CN-122018405-A - Software and hardware integrated intelligent central control system control method and related device

CN122018405ACN 122018405 ACN122018405 ACN 122018405ACN-122018405-A

Abstract

The application provides a control method and a control device of a software and hardware integrated intelligent central control system, which belong to the technical field of control, and comprise the steps of firstly loading a training flow template, determining corresponding equipment linkage rules in response to training scenes selected by users, generating a hardware reconfiguration instruction and an equipment control instruction at the same time, configuring a logic gate circuit in a driver based on the hardware reconfiguration instruction, instantiating a target hardware control interface uniquely matched with the training scenes on site, and finally outputting equipment control instructions to corresponding training equipment through the target hardware control interface, so that a plurality of training equipment execute accurate linkage operation according to preset time sequences. According to the application, the training scene requirements are directly mapped into the hardware circuit structure, so that the on-demand dynamic generation of the control interface is realized, and the time sequence precision and the instantaneity of the cooperative control of multiple devices are remarkably improved.

Inventors

LV BAO
YANG XI
XU YUANJI
SHEN ZHONGPING
XIAO WENQIANG
XU HONGJIE

Assignees

上海有间建筑科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260212

Claims (10)

1. The control method of the software and hardware integrated intelligent central control system is characterized in that the intelligent central control system comprises a controller, a driver and training equipment, and the method is executed by the controller and comprises the following steps of: Loading a training process template, wherein the training process template comprises equipment linkage rules corresponding to different training scenes; determining the corresponding equipment linkage rule in response to the training scene selected by the user, and generating a hardware reconstruction instruction and an equipment control instruction according to the equipment linkage rule; configuring logic gates in the driver based on the hardware reconfiguration instructions to generate a target hardware control interface that matches the training scenario; Outputting the equipment control instruction to the corresponding training equipment based on the target hardware control interface so as to enable the training equipment to execute linkage operation according to a preset time sequence.
2. The method of claim 1, wherein the logic gate circuit includes a plurality of virtual slots, wherein each virtual slot corresponds to a reconfigurable partition, and each virtual slot corresponds to one training scenario, the method further comprising: receiving concurrent selection of a first training scene and a second training scene by a user; Configuring a first target hardware control interface in a first virtual slot, and configuring a second target hardware control interface in a second virtual slot; And controlling a first training equipment group based on the first target hardware control interface, and controlling a second training equipment group based on the second target hardware control interface.
3. The control method of a software and hardware integrated intelligent central control system according to claim 2, wherein the method further comprises: Acquiring a historical operation sequence of the user, inputting the historical operation sequence into a neural network model, and determining a predicted training scene according to an output result of the neural network model; Acquiring prediction confidence, and configuring the logic gate circuit in the driver to generate the target hardware control interface matched with the prediction training scene based on the hardware reconstruction instruction corresponding to the prediction training scene before the user confirms selection when the prediction confidence exceeds a preset threshold; configuring candidate hardware control interfaces in the idle virtual slots; and if the user confirms that the selected training scene is the same as the predicted training scene, switching the candidate hardware control interface into an activated state.
4. The control method of a software and hardware integrated intelligent central control system according to claim 3, wherein obtaining a historical operation sequence of the user, inputting the historical operation sequence into a neural network model, and determining a predicted training scene according to an output result of the neural network model, comprises: determining a time sequence feature map based on the wiring operation sequence of the user on the operation panel of the training equipment, a knob adjusting angle curve, key pressing duration and equipment response state switching time; inputting the time sequence feature map into a space-time attention network, wherein the space-time attention network respectively determines the time dependent features of the operation event and the spatial correlation features of the equipment ports through a multi-head attention mechanism; performing feature intersection on the time-dependent features and the space-associated features, and outputting matching probability distribution of the current operation sequence and each candidate training scene; And determining the candidate training scene with the highest probability value in the matching probability distribution as the predicted training scene.
5. The method for controlling a software and hardware integrated intelligent central control system according to claim 4, wherein determining a time sequence feature map based on a wiring operation sequence of the user on an operation panel of the training device, a knob adjustment angle curve, a key pressing duration, and a device response state switching time comprises: acquiring a wiring terminal number and a plug event time stamp corresponding to the wiring operation sequence, acquiring a continuous voltage sampling sequence corresponding to the knob adjusting angle curve, acquiring a pulse width sequence corresponding to the key pressing duration, and acquiring a response delay time difference corresponding to the equipment response state switching moment; mapping the connection terminal number into a port space coordinate code, uniformly aligning the plug event time stamp, the continuous voltage sampling sequence, the pulse width sequence and the response delay time difference to the same clock domain, and generating a heterogeneous operation event stream; dividing the heterogeneous operation event stream into a slice sequence of equal time windows along a time axis, and determining dense feature vectors corresponding to different operation events in each time window; Stacking the dense feature vectors into three-dimensional tensors in time sequence to form the time sequence feature map, wherein three dimensions of the three-dimensional tensors are a time window index, an operation event category and a port space coordinate respectively.
6. The method for controlling a software and hardware integrated intelligent central control system according to claim 5, wherein the time series feature map is input to a spatiotemporal attention network, and wherein the spatiotemporal attention network determines the spatial correlation feature of the time dependent feature of the operation event and the device port through a multi-head attention mechanism, respectively, and the method comprises the following steps: Dividing the time series feature map into a plurality of time heads along a dimension of the time window index, wherein each time head determines a corresponding time self-attention and determines the time dependent feature based on outputs of the plurality of time heads; Dividing the time series feature map into a plurality of spatial heads along a dimension of the port spatial coordinates, wherein each spatial head determines a corresponding spatial self-attention and determines the spatial correlation feature based on outputs of the plurality of spatial heads.
7. The method for controlling a software and hardware integrated intelligent central control system according to claim 6, wherein the step of performing feature intersection on the time-dependent feature and the space-dependent feature and outputting a matching probability distribution of a current operation sequence and each candidate training scene comprises the steps of: Performing attention calculation by taking the time-dependent features as queries and the space-dependent features as key values based on a cross attention mechanism to obtain fusion features; and determining matching probability distribution of the current operation sequence and a plurality of candidate training scenes based on the fusion characteristics.
8. A software and hardware integrated intelligent central control system, the intelligent central control system comprising a controller, a driver, and a training device, the system configured to: Loading a training process template, wherein the training process template comprises equipment linkage rules corresponding to different training scenes; determining the corresponding equipment linkage rule in response to the training scene selected by the user, and generating a hardware reconstruction instruction and an equipment control instruction according to the equipment linkage rule; configuring logic gates in the driver based on the hardware reconfiguration instructions to generate a target hardware control interface that matches the training scenario; Outputting the equipment control instruction to the corresponding training equipment based on the target hardware control interface so as to enable the training equipment to execute linkage operation according to a preset time sequence.
9. An electronic device, the electronic device comprising: At least one processor; And a memory communicatively coupled to at least one of the processors; Wherein the memory stores instructions executable by at least one of the processors, the instructions being executable by at least one of the processors to enable the at least one of the processors to perform a software and hardware integrated intelligent central control system control method as set forth in any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, implements a software and hardware integrated intelligent central control system control method as set forth in any one of claims 1-7.

Description

Software and hardware integrated intelligent central control system control method and related device Technical Field The application relates to the technical field of control, in particular to a control method and a related device of a software and hardware integrated intelligent central control system. Background In vocational education, industrial training and college experimental teaching, an intelligent central control system has become a core platform for integrally controlling a plurality of training devices. Typical training scenarios such as automobile engine fault diagnosis, industrial robot offline programming, aircraft maintenance simulation training, etc., often require a central control system to simultaneously drive multiple types of equipment such as simulators, oscilloscopes, signal generators, execution mechanisms, etc., and complete cooperative actions according to strict teaching logic time sequences. The prior central control system generally adopts a technical architecture of fixed hardware interfaces and software scheduling. The controller main board is pre-provided with a fixed number of general input/output pins, serial communication interfaces or analog output channels, and all training equipment needs to adapt to the electrical specifications and communication protocols of the fixed interfaces. When the multi-device linkage task needs to be executed, the controller runs embedded software, and sequentially sends instructions to each device through an operating system scheduling or interrupt service routine. The software layer approximately implements timing control through a timer chain, state machine, or real-time task orchestration. However, the multi-device linkage requires a strict time alignment relationship between control signals, and partial training scenes such as power-off detection of a high-voltage system, observation of engine oil injection timing, radar pulse triggering and the like require that timing deviation between multiple signals is controlled at microsecond or even nanosecond levels. Limited by operating system interrupt response jitter, bus contention delay, and instruction interpretation execution overhead, pure software schemes have difficulty guaranteeing such high precision synchronization requirements. Disclosure of Invention The embodiment of the application provides a control method and a related device of a software and hardware integrated intelligent central control system, which are used for solving the problems. In order to achieve the above purpose, the application adopts the following technical scheme: In a first aspect, the present application provides a control method of a software and hardware integrated intelligent central control system, where the intelligent central control system includes a controller, a driver, and a training device, and the method is executed by the controller, and includes: Loading a training process template, wherein the training process template comprises equipment linkage rules corresponding to different training scenes; Determining corresponding equipment linkage rules in response to training scenes selected by a user, and generating a hardware reconfiguration instruction and an equipment control instruction according to the equipment linkage rules; Configuring logic gates in the driver based on the hardware reconfiguration instructions to generate a target hardware control interface that matches the training scenario; and outputting equipment control instructions to corresponding training equipment based on the target hardware control interface so that the plurality of training equipment execute linkage operation according to a preset time sequence. With reference to the first aspect, optionally, the logic gate circuit includes a plurality of virtual slots, where each virtual slot corresponds to one reconfigurable partition, and each virtual slot corresponds to one training scenario, and the method further includes: receiving concurrent selection of a first training scene and a second training scene by a user; Configuring a first target hardware control interface in a first virtual slot, and configuring a second target hardware control interface in a second virtual slot; The first training device group is controlled based on the first target hardware control interface, and the second training device group is controlled based on the second target hardware control interface. With reference to the first aspect, the method optionally further includes: Acquiring a historical operation sequence of a user, inputting the historical operation sequence into a neural network model, and determining a predicted training scene according to an output result of the neural network model; acquiring prediction confidence, and when the prediction confidence exceeds a preset threshold, configuring a logic gate circuit in a driver based on a hardware reconstruction instruction corresponding to a prediction training scene to generate a t