12results about How to "Achieve intelligence" patented technology

The invention discloses an intelligent tooling for paving a photovoltaic module and a control method thereof, the method is suitable for a robot end effector, and the method comprises the following steps: collecting three-dimensional space point cloud data of the photovoltaic module to generate pose information of the photovoltaic module, and controlling the end effector to carry out adaptive pose adjustment according to the pose information; the tooling is controlled to press down, and after it is judged that fitting is in place by monitoring the compression stroke of the suction cup, a vacuum adsorption instruction is started; the adsorption state is judged based on vacuum pressure change curve parallel monitoring and a dynamic balance algorithm, and a carrying permission signal is generated after a preset adsorption success condition is met; continuously carrying out anomaly detection in the carrying process, and if an anomaly is found, triggering a fault processing strategy; and releasing the negative pressure to place the photovoltaic module after the target position is reached, and rechecking the placement pose. Intelligent and self-adaptive picking and placing of the photovoltaic module by the tooling are realized, and the reliability, the safety and the automation level in the carrying process are improved.

This application relates to a monitoring intelligent processing method, apparatus, device, and medium based on transfer learning. The method includes: acquiring monitoring data via IoT communication connected to monitoring devices; preprocessing the data to obtain initial monitoring data; performing data analysis on the initial monitoring data to obtain labeled business segments and non-business segments; generating a decision scheme and executing the decision scheme when triggered, while sending the business segments and non-business segments to an integrated intelligent monitoring processing center; training an integrated model based on the business segments and non-business segments to obtain a target integrated model and target monitoring feature data; performing transfer learning based on the target monitoring feature data to generate multiple target lightweight models, and deploying these multiple target lightweight models to the connected devices. This application improves the intelligence and efficiency of monitoring intelligent processing, meets the requirements of real-time monitoring, and reduces the cost of monitoring video storage.

This utility model relates to a spiral propulsion type cooling device for filler material, including a filler pipe, coolers, and a spiral propulsion system. The filler pipe is used to transport filler material. Several coolers are present, with at least two coolers installed on the outer wall of the filler pipe along the filler material transport direction. The temperature of the coolers gradually decreases along the filler material transport direction. The coolers are used to cool the filler material in the filler pipe. The spiral propulsion system is installed in the filler pipe and is used to push the material through the filler pipe for transport. With the above configuration, multiple coolers work together to continuously cool the filler material in the filler pipe while it is being transported, resulting in good cooling effect, high efficiency, simple structure, convenient operation, and low cost.

The utility model relates to the technical field of air tightness testing, and discloses a heating tube air tightness testing device, which comprises a rack, an upper plate I is fixedly arranged in the rack, a heating tube is fixedly arranged above a heating tube base, and an air inlet tube is arranged in the heating tube base. The heating tube upper die is fixedly installed at the bottom of the first upper plate, the heating tube base is fixed between the heating tube upper die and the quick-change lower die base, the interior of the heating tube base is sealed, then the air inlet pipe is connected with an external high-precision airtight instrument, compressed air of 8 mpa to 12 mpa is injected, and the air inlet pipe is connected with the air inlet pipe through the external high-precision airtight instrument. After injection is conducted for one minute, pressure stabilization is stopped, whether the internal air pressure has a difference value or not is detected, if no difference value exists, it represents that the sealing performance is good, if the difference value exists, marking is conducted, follow-up processing is conducted, and therefore the effects of being simple in operation and improving the detection efficiency are achieved.

The application discloses an intelligent visual projection method and system suitable for optical imaging, wherein the system comprises a visual stimulation control module for setting a visual stimulation control signal; an image output module for generating full-spectrum visual stimulation and light intensity according to the visual stimulation control signal; a spectrum switching module for receiving the full-spectrum visual stimulation and the light intensity and outputting first specific spectrum visual stimulation; an infrared light source module for outputting infrared spectrum visual stimulation; a spectrum processing module for filtering preset green spectrum signals of the first specific spectrum visual stimulation and integrating the infrared spectrum visual stimulation to output second specific spectrum visual stimulation; and an image stimulation focusing module for fine-tuning the projection area and light intensity of the second specific spectrum visual stimulation and projecting the second specific spectrum visual stimulation to a visual tissue region. The application can solve the problem that the prior art cannot meet the research demand of visual neural optical signals and has the characteristics of intelligence, automation, precision and no optical pollution.

The application discloses a data-driven manufacturing system sustainability evaluation and improvement method, which belongs to the technical field of manufacturing system sustainability evaluation and improvement, and specifically comprises the following steps: S1, obtaining process yield and material consumption data, and constructing an environmental load rate based on the material consumption data and a preset energy value conversion rate database; S2, obtaining photoresist sensitivity and production cycle coincidence, and establishing a nonlinear coupling relationship model for representing the coupling relationship between the process yield and the environmental load rate; and establishing a sustainability index calculated from the energy value output rate and the environmental load rate; S3, constructing a digital twin model with controllable process parameters as input and outputting predicted process yield and predicted environmental load rate; and then solving the optimal process parameters for maximizing the sustainability index through a reinforcement learning decision engine, and generating a process recipe to realize closed-loop control. The application solves the problem that the traditional method cannot comprehensively evaluate multidimensional performance.

The application belongs to the field of simulation and is particularly related to a large language model role interaction system based on plot driving and tool calling, which comprises a role mapping module, a state library module, a plot evolution module, a scene behavior constraint module, a tool calling module and a conversation generation module. The role mapping module generates a language-characteristic feature set according to user input; the state library module initializes plot parameters according to the feature set; the plot evolution module drives plot logic based on a plot rule engine, dynamically generates a role behavior target, a tone strategy and a tool calling request or a random branch event; the scene behavior constraint module generates a behavior constraint rule set from a multi-scene behavior constraint rule library according to a scene identifier and a plot event; the tool calling module responds to the request and obtains a response result parameter of an external tool; and the conversation generation module integrates all the above information, drives a large language model to generate a coherent role conversation combined with a scene, an action and a tool. The application improves the personalization, coherence, scene adaptability and functional integration of role interaction.

The utility model discloses an induction type ceiling lamp which comprises an inductor, an installation disc, a diffusion ring, a back plate, a light source belt, a shell, a light source plate, a light-transmitting panel and a power source driver. A light source belt is laid around the edge of the upper surface of the light source plate; the light source plate with a light source belt is arranged at the bottom of the back plate; the light-transmitting panel is assembled in the shell and is positioned below the back plate in the shell; the diffusion ring is arranged on the upper surface of the back plate; a power supply driver and a sensor are assembled on the inner side of the mounting disc, and the mounting disc is fixedly connected with the back plate through a fastener; and the back plate is provided with a light outlet hole site. According to the utility model, the microwave sensor is adopted to control the work, the sensitivity is high, the detection distance is long, the influence of light, temperature and airflow is small, and the spatial position of a target and the movement of a human body can be detected in a larger spatial range, so that the lamp is controlled to be automatically turned on and turned off, intelligence and energy conservation are achieved, and the practicability and intelligence are remarkably improved.

The present application relates to the technical field of intelligent transportation and vehicle behavior prediction, in particular to a real-time trajectory prediction method for over-limit and over-load vehicles based on collaborative filtering, especially to a trajectory prediction method for over-limit and over-load vehicles, combining multi-dimensional behavior clustering and BiLSTM-Transformer hybrid model, introducing a DBSCAN clustering step based on multi-dimensional comprehensive similarity, which can automatically and accurately classify over-limit and over-load vehicles with similar behavior patterns into the same group. The most similar group is matched for the target vehicle for model training, effectively solving the problem of fuzzy model learning target caused by data heterogeneity. At the same time, the hybrid model architecture layer is good at capturing local time series dynamics and short-term driving rules, while the self-attention mechanism of the encoder can effectively model global long-distance dependence and complex trajectory patterns, and the two complement each other, thus achieving a leap in prediction accuracy as a whole. The algorithm can automatically identify noise points, further enhancing the robustness of the method to data noise.

The application belongs to the technical field of intelligent manufacturing and production scheduling, and particularly relates to an LLM and reinforcement learning method and system for AGV flexible workshop scheduling, which comprises the following steps: (1) multi-objective cooperative initialization: initial solutions with advantages in maximum completion time and total energy consumption are generated to form an initial population; (2) multi-objective search guided by LLM: the distribution state of the population in the multi-objective space is analyzed by a large language model, and the crossover and mutation strategies are dynamically adjusted to guide the population to approach the Pareto optimal frontier; (3) multi-objective local search driven by Q-learning: based on the Pareto level and target value of the current solution, an energy-saving neighborhood operation is adaptively selected by Q-learning for local optimization; (4) multi-objective feedback and population cooperation: the multi-objective performance indicators of the population are monitored in real time, the LLM guidance strategy and the Q-learning exploration rate are dynamically adjusted according to the feedback, and the convergence and diversity of the population are maintained.

This invention discloses a wire winding machine and method for winding steel wire around high-strength concrete pipe cores. The invention uses two winding reels to clamp and position the wire-winding component. A drive motor rotates the positioned winding reels and the wire-winding component, while a wire-releasing mechanism releases the wire, enabling the wire winding machine to wind the component. Simultaneously, under the operation of a wire sensor and an automatic control device, the winding process is monitored in real time, achieving intelligent and automated monitoring of the wire winding machine. Furthermore, the cooperation between the guiding mechanism and the wire-releasing mechanism improves the transmission of the wire during release, enhancing the tension of the wire and maintaining appropriate tension during transmission. The guide plate also restricts the range of motion of the wire, thereby improving the winding effect on the outside of the component.

The invention relates to the technical field of three-dimensional modeling, and discloses a knowledge graph-driven automatic evolution type factory component three-dimensional modeling system, which comprises the following modules: a ternary fusion knowledge graph construction module used for integrating component physical attributes, connection rules and semantic constraints; the GCN self-inference engine module is used for realizing automatic relation inference of an unknown component combination; the community co-evolution module is used for supporting a user to contribute a new component and completing verification updating; the alliance chain evidence storage and right and interest guarantee module is used for guaranteeing data security and knowledge contribution rights and interests; and the standardized interface module is used for realizing seamless integration with industrial software. According to the technical scheme, multi-dimensional attributes and constraints of components are integrated through the ternary fusion knowledge graph, automatic reasoning of unknown component combination relations is achieved in combination with a GCN self-reasoning engine, the intelligent and precise effect of component three-dimensional modeling is achieved, and the problems that it is difficult to adapt to novel component combinations, and assembly logic recognition is inaccurate are solved.