30 results about "Data driven algorithms" patented technology

The invention discloses an integral modeling and optimal control integrated method of a solar lithium bromide refrigeration unit, comprising: determining input variables; reconstructing the input variables; determining output variables of the overall modeling; determining internal operating parameter optimization variables and external processes Control variables; determine the objective function for the optimization of the internal operating parameters of the solar lithium bromide refrigeration unit and the external process control variables; send the optimal internal operating parameters to the control system of the solar lithium bromide refrigeration unit for operation, and issue the optimal external process variables to the two The controller of the control loop, the controller uses a data-driven PID algorithm to quickly track the optimal external process variable value. It effectively solves the technical problems of difficult modeling, optimization and control of the solar lithium bromide refrigeration unit, enables the solar lithium bromide refrigeration unit to operate in the optimal parameter and high-efficiency area under different working conditions and loads, and effectively improves the solar lithium bromide refrigeration unit. Cooling efficiency and safety stability.

The invention relates to a multi-shaft motion control method based on data driving and parameter mixing optimization. According to the method, a data driving algorithm and a parameter mixing optimization algorithm are established and debugged in a PC host computer, and motion control codes which can be identified by a multi-shaft motion controller end of a lower computer are generated by a compiling module and an operation module of the host computer; an operation state of a motor side is detected by a photoelectric encoder, a detection result is taken as a feedback signal which is transmitted to a multi-shaft motion controller, the feedback signal is compared with an expected position input signal to acquire a position error signal, the position error signal is taken as input of an MFAC control algorithm, and an outer-most layer position control ring of a motor driving system is constructed. Through a multi-shaft motion control method based on a data driving theory, no specific controlled system mathematic model is required, the input and output data information is only required to design a controller of a controlled system, and influence of unmodeled dynamics on a multi-motor driving system and dependence on the system are solved.

The invention belongs to the technical field of convexity prediction, and in particular relates to a board convexity prediction method based on kernel partial least squares combined with a support vector machine, comprising the following steps: S1, using a high-precision monitoring device to collect on-site data; S2, collecting the collected Data preprocessing; S3, establishment of KPLS regression prediction model; S4, establishment of KPLS-SVM plate convexity prediction model. In the present invention, the data-driven algorithm is used as a mathematical tool, and abnormal values ​​can be removed from a large amount of collected on-site rolling process data. The present invention establishes a continuous strip rolling strip convexity prediction model based on the kernel-partial least squares method combined with the support vector machine, The prediction of the crown of the strip continuous rolling is realized, and the invention adopts the particle swarm optimization algorithm to optimize the built model, and further improves the prediction accuracy of the strip continuous rolling crown. The invention is used for the prediction of the crown of the continuous rolling strip.

The invention relates to a method for estimating passenger flow between bus stops based on IC card data. The method determines the passenger's travel route and boarding station according to the IC card data and the bus GPS station report data, and then infers the passenger's alighting station. Obtain the complete OD information of passenger travel, calculate the OD amount according to the complete OD information, redistribute the missing passenger flow at the drop-off site using the site attraction weight, and use the redistributed passenger flow to correct the OD amount of the complete OD information. , and calculate the number of people getting on and off at the station and the passenger capacity between the stations through the corrected OD amount. Compared with the prior art, the passenger flow estimation method provided by the present invention is based on pure data driving, the algorithm has wide applicability and high accuracy, and can intuitively grasp the bus passenger flow and operation and service conditions.

The invention provides a method and a device for adaptively calibrating transmitting power in a radio frequency front-end module based on a data driving algorithm for a wireless communication system.By converting a transmitting power calibration problem into a dynamic linearized model, the design of a control system is simplified. Compared with other power calibration methods, the calibration algorithm provided by the invention eliminates a modeling step, does not need to establish an accurate system model, and only needs input / output (I / O) measurement data of the system. Related experimentalresults show that by using the proposed calibration algorithm and device based on data driving, the transmitting power error of the device can be reduced from 1.5 dB to 0.25 dB or less.

The present invention provides a multi-scale concurrent simulation method for composite materials, which includes the following steps: Step S1: Construct the constitutive phase materials of each component phase of the composite material through a data-driven algorithm; Step S2: Perform adaptive cluster analysis for the constitutive model, Multi-scale concurrent computing of composite materials is realized through adaptive cluster analysis. Adaptive cluster analysis includes online and offline stages. Through the offline stage, RVE is divided into clusters based on strain concentration tensors and the interaction between clusters is solved. The tensor component adjusts the stiffness of the reference material through self-adaptive iterative adjustment in the online stage, and combines the material constitutive model of each component phase to obtain the cluster stress-strain distribution. The invention also provides a composite material multi-scale concurrent simulation system. The invention does not need to introduce any empirical material model when performing multi-scale analysis on the composite material, omits the cumbersome parameter calibration process, and is more convenient to apply.

The invention relates to the technical field of heating and air-conditioning equipment, in particular to a method and system for controlling the variable return water temperature of an air source heat pump based on supply and demand matching. Building model; according to the measured data of air source heat pump operation, state identification parameters are introduced to distinguish the start-up stage and stable operation stage, and a unit model that can reflect the dynamic process and loss of start-up and shutdown is established through data-driven algorithms; the end model considering the dynamic thermal process is established and considered The transmission and distribution model of the waterway inertia; the dynamic coupling relationship between the unit heating capacity, the terminal heat supply and the building heat dissipation is used to form the dynamic model of the air source heat pump system; according to the indoor thermal comfort requirements of the target system, the variable return water temperature control strategy is established , and control the unit operation according to the variable return difference water temperature control strategy during operation. The invention improves the problem of frequent start and stop of the air source heat pump unit under low load state, improves the system performance, reduces the power consumption of the system, reduces the influence of noise during the start and stop process, and helps to prolong the life of the compressor.

The present invention provides a fully-shielded pedestrian tracking method based on a hybrid system. According to the pedestrian movement features and pedestrian features required learning in the tracking, a corresponding tracking model and an identification model are constructed, when pedestrians are not shielded, the tracking model learns pedestrian features while tracking the pedestrians, the shielded pedestrians are sensed through the sensing condition of the model transition result and the tracking model is switched to the identification model when the pedestrians are shielded; the identification model utilizes the learned pedestrian features to continuously identify pedestrians with tracking loss from the detection result according to the identification condition of the model transition rule; and when the identification model identifies the pedestrians with tracking loss, and the states of tracking pedestrians are reset through the reset condition of the model transition rule and the is identification model switched to the tracking model for going on tracking so as to realize pedestrian tracking in the full shielding condition. The design is reasonable, the model driving and the data driving algorithm employ the idea of the hybrid system to perform integration so as to solve the actual problem so as to greatly improve the tracking accuracy and success rate.