hardware circuit
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Analog circuit design requires large amounts of human knowledge. A special case of circuit design is the synthesis of robust and failure-resilient electronics. Evolutionary algorithms can aid designers in exploring topologies with new properties. Here, we show how to encode a circuit topology with an upper-triangular incident matrix and use the NSGA-II algorithm to find computational circuits that are robust to component failure. Techniques for robustness evaluation and evolutionary algorithm guidances are described. As a result, we evolve square root and natural logarithm computational circuits that are robust to high-impedance or short-circuit malfunction of an arbitrary rectifying diode. We confirm the simulation results by hardware circuit implementation and measurements. We think that our research will inspire further searches for failure-resilient topologies.

According to the reliability requirement of the Flight Control Computer for Unmanned Aerial Vehicle (UAV), a design scheme is proposed to ensure its reliability by using tri-redundancy technology. Further, by selecting appropriate redundant mode and the architecture model of the triple redundant flight control computer is established in this paper. The multi-channel security level method can give full play to the error tolerance ability of the system and improve the fault tolerance performance of the aircraft. After an extensive analysis and study of the structure of each module, the hardware circuit and software flow chart of the key technologies, such as redundancy strategy and synchronization method are suggested. A channel selection method based on channel security level is proposed. Combined with the comparison technology between channels, the selection of the optimal safe channel is realized.

Purpose As the infrastructure of the railway, the rail could sink or deform to different degrees due to the impact of train operation or the geological changing force for years, which will lead to the possibility that the facilities on both sides of the rail invade the rail clearance and bring hidden dangers to the safe operation of the train. The purpose of this paper is to design the gauge to measure the clearance parameters of rail. Design/methodology/approach Aiming at the problem, the gauge for clearance measurement was designed based on a combination measurement method in this paper. It consists of the measurement box and the rail measurement vehicle, which integrates a laser displacement sensor, inclination sensor, gauge sensor and mileage sensor. The measurement box was placed outside the rail vehicle. Through the design of a hardware circuit and software system, the movement measurement of the clearance parameters was realized. Findings In this paper, the measurement equations of horizontal distance and vertical height were established, the optimal solutions of the structural parameters in the equations were obtained by Levenberg–Marquardt method, then the parameter calibration problem was also solved. Originality/value The gauge has high precision; its measurement uncertainty reaches 1.27 mm. The gauge has manual and automatic working modes, which are convenient to operate and have practical popularization value.

The unreliability of traceability information on agricultural inputs has become one of the main factors hindering the development of traceability systems. At present, the major detection techniques of agricultural inputs were residue chemical detection at the postproduction stage. In this paper, a new detection method based on sensors and artificial intelligence algorithm was proposed in the detection of the commonly agricultural inputs in Agastache rugosa cultivation. An agricultural input monitoring platform including software system and hardware circuit was designed and built. A model called stacked sparse denoising autoencoder-hierarchical extreme learning machine-softmax (SSDA-HELM-SOFTMAX) was put forward to achieve accurate and real-time prediction of agricultural input varieties. The experiments showed that the combination of sensors and discriminant model could accurately classify different agricultural inputs. The accuracy of SSDA-HELM-SOFTMAX reached 97.08%, which was 4.08%, 1.78%, and 1.58% higher than a traditional BP neural network, DBN-SOFTMAX, and SAE-SOFTMAX models, respectively. Therefore, the method proposed in this paper was proved to be effective, accurate, and feasible and will provide a new online detection way of agricultural inputs.

Abstract Aiming at the problem of motion instability caused by the climbing of intelligent vehicles in the process of warehouse transportation, a design of intelligent variable speed warehouse transport vehicle system was proposed. STM32F103C8T6 single-chip microcomputer is used as the core controller of the intelligent variable speed car. The hardware circuit of the system is composed of power module, servo motor module, ultrasonic sensor module, infrared sensor module, MPU6050 gyroscope, motor drive and other modules. At the same time, the software test of vehicle downhill intelligent transportation, tracking detection speed and differential steering conditions is completed. Finally, the performance of the car is verified, and the results show that the smart car has achieved high stability of avoidance tracking, speed and other key functions. It is a downhill process, which has a lot of practical value.

Abstract With the increasingly serious aging of our society, labor shortage will seriously hinder the development of social economy. Robots gradually integrate into human production and life, and gradually serve more and more people. In order to solve the problem of large path deviation of the transmission system in the food conveying path, an intelligent food conveying system based on machine vision is proposed. The hardware circuit of the whole system is composed of image acquisition module, power module, electric drive module, etc. in the software part, the vertical volume matching method is used to set the optimal path. Through practical investigation, the scheme is feasible, can rely on the actual intelligence of catering distribution, has good application and promotion value.

Abstract Grain is the material basis of human existence and development. Food quality has an important effect on people’s physical health for our country. Moisture content of grain has been an important factor in affecting food quaility. Every year, a substantial part of the food production is lost because of too much water contained in the food without drying. According to the annual statistics of the country’s harvest, loss of food due to drying time caused by water take up 500 - 10000000 tons, according to approximate 1.5% - 3% of the total grain output.With the development of science and technology, grain moisture detection, especially the real-time and accurate detection, has attracted more and more purchase, production, processing, storage, transportation, and attention from various aspects. Under this problem context, hardware-circuit-control system of grain moisture detection based on ATmega128 has been investigated and designed.

In the process of complex product design, modeling in different fields and different disciplines is often involved. Designers often face many different development kits, platforms, and theories, among which significant differences exist. Especially in the process of algorithm-hardware implementation, it is necessary to have mastery of the knowledge including algorithm, hardware, circuit, and system engineering. In this paper, a modeling method of algorithm-hardware based on SysML is proposed to reduce the difficulty of algorithm-hardware modeling. By using the method, the designers who do not know the knowledge of hardware can also easily build the algorithm-hardware model. In this method, a method of graphical system modeling based on SysML is used, where the elements of the algorithm-hardware model are described by SysML graphical models. Then, the SysML graphical models are converted to Very-High-Speed Integrated Circuit Hardware Description Language. At last, a detecting algorithm of random number is complemented by the modeling method in this paper and the simulation results are presented at the conclusion.