6 results about "Fuzzy identification" patented technology

The invention relates to the technical field of intelligent adjustment of audio equipment, and discloses a system for automatically adjusting loudspeaker volume and sound effect according to wind sound volume, which comprises a wind noise acquisition module, an audio processing module, a main control module and a loudspeaker module, and is characterized in that the modules are sequentially in signal transmission connection. The loudspeaker volume and the sound effect type are dynamically adjusted according to the wind noise level, the wind noise is not counteracted to retain environment sound perception, and the problems that an existing noise reduction scheme is not real, influences safety and is not adaptive to the wind noise adjustment sound effect are solved. According to the invention, the wind noise acquisition module adopts a loudspeaker periphery distributed microphone layout, and captures a wind noise and environmental noise mixed signal near a loudspeaker at 360 degrees, thereby avoiding irrelevant noise interference; the audio processing module separates and recognizes the wind noise through a special DSP algorithm, and accurately judges the wind noise level by combining with the comparison of a wind noise feature database, thereby providing a reliable basis for adjustment, and overcoming the defects of inaccurate collection and fuzzy recognition of traditional equipment.

The invention belongs to the technical field of sensors, and discloses a seat self-adaptive system sensor which is characterized in that when an upper-layer film semi-finished product or a lower-layer film semi-finished product generates elastic deformation, output end wires corresponding to the upper-layer film semi-finished product and the lower-layer film semi-finished product are in a loop state; the upper-layer film semi-finished product and the lower-layer film semi-finished product respectively have quantitative resistance values which are reduced along with the increase of the mutual contact area of the upper-layer film semi-finished product and the lower-layer film semi-finished product, and data are transmitted to an external controller. The induction contacts are relatively independent, the creep phenomenon of continuous resistance change under constant external force can be eliminated through the exhaust hole layer, and accurate data can be rapidly and stably output; a flexible circuit structure is adopted and is flexibly laid in each area according to the shape of the seat. The problems of fuzzy recognition, coverage limitation, crosstalk, serious creep and the like of existing similar sensors can be effectively solved, and the use experience with higher science and technology and comfort is brought to users.

The application discloses a kind of weak stratum receding type section grouting intelligent fuzzy identification and control method and system, comprising the following steps: in the process of grouting, real-time acquisition grouting pressure, grouting flow and pull tube displacement data;According to fixed section length, the grouting process is divided, and the grouting parameters of each section are calculated;With grouting parameters as features, a three-level fuzzy inference system is used to identify weak strata;According to the identification result, the grouting parameters are adjusted adaptively, and the grouting is continued until the standard condition is reached;After grouting is completed, a three-level grouting effect evaluation system of point, line and body is constructed to evaluate the grouting effect.The application realizes real-time acquisition of grouting parameters, combined with hierarchical fuzzy judgment, to identify the weak characteristics of strata and the grouting state in real time, and uses the identification result as a closed-loop control decision, to adaptively optimize the section grouting parameters during construction, and to ensure stable and reliable reinforcement effect.Through the evaluation system, the improvement effect of single point, single tube and overall strata is graded.

This invention provides a method and system for fusion of ore and rock attributes in implicit modeling of polymetallic ore bodies. The method includes: collecting multi-source heterogeneous data of complex polymetallic associated ore deposits and preprocessing the multi-source heterogeneous data; constructing an ore and rock type classification model based on a random forest algorithm; inputting the preprocessed multi-source heterogeneous data into the pre-trained ore and rock type classification model; calculating the Gini importance index of each attribute data in the multi-source heterogeneous data; identifying attribute data with a Gini importance index greater than a first threshold as core attribute data; inputting the core attribute data into a pre-trained fusion network to obtain a comprehensive ore and rock evaluation index; using a fuzzy C-means clustering algorithm to perform three-dimensional spatial clustering of the comprehensive ore and rock evaluation index, outputting spatial confidence scores, and determining ore and rock transition zones based on the spatial confidence scores. This invention enables high-precision fusion of multi-source heterogeneous data and fuzzy identification and confidence quantification of ore and rock transition zones.

The application discloses a tower crane bolt axial force intelligent ultrasonic detection method and system based on multi-modal data fusion. First, a multi-level influence factor system is constructed based on fuzzy hierarchy comprehensive evaluation theory, and a high-risk area identification model is established. Based on the model, the regional risk value is calculated, and the monitoring distribution scheme is determined. In the selected area, a heterogeneous network composed of fiber Bragg grating strain sensors and ultrasonic sensors is arranged, and strain and ultrasonic data are synchronously collected. The multi-modal data are input into a deep belief network for feature fusion, and dynamic evaluation of the health state is realized through a fuzzy recognition model. Based on the dynamic grading evaluation result, an improved rain flow counting method and cumulative damage theory are used for fatigue life prediction. Finally, data fusion display and intelligent early warning are realized through a remote monitoring platform. The application realizes intelligent health management of the whole chain from risk identification, real-time monitoring to life prediction.

The invention relates to the technical field of printed circuit boards, in particular to an AI statistical method, device and equipment for printed circuit board assembly process parameters, and the method comprises the steps: converting a received original bill of materials into a target format text with semantic information reserved by using a document conversion service; identifying metadata in the target format text by using an AI semantic understanding and reasoning model, positioning the position of effective data corresponding to the metadata, obtaining the effective data based on position identification, and storing the effective data to a structured standard file based on semantic mapping; on the basis of the structured standard file and the pin calculation rule template, performing fuzzy recognition by using an AI semantic understanding and reasoning model, and calculating to obtain welding pin data; and calculating mounting point data based on the welding pin data and the mounting process rule base. Therefore, the problems that in the prior art, a technological parameter calculation method is low in applicability, BOM file content recognition accuracy is low, and parameter calculation accuracy is low can be effectively solved.