2results about How to "Improve resilience" patented technology

A biological agent packing material, its preparation method, and its reactor for the simultaneous removal of ammonia nitrogen and nitrate are disclosed. The steps include: sludge enrichment and acclimatization, preparation of biological agent, preparation of steel slag and coal gangue micro-packing material, and biofilm formation. The reactor includes, from top to bottom, steel slag and coal gangue microporous packing material, porous aeration plates, guide plates, a support layer, a microporous aeration system, and filter plates. A backwash valve is installed at the bottom of the reactor, and the flow rate is controlled by a backwash water tank through a backwash flow meter. Backwashing is achieved by an inlet pump pumping water in conjunction with the porous aeration plates. An exhaust port is provided at the top of the reactor, and the water discharged through the outlet enters a sedimentation tank for sedimentation and drainage. The steel slag and coal gangue microporous packing material used in this invention simultaneously removes ammonia nitrogen and nitrate under the driving action of iron circulation. The preparation process is simple, suitable for domestic sewage and industrial wastewater, and features no secondary pollution, high biological activity, low cost, and simple operation and management. It has significant effects in the simultaneous removal of ammonia nitrogen and nitrate.

This invention discloses an anti-skid navigation control method for agricultural machinery based on historical driver data, comprising: S1, collecting operational data of the driver operating the agricultural machinery on slippery road sections, using the Pearson correlation coefficient method to screen key dependent variables affecting steering control, and constructing training samples; S2, constructing an attention-BP-LSTM neural network regression prediction model for desired wheel angle and steering wheel torque; S3, model training; S4, evaluating and verifying the model's prediction results; S5, deploying the model on the terminal controller of the agricultural machinery to acquire real-time operational data of the agricultural machinery. When slippage is detected, the model outputs the desired wheel angle and steering wheel torque, and, combined with the safety protection mechanism of output limiting and gradual control, automatically adjusts the steering mechanism of the agricultural machinery to control the agricultural machinery to escape slippage. This invention generates precise and real-time control commands through deep learning of the driver's historical sideslip correction data, solving the problems of traditional methods relying on physical models and lacking experience utilization.