition with improved central filtering. An improved VGG19 network model is constructed to achieve efficient segmentation of tunnel crack images through deep learning methods and then form the segmented binary image. The Zhang–Suen fast parallel-thinning method is used to obtain the skeleton map of the single-layer pixel, and the length and width information of the tunnel cracks are obtained. The feasibility and effectiveness of the proposed method are verified by experiments. Compared with other methods in the literature, the maximum deviation in the length of the tunnel crack is about 5 mm, and the maximum deviation in the width of the tunnel crack is about 0.8 mm. The experimental results show that the proposed method has a shorter detection time and higher detection accuracy. The research results of this paper can provide a strong basis for the health evaluation of tunnels.

This article develops a new sensor that can detect projectiles in all-weather with high sensitivity and a large field of view. Two high-power line lasers are used to design an active photoelectric detection sensor with a fan-shaped detection plane. The size of the designed fan-shaped photoelectric detection receiving plane is the same as the luminous fan-shaped plane light source to make the two fan-shaped planes coincide with each other, forming an active detection screen. Based on the principle of active photoelectric detection sensor, a linear array photoelectric detector is selected, in which multiple unit p-i-n detectors are spliced together, and an amplifier processing circuit with low noise and high sensitivity is designed. Combined with the geometric structural features of the active detection screen, the radiation characteristics calculation model of the projectile in a fan-shaped detection plane is developed using a five-parameters bidirectional reflectance distribution function (BRDF). Finally, the total radiation intensity calculation function of the projectile’s surface is derived considering the influence of environmental factors and the output signal and signal-to-noise ratio (SNR) model of the active photoelectric detection sensor is set up. Comparative experiments under different environmental illuminations verify that the detection ability has been significantly improved in active photoelectric detection sensors.

To improve the detection ability of photoelectric detection targets under low-illumination conditions, based on the traditional infrared photoelectric detection targets, in this paper, we propose a design method for an infrared detection screen by using a double high-power line laser interactive layout auxiliary mode, and we form an active infrared photoelectric detection target. We then establish the calculations of the laser beam’s illumination and the emission power of the pulse laser as a projectile passes through the infrared detection screen. According to the relation of the thickness of the infrared detection screen, the time period over which the projectile passes through the infrared detection screen, and the projectile’s spatial position, we use the grid division method to establish the temporal- and spatial-domain echo power model and the output signal voltage function of the active infrared photoelectric detection target. Through calculations and experimental analysis, it is found that the echo power is reduced as the detection distance is increased, and the intensity of the echo power is not linear with the thickness of the detection screen or the length of the projectile in the temporal and spatial domains. The detection performance of the proposed active infrared photoelectric detection target is better than the traditional infrared photoelectric detection target, and it can be improved to a certain extent by increasing the laser emission power appropriately.

In order to scientifically evaluate the target damage effectiveness when warhead fragments formed by projectile explosion attack targets, this paper proposes a new method by using the multi-layer warhead fragments distribution division mechanism to study an evaluation and calculation model of target damage effectiveness under uncertain information of warhead fragments. On the basis of the spatial relationship between projectile explosion position and target, we first analyze the target damage rules based on the target’s own vulnerability characteristics. Then we use the fuzzy prior probability theory to establish the membership function of the target damage factor and an evaluation model of the target damage grade, and use the stochastic multi-criteria acceptability analysis method to obtain the evaluation index value of the target damage level. Finally, considering the ratio between the effective area of the warhead fragment group attacking target and the area of target itself and the effective number and area ratio of warhead fragments penetrating target, we give a numerical calculation method of target damage effectiveness. Through simulation and calculation, the results show that when the distance between the projectile explosion position and the target is less than 7 m and the coordinate interval of the projectile flight direction is −2.5 m to 2.5 m, the damage probability of warhead fragments to the target is greater than 75%. When the weight of the damage factor of the target changes, the damage effectiveness of the target also changes, and this result is in accordance with the actual experiment, which verifies the rationality of the proposed mathematical model.

Aiming to address the issue of assessing the effectiveness of target damage in air defense interception under projectile and target intersection, this paper proposes a novel target damage effectiveness assessment mathematical calculation method using an adaptive fuzzy neural network. The design and calculation methods introduce the target cabin’s damage weight factor, the dispersion error and coverage density and fire density of warhead fragment, and the ratio of the number of warhead fragments to the cross‐sectional area of the target as the primary damage factors, and we establish a new model for calculating the target damage efficiency using Takagi‐Sugeno adaptive fuzzy neural network with the multiple damage factors. In the designed model, we take the characteristic parameters of warhead fragments formed by the projectile explosion as the sample data and learn the mapping relationship between damage factors and damage effect expressed by the system of fuzzy rule. Combined with the vulnerability weight and damage factors of the target, the fuzzy rule system is applied to predict and calculate the damage probability and damage effectiveness. In addition, we use shot‐line technology to set up the intersection criterion between warhead fragments and target, analyze the coordinate relationship of the projectile explosion relative to the target based on the ground coordinate system, and derive the distribution density function of warhead fragment and research a calculation model for target damage probability with multiple vulnerable cabins. Finally, we use the established model to train, test, and calculate the data from the actual projectile and target intersection damage test and present the comparison results to other damage calculation methods. By calculation and comparative analysis, the results show the smaller the distance between projectile and target, as well as the smaller the average intersection angle, and the larger the weight coefficient of the warhead fragment covering the target cabin, the total target damage probability increases obviously. In the two experimental calculations, the target cabin with the largest weight coefficient was considered, and compared with the existing literature, the damage probability of the proposed calculation method was increased by 9.13% and 10.93%, respectively, and it is clear that the proposed target damage assessment method can effectively reflect the real target damage effectiveness in the state of projectile and target intersection.