A non-extracting rotor detection control method and system

Abstract

The present invention provides a non-extracting rotor detection control method and system, which relates to the technical field of generator detection, and the method includes: obtaining the control instructions of the robot in real time, and at the same time, obtaining the motion data of the robot in real time through a preset sensor, and outputting the initial data; parsing the initial data to obtain the parsed data, and performing data analysis on the parsed data to obtain the target current data corresponding to the electromagnet set in the robot; based on the target current data, and in combination with the acquired time constant, determining the control data of the electromagnet, and outputting the electromagnet control data; based on the electromagnet control data, controlling the operating parameters of the electromagnet, synchronously outputting the control process data, evaluating the effect of the control process, outputting the control evaluation result, and optimizing the control process. The present invention can monitor the operating state of the robot in the generator in real time, and improve the operating efficiency and operating accuracy of the robot in the generator, so as to realize the precise control of the robot.

Description

Technical Field

[0001] The present invention relates to the technical field of generator detection, and in particular to a non-rotor detection control method and system. Background Art

[0002] The generator is an important part of the power system. In order to ensure that the generator can supply electricity stably, it is necessary to regularly inspect and maintain the magnetic circuit components of the generator.

[0003] At present, the common way to inspect generators is to pull out the rotor for manual inspection. This traditional maintenance mode has disadvantages such as long maintenance cycle, low detection efficiency, high work intensity, high cost, and certain risks of equipment disassembly and assembly. In recent years, a detection method without pulling out the rotor has emerged. By controlling the robot to move on the stator, the appearance images of the rotor and stator are obtained, and whether there is mechanical wear is determined based on the appearance images. However, the movement of the robot inside the generator requires the coordinated work of components including motors, tracks, electromagnets, etc., which is prone to inaccurate robot control, resulting in a high detection abnormality rate for detection without pulling out the rotor.

[0004] Therefore, the present invention provides a non-rotor detection control method and system. Summary of the invention

[0005] The present invention provides a non-extracted rotor detection control method and system, which are used to monitor the operating status of a robot in a generator in real time, improve the operating efficiency and accuracy of the robot in the generator, achieve precise control of the robot, and thereby ensure the robot's monitoring efficiency of the non-extracted rotor of the generator.

[0006] The present invention provides a non-extraction rotor detection control method, comprising:

[0007] Step 1: obtaining control instructions for controlling the robot in the generator in real time, and at the same time, obtaining the motion data of the robot in real time through a preset sensor set on the robot, and outputting initial data;

[0008] Step 2: parsing the initial data to obtain parsed data, and performing data analysis on the parsed data to obtain target current data corresponding to the electromagnet provided in the robot;

[0009] Step 3: Determine the control data of the electromagnet based on the target current data and in combination with the acquired time constant, and output the control data of the electromagnet;

[0010] Step 4: Based on the electromagnet control data, the operating parameters of the electromagnet are controlled, the control process data is output synchronously, and the effect of the control process is evaluated in combination with preset indicators, the control evaluation results are output, and the control process is optimized based on the control evaluation results.

[0011] Preferably, the real-time acquisition of control instructions for controlling the robot in the generator includes:

[0012] Acquire the control instructions being executed, completed, and to-be-executed by the robot in real time, and construct a control instruction set;

[0013] At the same time, the control instructions in the control instruction set are divided by time to obtain a control instruction subset corresponding to each moment, and a real-time control instruction subset corresponding to the current moment is output.

[0014] Preferably, the obtaining the motion data of the robot in real time through a preset sensor provided on the robot and outputting the initial data comprises:

[0015] Acquire monitoring demand information of the generator set in real time, and activate corresponding preset sensors on the robot based on the monitoring demand information;

[0016] The motion data of the robot at the current moment is acquired through the preset sensor, and the initial data is comprehensively output in combination with the control instruction.

[0017] Preferably, obtaining target current data corresponding to the electromagnet provided in the robot includes:

[0018] Determine the target motion range corresponding to the motion data according to the control instruction;

[0019] Comparing and analyzing the motion data with the corresponding target motion range to obtain a first comparison result;

[0020] The current data of the electromagnet provided in the robot at the current moment is obtained, the real-time current data is output, the preset result-current comparison table is combined, and the target current data of the electromagnet is determined based on the first comparison result and the real-time current data.

[0021] Preferably, the step of combining the preset result-current comparison table and determining the target current data of the electromagnet based on the first comparison result and the real-time current data includes:

[0022] Acquire current change data matching the first comparison result in the preset result-current comparison table, and output a first corresponding relationship between the first comparison result and the current change data;

[0023] Based on the first corresponding relationship and the first comparison result, the current adjustment data of the electromagnet is determined, and the real-time current data and the current adjustment data are analyzed in combination with a preset current adjustment algorithm to obtain the target current data.

[0024] Preferably, step 3 includes:

[0025] Selecting a first model matching the monitoring requirement information and a format requirement corresponding to the first model from a model database;

[0026] Selecting historical current data matching the monitoring requirement information from a historical database, performing format conversion on the matched historical current data based on the format requirement, and outputting the data to be divided;

[0027] Using a preset data partitioning method to partition the data to be partitioned, to obtain a training data set, a verification data set, and a test data set;

[0028] Training and optimizing the first model based on the training data set, the validation data set, and the test data set to obtain a prediction model;

[0029] Using a preset data analysis model to obtain a time constant corresponding to an inherent parameter of the generator;

[0030] Input the target current data, real-time current data and time constant at each moment into the prediction model for prediction analysis, obtain the predicted current at each moment, and output current prediction data;

[0031] At the same time, in combination with the current-voltage comparison table, the target voltage corresponding to the target current data is obtained, and the control data of the electromagnet to be selected is output;

[0032] Combining manual selection instructions and system self-selection instructions, selecting a scoring method that matches the monitoring demand information in the method database;

[0033] At the same time, combined with the preset requirement-method-indicator mapping table, the scoring indicators matching the scoring method are selected from the indicator database to construct a scoring indicator set;

[0034] Based on the scoring method and the scoring index set, the current prediction data and the selected electromagnet control data at each same moment are evaluated and analyzed, and a first evaluation result is output;

[0035] The first evaluation result is compared and analyzed with a preset target score, and the to-be-selected electromagnet control data corresponding to the comparison and analysis result that meets preset conditions is output as electromagnet control data.

[0036] Preferably, step 4 includes:

[0037] In combination with the preset data-instruction comparison table, an execution instruction matching the electromagnet control data is obtained in the instruction database, and an execution instruction set is constructed;

[0038] Based on the execution instruction set, corresponding operating parameters of the robot are controlled, and control process data is synchronously output;

[0039] Parsing the control process data to obtain first process data corresponding to the motion trajectory of the robot and second process data corresponding to the motion data of the robot;

[0040] At the same time, target process data corresponding to the electromagnet control data is acquired, and first target data corresponding to the first process data and second target data corresponding to the second process data are obtained by parsing;

[0041] Comparing and analyzing the first process data and the first target data to obtain a first result, and at the same time, comparing and analyzing the second process data and the second target data to obtain a second result;

[0042] Based on the first result and the second result, comprehensively output the real-time process data of the robot during the instruction execution process;

[0043] At the same time, a historical control process instruction matching the robot and historical data during the execution of the historical control process instruction are obtained from a historical database, and the historical process data is output;

[0044] Combined with the preset indicators selected from the indicator database, the real-time process data and the historical process data are evaluated and compared and analyzed, and the control evaluation results are output;

[0045]

[0046] in, Indicates the control evaluation results; Represents the total number of preset indicators used to evaluate the robot's motion trajectory; Indicates the total number of preset indicators used to evaluate the robot's motion data; represents the data offset of the robot motion trajectory data in the real-time process data under the i-th index; Represents the data offset of the robot motion trajectory data in the historical process data under the i-th index; represents the weight factor corresponding to the i-th indicator related to the robot's motion trajectory; represents the standard control parameter corresponding to the i-th indicator related to the robot motion trajectory; represents the exponential function; represents the error adjustment coefficient corresponding to the i-th indicator related to the robot motion trajectory; represents the data offset of the robot motion data in the real-time process data under the jth index; represents the data offset of the robot motion data in the historical process data under the jth index; represents the weight factor corresponding to the jth indicator related to the robot motion data; represents the standard control parameter corresponding to the jth indicator related to the robot motion data; represents the error adjustment coefficient corresponding to the jth indicator related to the robot motion data;

[0047] Combined with the preset result-correction comparison table, obtain the correction instruction matching the control evaluation result;

[0048] Based on the deviation correction instruction, the to-be-executed instruction of the robot is corrected to generate a correction instruction set, and the deviation correction feedback data is output synchronously, and the control process is optimized based on the deviation correction feedback data.

[0049] On the other hand, the present invention also provides a non-extraction rotor detection control system, comprising:

[0050] A data acquisition module, used to acquire control instructions for controlling the robot in the generator in real time, and at the same time, acquire the motion data of the robot in real time through a preset sensor set on the robot, and output initial data;

[0051] A data analysis module, used to analyze the initial data to obtain analysis data, and to perform data analysis on the analysis data to obtain target current data corresponding to the electromagnet provided in the robot;

[0052] A data analysis module, used for determining control data of the electromagnet based on the target current data and in combination with the acquired time constant, and outputting the control data of the electromagnet;

[0053] The process optimization module is used to control the operating parameters of the electromagnet based on the electromagnet control data, synchronously output the control process data, evaluate the effect of the control process in combination with preset indicators, output the control evaluation results, and optimize the control process based on the control evaluation results.

[0054] The present invention provides a non-extracting rotor detection control method and system. The present invention obtains control instructions and motion data in real time, determines the control data of the electromagnet in combination with the target current data and the time constant, controls the operating parameters of the electromagnet, evaluates the control effect and optimizes it, thereby realizing precise control of the robot movement. The present invention can not only accurately sense the robot's operating status by accurately acquiring the control instructions and operating data of the robot in the generator, but also facilitates precise control of the robot's subsequent motion process through the analysis results obtained through subsequent data analysis, improves the robot's operating efficiency and stability during the detection process, and reduces the probability of abnormalities in the robot during the detection of the generator, thereby ensuring the robot's monitoring efficiency of the generator set. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 It is a flow chart of a non-rotor extraction detection control method provided by an embodiment of the present invention;

[0057] Figure 2 It is a schematic diagram of the framework of a non-rotor detection control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] like Figure 1 As shown, an embodiment of the present invention provides a non-rotor detection control method, including:

[0060] Step 1: Acquire control instructions for controlling the robot in the generator in real time, and at the same time, acquire the motion data of the robot in real time through the preset sensors set on the robot, and output the initial data;

[0061] Step 2: parse the initial data to obtain parsed data, and perform data analysis on the parsed data to obtain target current data corresponding to the electromagnet set in the robot;

[0062] Step 3: Based on the target current data and in combination with the acquired time constant, the control data of the electromagnet is determined, and the control data of the electromagnet is output;

[0063] Step 4: Based on the electromagnet control data, control the operating parameters of the electromagnet, output the control process data synchronously, evaluate the effect of the control process in combination with preset indicators, output the control evaluation results, and optimize the control process based on the control evaluation results.

[0064] In this embodiment, control instructions: instructions for controlling the robot, including but not limited to robot movement instructions, robot stillness instructions and robot detection instructions;

[0065] In this embodiment, the preset sensor is a sensor for obtaining parameters of the surrounding environment, such as a gyroscope and an acceleration sensor, etc. Specifically, the speed data and acceleration data at the current moment can be obtained through the accelerometer, and at the same time, the direction of the robot can be determined according to the gyroscope to determine the direction of the speed, and the vibration data of the robot can be collected through the vibration sensor;

[0066] In this embodiment, motion data refers to the motion parameters of the robot, such as speed, acceleration, orientation, vibration amplitude, vibration frequency, and motion direction;

[0067] In this embodiment, the initial data: i.e., the comprehensive data including the control instructions and the motion data;

[0068] In this embodiment, parsed data refers to data obtained by parsing initial data;

[0069] In this embodiment, the target current data is the current data used to control the electromagnets provided in the robot;

[0070] In this embodiment, the time constant is a parameter related to factors such as the resistance and inductance of the coil and the Felice characteristics of the magnetic core, which can be obtained through the parameters of the robot or through experiments;

[0071] In this embodiment, the electromagnet control data is: data determined according to the target current data and the time constant of the electromagnet, and used to adjust the magnitude of the electromagnetic force between the electromagnet and the stator;

[0072] In this embodiment, the operating parameters are operating data used to control the electromagnets in the robot, which are generally voltage or current parameters;

[0073] In this embodiment, the control process data is composed of data collected during the control or adjustment of the operating parameters of the electromagnet;

[0074] In this embodiment, the preset indicators are indicators used to evaluate the control process, such as stability, sensitivity, etc.;

[0075] In this embodiment, the control evaluation result refers to the result obtained by evaluating the control process through preset indicators.

[0076] The implementation principle and beneficial effects of this embodiment: The present invention obtains control instructions and motion data in real time, determines the control data of the electromagnet in combination with the target current data and the time constant, controls the operating parameters of the electromagnet, evaluates the control effect and optimizes it, thereby achieving precise control of the robot's motion. The present invention can not only accurately sense the robot's operating status by accurately acquiring the control instructions and operating data of the robot in the generator, but also facilitates precise control of the robot's subsequent motion process through the analysis results obtained through subsequent data analysis, improves the robot's operating efficiency and stability during the detection process, and reduces the probability of abnormalities in the robot during the detection of the generator, thereby ensuring the robot's monitoring efficiency of the generator set.

[0077] An embodiment of the present invention provides a non-rotor detection control method for real-time acquisition of control instructions for controlling a robot in a generator, including:

[0078] Obtain the control instructions being executed, completed, and to-be-executed by the robot in real time, and build a control instruction set;

[0079] At the same time, the control instructions in the control instruction set are divided by time to obtain a control instruction subset corresponding to each moment, and a real-time control instruction subset corresponding to the current moment is output.

[0080] In this embodiment, the control instruction set is an instruction set including control instructions being executed, completed, and to be executed;

[0081] In this embodiment, the control instruction subset is a set of instructions corresponding to each moment obtained after time division;

[0082] In this embodiment, the real-time control instruction subset is a set of control instructions corresponding to the current moment.

[0083] The implementation principle and beneficial effects of this embodiment: The present invention obtains the control instructions of all stages of the robot that have been completed, are being executed, and are to be executed, so as to accurately sense the execution status of the robot's instructions. At the same time, the control instruction set of the robot corresponding to each moment is obtained through time division, which not only facilitates the precise control of the robot, but also provides data support for the subsequent optimization of the control process.

[0084] An embodiment of the present invention provides a non-extracted rotor detection control method, which obtains the robot's motion data in real time through a preset sensor set on the robot and outputs initial data, including:

[0085] Obtain monitoring demand information of the generator set in real time, and activate the corresponding preset sensors on the robot based on the monitoring demand information;

[0086] The robot's current motion data is obtained through preset sensors, and the initial data is output in combination with control instructions.

[0087] In this embodiment, the monitoring requirement information: that is, the monitoring requirements for the generator set, includes but is not limited to operating status monitoring, electrical parameter monitoring, etc., for example, the speed, temperature, vibration and other parameters of the generator to ensure that it operates within a normal range.

[0088] The implementation principle and beneficial effects of this embodiment: The present invention obtains the monitoring requirement information of the generator set in real time, and then can activate the corresponding preset sensors on the robot according to the monitoring requirements, so that the corresponding operating parameters in the generator can be obtained through the activated preset sensors. While meeting the monitoring requirement information, it can also reduce the mutual interference between sensors, thereby ensuring the accuracy of the monitoring data.

[0089] An embodiment of the present invention provides a non-rotor detection control method, which obtains target current data corresponding to an electromagnet set in a robot, including:

[0090] Determine the target motion range corresponding to the motion data according to the control instruction;

[0091] Comparing and analyzing the motion data with the corresponding target motion range to obtain a first comparison result;

[0092] The current data of the electromagnet set in the robot at the current moment is obtained, the real-time current data is output, the preset result-current comparison table is combined, and the target current data of the electromagnet is determined based on the first comparison result and the real-time current data.

[0093] In this embodiment, the target motion range includes but is not limited to a speed range, an acceleration range, and a vibration parameter range. For example, since the robot movement instruction has speed data, the speed range is generally determined according to the movement speed of the robot. For example, when the speed is 10 cm / s, the corresponding speed range should be: [9.5, 10.0], unit: centimeters per second;

[0094] In this embodiment, the first comparison result is a result obtained by analyzing the motion data and the target motion range, for example, comparing the motion data with the target range to determine whether the motion data is within the target range, and calculating the difference between the motion data and the target range when the motion data is not within the target range;

[0095] In this embodiment, the real-time current data refers to the current data in the electromagnet at the current moment;

[0096] In this embodiment, the preset result-current comparison table: a table containing the comparison relationship between the first comparison result and the target current data, is preset and used to determine the corresponding target current data according to the input first comparison result.

[0097] The implementation principle and beneficial effects of this embodiment: The present invention can utilize the comparative analysis of the target motion range and real-time data, combined with the preset result-current comparison table, to dynamically adjust the target current data of the electromagnet, and then through comparative analysis and data processing, it can intelligently determine the optimal target current data according to the situation of the motion data and the real-time state of the electromagnet, and realize accurate detection and control of the non-extracted rotor. By dynamically adjusting the target current data of the electromagnet, the present invention can quickly respond to the motion instructions of the robot and adjust the current of the electromagnet in time, so as to realize accurate control of the robot, thereby ensuring the stability and accuracy of the robot movement and monitoring process.

[0098] An embodiment of the present invention provides a non-rotor detection control method, which combines a preset result-current comparison table and determines the target current data of the electromagnet based on a first comparison result and real-time current data, including:

[0099] Acquire current change data matching the first comparison result in a preset result-current comparison table, and output a first corresponding relationship between the first comparison result and the current change data;

[0100] Based on the first corresponding relationship and the first comparison result, the current adjustment data of the electromagnet is determined, and the real-time current data and the current adjustment data are analyzed in combination with a preset current adjustment algorithm to obtain the target current data.

[0101] In this embodiment, the current change data: data obtained by combining the preset result-current comparison table to determine how the current needs to be adjusted according to different first comparison results;

[0102] In this embodiment, the first corresponding relationship: the first corresponding relationship may be a functional relationship, which is obtained by fitting the functional relationship according to the difference between any two historical current data collected before the current moment and the difference between the corresponding motion data. Optionally, the first corresponding relationship may also be a mapping relationship between the data in the corresponding table;

[0103] In this embodiment, the current adjustment data is used to adjust the current of the electromagnet to achieve the desired target state;

[0104] In this embodiment, a current adjustment algorithm is preset: used to adjust the current of the electromagnet according to the real-time current data and the current adjustment data to achieve adjustment of the target current data, for example, a PID control algorithm, a fuzzy control algorithm, and a neural network control algorithm.

[0105] The implementation principle and beneficial effects of this embodiment: The present invention dynamically adjusts the current of the electromagnet by combining the first comparison result and the real-time current data through the preset result-current comparison table and the current adjustment algorithm, and then determines the final target current data by analyzing the real-time current data and the current adjustment data, thereby realizing precise control of the electromagnet. The present invention determines the target current data through the first comparison result and the real-time current data, and can accurately adjust the target current data, thereby accurately controlling the electromagnetic force of the electromagnet and improving the accuracy of the robot control.

[0106] An embodiment of the present invention provides a non-rotor detection control method, in step 3, comprising:

[0107] Selecting a first model matching the monitoring requirement information and a format requirement corresponding to the first model from a model database;

[0108] Select historical current data matching the monitoring requirement information from the historical database, perform format conversion on the matched historical current data based on the format requirement, and output the data to be divided;

[0109] The data to be divided is divided by using a preset data division method to obtain a training data set, a verification data set and a test data set;

[0110] Training and optimizing the first model based on the training data set, the validation data set, and the test data set to obtain a prediction model;

[0111] Using a preset data analysis model to obtain a time constant corresponding to an inherent parameter of the generator;

[0112] Input the target current data, real-time current data and time constant at each moment into the prediction model for prediction analysis, obtain the predicted current at each moment, and output the current prediction data;

[0113] At the same time, combined with the current-voltage comparison table, the target voltage corresponding to the target current data is obtained, and the control data of the electromagnet to be selected is output;

[0114] Combining manual selection instructions and system self-selection instructions, a scoring method matching the monitoring demand information is selected from the method database;

[0115] At the same time, combined with the preset requirement-method-indicator mapping table, the scoring indicators matching the scoring method are selected from the indicator database to construct a scoring indicator set;

[0116] Based on the scoring method and the scoring index set, the current prediction data and the selected electromagnet control data at each same moment are evaluated and analyzed, and a first evaluation result is output;

[0117] The first evaluation result is compared and analyzed with the preset target score, and the selected electromagnet control data corresponding to the comparison and analysis result that meets the preset conditions is output as the electromagnet control data.

[0118] In this embodiment, the model database: that is, a database storing a variety of data analysis models;

[0119] In this embodiment, the first model is a model selected from the model database and matched with the monitoring requirement information;

[0120] In this embodiment, the format requirement refers to the requirement of the data format of the data to be processed when the first model performs data analysis;

[0121] In this embodiment, the historical database: a database storing historical current data, used to provide a record of the current of the robot over a period of time in the past;

[0122] In this embodiment, historical current data: current data of the robot recorded in the past period of time;

[0123] In this embodiment, data to be divided: data to be divided after format conversion, used for subsequent training, verification and testing;

[0124] In this embodiment, the preset data partitioning method is a method for partitioning the data to be partitioned into a training data set, a validation data set, and a test data set, so as to be used for training and optimizing the first model;

[0125] In this embodiment, the training data set, the validation data set and the test data set are data sets used to train, validate and test the first model;

[0126] In this embodiment, the prediction model: a model trained and optimized based on the training data set, the validation data set and the test data set is used to predict the current data;

[0127] In this embodiment, the preset data analysis model is: a model for obtaining a time constant corresponding to the inherent parameters of the generator;

[0128] In this embodiment, inherent parameters: specific parameters inherent to the generator, such as resistance, inductance, etc.;

[0129] In this embodiment, the predicted current is a current prediction value obtained by the prediction model. For example, the current at each time can be calculated according to the following formula:

[0130]

[0131] Where t is time, is the current at time t, that is, the predicted current corresponding to each moment, is the target current data, is the current data at the current moment, represents the time constant, is the base of natural logarithms, and its value is approximately equal to 2.71828;

[0132] In this embodiment, the current prediction data includes the data of the predicted current at each moment, which is used for subsequent analysis and control;

[0133] In this embodiment, the current-voltage comparison table: a table or rule containing the corresponding relationship between target current data and target voltage;

[0134] In this embodiment, target voltage: a desired voltage value determined according to target current data and a current-voltage comparison table;

[0135] In this embodiment, the electromagnet control data to be selected is obtained based on the evaluation analysis and the comparative analysis, and the control parameters to be selected and determined. Specifically, the electromagnet control data to be selected may be the input voltage, which is calculated based on the target current data and the coil resistance.

[0136] In this embodiment, the manual selection instruction: that is, the selection instruction input manually, is used to select a suitable scoring method in the method database;

[0137] In this embodiment, the system self-selection instruction: that is, the instruction automatically selected by the system, used to select a scoring method in the method database in combination with the manual selection instruction;

[0138] In this embodiment, method database: a database storing various scoring methods;

[0139] In this embodiment, the scoring method is a method for evaluating the current prediction data and the selected electromagnet control data, for example, the scoring can be performed by calculating the time length for the current to reach 90% of the value of the target current data, and when the scoring fails, the voltage is increased, that is, the target current data value is increased to the second target current data, and when the value reaches 90% of the original target current data, the voltage is reduced so as to be adjusted to the original target current data;

[0140] In this embodiment, the preset requirement-method-indicator mapping table: a pre-set table or rule containing the mapping relationship between monitoring requirements, scoring methods, and scoring indicators;

[0141] In this embodiment, the scoring indicator set: a scoring indicator set selected according to a preset requirement-method-indicator mapping table;

[0142] In this embodiment, the first evaluation result is the result obtained by evaluating and analyzing the current prediction data and the electromagnetic control data to be selected at each same moment based on the scoring index set and the scoring method;

[0143] In this embodiment, preset target score: a preset target score value used to evaluate and compare evaluation results;

[0144] In this embodiment, preset condition: a pre-set condition used to determine whether the first evaluation result meets the preset requirement, for example, when the first evaluation result reaches the preset target score, the electromagnet control data to be selected is determined to be the electromagnet control data.

[0145] The implementation principle and beneficial effects of this embodiment: The present invention realizes the prediction and control of the robot current through the data and preset model in the historical database, combined with the data partitioning method and the prediction model. The evaluation analysis and scoring method can help determine the optimal electromagnet control data, thereby realizing the precise control of the robot. The present invention realizes the precise control of the electromagnet through the prediction model and evaluation analysis, realizes the real-time monitoring and response of the generator through the prediction of current data and evaluation analysis, reduces the possibility of failure, and optimizes the electromagnet control data through the scoring method and indicator set to meet the control requirements under different working conditions and improve the stability and adaptability of the robot.

[0146] An embodiment of the present invention provides a non-rotor detection control method, in step 4, comprising:

[0147] Combined with the preset data-command comparison table, the execution instructions matching the electromagnet control data are obtained in the instruction database, and an execution instruction set is constructed;

[0148] Based on the execution instruction set, the corresponding operating parameters of the robot are controlled and the control process data is output synchronously;

[0149] The control process data is parsed to obtain first process data corresponding to the motion trajectory of the robot and second process data corresponding to the motion data of the robot;

[0150] At the same time, target process data corresponding to the electromagnet control data is acquired, and first target data corresponding to the first process data and second target data corresponding to the second process data are obtained by parsing;

[0151] Comparing and analyzing the first process data and the first target data to obtain a first result, and at the same time, comparing and analyzing the second process data and the second target data to obtain a second result;

[0152] Based on the first result and the second result, comprehensively output the real-time process data of the robot during the instruction execution process;

[0153] At the same time, the historical control process instructions matching the robot and the historical data during the execution of the historical control process instructions are obtained from the historical database, and the historical process data is output;

[0154] Combined with the preset indicators selected in the indicator database, the real-time process data and historical process data are evaluated and compared, and the control evaluation results are output;

[0155]

[0156] in, Indicates the control evaluation results; Represents the total number of preset indicators used to evaluate the robot's motion trajectory; Indicates the total number of preset indicators used to evaluate the robot's motion data; Represents the data offset of the robot motion trajectory data in the real-time process data under the i-th index; Represents the data offset of the robot motion trajectory data in the historical process data under the i-th index; represents the weight factor corresponding to the i-th indicator related to the robot's motion trajectory; represents the standard control parameter corresponding to the i-th indicator related to the robot motion trajectory; represents the exponential function; represents the error adjustment coefficient corresponding to the i-th indicator related to the robot motion trajectory; Represents the data offset of the robot motion data in the real-time process data under the jth index; Represents the data offset of the robot motion data in the historical process data under the jth index; represents the weight factor corresponding to the jth indicator related to the robot motion data; represents the standard control parameter corresponding to the jth indicator related to the robot motion data; represents the error adjustment coefficient corresponding to the jth indicator related to the robot motion data;

[0157] Combine the preset result-correction comparison table to obtain the correction instructions that match the control evaluation results;

[0158] Based on the deviation correction instructions, the robot's pending instructions are corrected, a correction instruction set is generated, and the deviation correction feedback data is output synchronously. Based on the deviation correction feedback data, the control process is optimized.

[0159] In this embodiment, the preset data-instruction comparison table: that is, a table containing the comparison relationship between the electromagnet control data and the execution instructions, is preset;

[0160] In this embodiment, the instruction database: a database storing various execution instructions;

[0161] In this embodiment, the execution instruction: the instruction matched according to the electromagnet control data is used to control the robot operation parameters;

[0162] In this embodiment, execution instruction set: an instruction set constructed by matching execution instructions;

[0163] In this embodiment, control process data refers to data generated during the process of controlling the robot based on the execution instructions;

[0164] In this embodiment, the first process data: that is, the process data corresponding to the motion trajectory of the robot;

[0165] In this embodiment, the second process data: that is, process data corresponding to the motion data of the robot, for example, velocity process data, acceleration process data, etc.;

[0166] In this embodiment, target process data: target data corresponding to the electromagnet control data;

[0167] In this embodiment, the first target data: target data corresponding to the first process data;

[0168] In this embodiment, the second target data: target data corresponding to the second process data;

[0169] In this embodiment, the first result is the result obtained by comparing and analyzing the robot motion trajectory data, which can reflect the performance of the robot's motion trajectory during the execution of instructions;

[0170] In this embodiment, the second result is the result obtained by comparing and analyzing the robot's motion data, which can reflect the robot's motion data performance during the execution of instructions;

[0171] In this embodiment, real-time process data refers to data generated in real time during the robot's execution of instructions, which is used to monitor and evaluate the robot's motion state in real time;

[0172] In this embodiment, historical control process instructions: that is, the records and historical data of instructions executed by the robot in the past period of time;

[0173] In this embodiment, the historical process data: includes the historical control process instructions of the robot in the past period of time and the summary of the data generated during the execution of the historical control process instructions, which is used to analyze and compare the historical motion states of the robot;

[0174] In this embodiment, preset indicators: a set of indicators for evaluating the robot's motion trajectory and motion data performance is preset;

[0175] In this embodiment, the control evaluation result: is an evaluation result obtained based on the comparative analysis of the real-time process data and the historical process data, and is used to characterize the state performance of the robot during the execution of the instruction;

[0176] In this embodiment, the preset result-correction comparison table: that is, a comparison table or rule containing the mapping relationship between the control evaluation results and the correction instructions;

[0177] In this embodiment, the deviation correction instruction: an instruction obtained by matching the control evaluation result, used to correct the execution instruction of the robot;

[0178] In this embodiment, the correction instruction set: is a new instruction set generated after the correction instruction processing, and is used to optimize the control process of the robot;

[0179] In this embodiment, the deviation correction feedback data refers to the feedback data generated during the deviation correction process and is used to evaluate the deviation correction effect and continue to optimize the control process.

[0180] The implementation principle and beneficial effects of this embodiment: The present invention controls the robot's operating parameters by executing an instruction set, obtains real-time data and historical data, evaluates and analyzes the robot's motion trajectory and motion data, and calculates according to preset indicators and weights to obtain a control evaluation result, and then obtains a correction instruction based on the evaluation result, corrects the robot's execution instructions, and optimizes the control process. The present invention realizes real-time optimization of the robot's operating parameters through comparative analysis of real-time data and historical data, and realizes precise control of the robot's motion trajectory and motion data through comparative analysis and indicator weight calculation. At the same time, the correction instruction is obtained according to the control evaluation result, and the robot's execution instructions are automatically corrected, thereby improving the stability and efficiency of the system.

[0181] like Figure 2 As shown, an embodiment of the present invention provides a non-extraction rotor detection control system, including:

[0182] A data acquisition module is used to acquire control instructions for controlling the robot in the generator in real time, and at the same time, acquire the motion data of the robot in real time through preset sensors set on the robot, and output initial data;

[0183] A data analysis module is used to analyze the initial data to obtain analysis data, and to analyze the analysis data to obtain target current data corresponding to the electromagnets set in the robot;

[0184] A data analysis module, used for determining control data of the electromagnet based on the target current data and in combination with the acquired time constant, and outputting the control data of the electromagnet;

[0185] The process optimization module is used to control the operating parameters of the electromagnet based on the electromagnet control data, synchronously output the control process data, evaluate the effect of the control process in combination with preset indicators, output the control evaluation results, and optimize the control process based on the control evaluation results.

[0186] The implementation principle and beneficial effects of this embodiment: The present invention obtains control instructions and motion data in real time, determines the control data of the electromagnet in combination with the target current data and the time constant, controls the operating parameters of the electromagnet, evaluates the control effect and optimizes it, thereby achieving precise control of the robot's motion. The present invention can not only accurately sense the robot's operating status by accurately acquiring the control instructions and operating data of the robot in the generator, but also facilitates precise control of the robot's subsequent motion process through the analysis results obtained through subsequent data analysis, improves the robot's operating efficiency and stability during the detection process, and reduces the probability of abnormalities in the robot during the detection of the generator, thereby ensuring the robot's monitoring efficiency of the generator set.

[0187] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A non-extracting rotor detection control method, characterized in that: include: Step 1: obtaining control instructions for controlling the robot in the generator in real time, and at the same time, obtaining the motion data of the robot in real time through a preset sensor set on the robot, and outputting initial data; Step 2: parsing the initial data to obtain parsed data, and performing data analysis on the parsed data to obtain target current data corresponding to the electromagnet provided in the robot; Step 3: Determine the control data of the electromagnet based on the target current data and in combination with the acquired time constant, and output the control data of the electromagnet; Step 4: Based on the electromagnet control data, the operating parameters of the electromagnet are controlled, the control process data is output synchronously, and the effect of the control process is evaluated in combination with preset indicators, the control evaluation result is output, and the control process is optimized based on the control evaluation result; Wherein, the real-time acquisition of the motion data of the robot by a preset sensor provided on the robot and the output of the initial data include: Acquire monitoring demand information of the generator set in real time, and activate corresponding preset sensors on the robot based on the monitoring demand information; Acquire the motion data of the robot at the current moment through the preset sensor, and output the initial data in combination with the control instruction; Wherein, obtaining target current data corresponding to the electromagnet provided in the robot includes: Determine the target motion range corresponding to the motion data according to the control instruction; Comparing and analyzing the motion data with the corresponding target motion range to obtain a first comparison result; Obtaining the current data of the electromagnet provided in the robot at the current moment, outputting the real-time current data, combining the preset result-current comparison table, and determining the target current data of the electromagnet based on the first comparison result and the real-time current data; The step of combining the preset result-current comparison table and determining the target current data of the electromagnet based on the first comparison result and the real-time current data includes: Acquire current change data matching the first comparison result in the preset result-current comparison table, and output a first corresponding relationship between the first comparison result and the current change data; Based on the first corresponding relationship and the first comparison result, determine the current adjustment data of the electromagnet, and analyze the real-time current data and the current adjustment data in combination with a preset current adjustment algorithm to obtain the target current data; Wherein, step 3 includes: Selecting a first model matching the monitoring requirement information and a format requirement corresponding to the first model from a model database; Selecting historical current data matching the monitoring requirement information from a historical database, performing format conversion on the matched historical current data based on the format requirement, and outputting the data to be divided; Using a preset data partitioning method to partition the data to be partitioned, to obtain a training data set, a verification data set, and a test data set; Training and optimizing the first model based on the training data set, the validation data set, and the test data set to obtain a prediction model; Using a preset data analysis model to obtain a time constant corresponding to an inherent parameter of the generator; Input the target current data, real-time current data and time constant at each moment into the prediction model for prediction analysis, obtain the predicted current at each moment, and output current prediction data; At the same time, in combination with the current-voltage comparison table, the target voltage corresponding to the target current data is obtained, and the control data of the electromagnet to be selected is output; Combining manual selection instructions and system self-selection instructions, selecting a scoring method that matches the monitoring demand information in the method database; At the same time, combined with the preset requirement-method-indicator mapping table, the scoring indicators matching the scoring method are selected from the indicator database to construct a scoring indicator set; Based on the scoring method and the scoring index set, the current prediction data and the selected electromagnet control data at each same moment are evaluated and analyzed, and a first evaluation result is output; The first evaluation result is compared and analyzed with a preset target score, and the to-be-selected electromagnet control data corresponding to the comparison and analysis result that meets preset conditions is output as electromagnet control data.

2. A non-extracting rotor detection control method according to claim 1, characterized in that: The real-time acquisition of control instructions for controlling the robot in the generator includes: Acquire the control instructions being executed, completed, and to-be-executed by the robot in real time, and construct a control instruction set; At the same time, the control instructions in the control instruction set are divided by time to obtain a control instruction subset corresponding to each moment, and a real-time control instruction subset corresponding to the current moment is output.

3. A non-extracting rotor detection control method according to claim 1, characterized in that: Step 4 includes: In combination with the preset data-instruction comparison table, an execution instruction matching the electromagnet control data is obtained in the instruction database, and an execution instruction set is constructed; Based on the execution instruction set, corresponding operating parameters of the robot are controlled, and control process data is synchronously output; Parsing the control process data to obtain first process data corresponding to the motion trajectory of the robot and second process data corresponding to the motion data of the robot; At the same time, target process data corresponding to the electromagnet control data is acquired, and first target data corresponding to the first process data and second target data corresponding to the second process data are obtained by parsing; Comparing and analyzing the first process data and the first target data to obtain a first result, and at the same time, comparing and analyzing the second process data and the second target data to obtain a second result; Based on the first result and the second result, comprehensively output the real-time process data of the robot during the instruction execution process; At the same time, a historical control process instruction matching the robot and historical data during the execution of the historical control process instruction are obtained from a historical database, and the historical process data is output; Combined with the preset indicators selected from the indicator database, the real-time process data and the historical process data are evaluated and compared and analyzed, and the control evaluation results are output; in, Indicates the control evaluation results; Represents the total number of preset indicators used to evaluate the robot's motion trajectory; Indicates the total number of preset indicators used to evaluate the robot's motion data; represents the data offset of the robot motion trajectory data in the real-time process data under the i-th index; Represents the data offset of the robot motion trajectory data in the historical process data under the i-th index; represents the weight factor corresponding to the i-th indicator related to the robot's motion trajectory; represents the standard control parameter corresponding to the i-th indicator related to the robot motion trajectory; represents the exponential function; represents the error adjustment coefficient corresponding to the i-th indicator related to the robot motion trajectory; represents the data offset of the robot motion data in the real-time process data under the jth index; represents the data offset of the robot motion data in the historical process data under the jth index; represents the weight factor corresponding to the jth indicator related to the robot motion data; represents the standard control parameter corresponding to the jth indicator related to the robot motion data; represents the error adjustment coefficient corresponding to the jth indicator related to the robot motion data; Combined with the preset result-correction comparison table, obtain the correction instruction matching the control evaluation result; Based on the deviation correction instruction, the to-be-executed instruction of the robot is corrected to generate a correction instruction set, and the deviation correction feedback data is output synchronously, and the control process is optimized based on the deviation correction feedback data.

4. A system for executing a non-extraction rotor detection control method according to any one of claims 1 to 3, characterized in that: include: A data acquisition module, used to acquire control instructions for controlling the robot in the generator in real time, and at the same time, acquire the motion data of the robot in real time through a preset sensor set on the robot, and output initial data; A data analysis module, used to analyze the initial data to obtain analysis data, and to perform data analysis on the analysis data to obtain target current data corresponding to the electromagnet provided in the robot; A data analysis module, used for determining control data of the electromagnet based on the target current data and in combination with the acquired time constant, and outputting the control data of the electromagnet; The process optimization module is used to control the operating parameters of the electromagnet based on the electromagnet control data, synchronously output the control process data, evaluate the effect of the control process in combination with preset indicators, output the control evaluation results, and optimize the control process based on the control evaluation results.

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