A fan master control PLC detection method, system, device and medium

Abstract

The application discloses a kind of fan master control PLC detection method, system, equipment and medium, belong to PLC detection technical field, including the following steps: establish the Ethernet communication connection between test controller and the to-be-tested PLC;Detect the manufacturer information, model information and communication protocol information of to-be-tested PLC, and generate test parameter configuration table according to the identification result;Perform to-be-tested PLC interface function test;Carry out fan control logic verification, verify the accuracy of the variable pitch control mechanism, yaw control mechanism and power control mechanism of to-be-tested PLC by inputting fan operation characteristic signal;Interface function test result and control logic verification result are displayed on man-machine interface.The application combines interface function test and fan control logic verification organically, forming an integrated detection system, which can not only verify the basic hardware function of PLC, but also evaluate its control performance in a real control environment, realizing the deep integration of hardware detection and software verification.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of PLC detection, and in particular to a fan master control PLC detection method, system, device and medium. BACKGROUND

[0002] As a core control device of a wind power generation system, the fan master control PLC undertakes key functions such as variable pitch control, yaw control and power control, and directly affects the power generation efficiency and operation safety of the fan. With the rapid development of wind power generation technology and the continuous growth of fan installed capacity, the performance requirements for the fan master control PLC are becoming higher and higher, and the PLC needs to have high reliability, fast response capability and adaptability to complex working conditions. Traditional PLC detection mainly adopts single hardware interface testing or simple control logic verification, and such separated detection method cannot comprehensively evaluate the comprehensive performance of the PLC in the actual fan operation environment.

[0003] In the prior art, the detection method of the fan master control PLC usually separates the interface function test from the control logic verification, and lacks overall performance evaluation of the PLC in the multivariable coupling control state. At the same time, the existing control logic verification mainly uses a single type of excitation signal, which cannot simulate the complex wind condition changes encountered by the fan in actual operation, especially the real working environment where gradual wind condition and sudden wind condition appear alternately. In addition, the traditional detection method lacks in-depth analysis of the interaction between control mechanisms, and it is difficult to find the stability problems that may occur in the control system under complex working conditions, resulting in a large deviation between the detection results and the actual operation performance. SUMMARY

[0004] In view of the above problems, the application provides a fan master control PLC detection method, system, device and medium.

[0005] Therefore, the technical problem solved by the application is that the existing control logic verification mainly uses a single type of excitation signal, which cannot simulate the complex wind condition changes encountered by the fan in actual operation.

[0006] To solve the above technical problems, the application provides the following technical scheme: a fan master control PLC detection method, comprising the following steps:

[0007] Establishing an Ethernet communication connection between a test controller and a PLC to be tested;

[0008] Detecting the manufacturer information, model information and communication protocol information of the PLC to be tested, and generating a test parameter configuration table according to the identification result;

[0009] Performing interface function testing of the PLC to be tested, including digital input / output interface testing, analog input / output interface testing and communication interface testing;

[0010] The fan control logic verification is performed by inputting a fan operation characteristic signal to verify the accuracy of the pitch control mechanism, the yaw control mechanism and the power control mechanism of the to-be-tested PLC.

[0011] The interface function test result and the control logic verification result are displayed on a man-machine interactive interface.

[0012] As a preferred scheme of the wind turbine main control PLC detection method, the test parameter configuration table generation step comprises:

[0013] A standardized device description request is sent.

[0014] The structured device description information corresponding to the device description request returned by the to-be-tested PLC is parsed.

[0015] The manufacturer information, the model information and the hardware configuration information of the to-be-tested PLC are extracted from the structured device description information.

[0016] According to the manufacturer information and the model information, corresponding wind turbine technical parameters are matched and obtained from a built-in wind turbine main control PLC parameter database.

[0017] The interface test parameters are determined through the hardware configuration information, and the control logic verification parameter set is established through the wind turbine technical parameters.

[0018] The interface test parameters and the control logic verification parameter set are integrated to generate a test parameter configuration table.

[0019] The preferred technical scheme has the beneficial effects that: through automatic recognition of the PLC device information and matching of the wind turbine technical parameters, intelligent configuration of the test parameters is realized, the combination of the hardware configuration information and the wind turbine technical parameters enables the interface test parameters and the control logic verification parameters to be optimized in coordination, and the problem of parameter mismatch caused by manual configuration is avoided.

[0020] As a preferred scheme of the wind turbine main control PLC detection method, the step of performing the interface function test of the to-be-tested PLC comprises:

[0021] According to the test parameter configuration table, a digital quantity interface input test signal is input to the to-be-tested PLC and the output response thereof is detected.

[0022] Different voltage values are input to the analog quantity interface of the to-be-tested PLC and the output precision thereof is detected.

[0023] Test data are sent to the communication interface of the to-be-tested PLC and it is verified whether the communication is normal.

[0024] The test results of the interfaces are recorded.

[0025] As a preferred embodiment of the wind turbine main control PLC testing method described in this invention, the step of verifying the wind turbine control logic includes:

[0026] A dynamic simulation model of the wind turbine is established based on the control logic verification parameter set in the test parameter configuration table.

[0027] The wind turbine operating characteristic signal is generated by combining gradual excitation signal and sudden excitation signal, and the signal is modulated by the wind turbine dynamic simulation model.

[0028] The wind turbine operating characteristic signals are input to the pitch control input, yaw control input, and power control input of the PLC under test, respectively. Response data from each control output is collected synchronously. For the three subsystems of pitch control, yaw control, and power control, a unit step excitation is applied to each control input, and the corresponding output change is measured. A three-by-three interaction matrix M is constructed using the following formula:

[0029] ;

[0030] in, Let be the gain representing the relative influence of the j-th control input on the i-th control output. Let i be the change in the i-th output. For the change of the j-th input, and These are the corresponding nominal values;

[0031] Calculate the multivariate coupling evaluation index based on the interaction matrix M. ,when A value greater than 0.3 indicates a strongly coupled system, and the calculation formula is as follows:

[0032] ;

[0033] For strongly coupled systems, the interaction influence matrix is... As the steady-state gain matrix of the system, the frequency domain transfer function matrix is ​​constructed by combining the dynamic characteristic parameters of each control loop of the PLC under test. and The interaction influence matrix M is and The value at zero frequency, through stability analysis using the generalized Nyquist stability criterion, is expressed mathematically as follows:

[0034] ;

[0035] In the formula, Let be the determinant of the matrix. It is the identity matrix. is a transfer function matrix of the fan controlled object, is a transfer function matrix of the PLC controller, is a complex frequency domain variable, is true for all frequencies;

[0036] When there is any frequency point such that the determinant is equal to zero, the system is determined to be unstable, and when the determinant of all frequency points is not equal to zero, the system is determined to be stable.

[0037] The beneficial effects of the preferred technical solution are: by establishing the interaction matrix M and combining the frequency domain stability analysis, quantitative evaluation of the fan PLC multivariable coupling control system is realized, and the mutual influence strength among the pitch, yaw and power control mechanisms can be identified, when the coupling degree index exceeds 0.3, the generalized Nyquist stability criterion analysis is triggered, and the stability risk of the system under complex working conditions is effectively predicted.

[0038] As a preferred scheme of the wind turbine master PLC detection method, the gradual change excitation signal and the sudden change excitation signal combination step comprises:

[0039] The gradual change excitation signal is generated by using a linear ramp function, and the mathematical expression is:

[0040] ;

[0041] wherein, is a starting value, is a slope coefficient; the sudden change excitation signal uses a step function, and the amplitude is set according to the system steady-state gain;

[0042] The gradual change excitation signal is generated and input to the PLC to be tested, and when the output of the PLC to be tested is stable, the sudden change excitation signal is superimposed;

[0043] After the sudden change excitation signal ends, the gradual change excitation signal is continuously input to form a combined test sequence;

[0044] By adjusting the change speed of the gradual change excitation signal and the jump amplitude of the sudden change excitation signal, a combined excitation mode of different strengths is constructed in combination with the combined test sequence;

[0045] The combined excitation mode of different strengths is used in turn to test the PLC to be tested, and the control mechanism response characteristics of the PLC to be tested are recorded.

[0046] The beneficial effects of the preferred technical scheme are that the time sequence combination of the gradual excitation and the sudden excitation simulates the real working condition change mode in the operation of the fan, the construction of the excitation mode with different intensities realizes the comprehensive evaluation of the adaptability of the control mechanism under various working conditions, and potential problems that cannot be exposed by a single excitation mode are found.

[0047] As a preferred scheme of the fan main control PLC detection method, the analysis step of the response characteristics of the control mechanism comprises:

[0048] The response time and the control accuracy of the to-be-tested PLC in the gradual excitation stage and the sudden excitation stage are measured respectively;

[0049] The control output fluctuation amplitude of the to-be-tested PLC at the switching moment of the excitation signal is calculated;

[0050] The response time, the control accuracy and the output fluctuation amplitude are compared with preset control mechanism performance benchmark values;

[0051] When any parameter deviates from the benchmark value by more than a preset threshold value, it is determined that the control mechanism is abnormal.

[0052] The beneficial effects of the preferred technical scheme are that the combination of the phased response characteristic measurement and the switching moment fluctuation analysis comprehensively captures the dynamic performance of the control mechanism.

[0053] As a preferred scheme of the fan main control PLC detection method, the depth diagnosis of the abnormal control mechanism comprises:

[0054] For the abnormal control mechanism, the corresponding control loop is activated alone, and the interference of other control loops is shielded;

[0055] A standard step signal is input to the control loop, and the dynamic response parameters are measured;

[0056] The matching degree analysis is performed on the dynamic response parameters and the factory standard parameters of the PLC of the type;

[0057] The performance degradation process of the control mechanism is determined according to the matching degree calculation result.

[0058] The application provides a fan main control PLC detection system.

[0059] To solve the above technical problems, the application provides the following technical scheme: a fan main control PLC detection system, comprising:

[0060] A test controller is configured to establish an Ethernet communication connection with a to-be-tested PLC, detect device information of the to-be-tested PLC and generate a test parameter configuration table;

[0061] A signal generating module is configured to generate digital test signals, analog test signals and communication test data according to the test parameter configuration table;

[0062] A fan simulation module is configured to establish a dynamic simulation model of the fan and generate fan operation characteristic signals;

[0063] A data acquisition module is configured to acquire interface response data and control mechanism response data of the to-be-tested PLC;

[0064] An analysis and processing module is configured to analyze and process the acquired data, establish an interaction influence matrix among the control mechanisms and perform stability analysis;

[0065] A man-machine interactive interface is configured to display interface function test results and control logic verification results.

[0066] The application provides a computer device, including a memory and a processor, the memory stores a computer program, characterized in that the processor executes the computer program to realize the steps of the fan master PLC detection method.

[0067] The application provides a computer readable storage medium, which stores a computer program, characterized in that the computer program is executed by a processor to realize the steps of the fan master PLC detection method.

[0068] The application has the following beneficial effects:

[0069] By organically combining the interface function test with the fan control logic verification, an integrated detection system is formed, which can not only verify the basic hardware function of the PLC, but also evaluate the control performance of the PLC in a real control environment, and realizes the deep integration of hardware detection and software verification. This combination mode enables the detection process to find potential problems that cannot be exposed in separate testing, especially abnormal conditions that may occur under the interaction of interface performance and control algorithm.

[0070] The gradual change excitation signal and the sudden change excitation signal are combined to creatively simulate the complex wind condition change mode encountered by the fan in actual operation. This combined excitation mode can not only test the tracking ability of the PLC under stable working conditions, but also evaluate the rapid response characteristics of the PLC under sudden working conditions. The organic combination of the two excitation modes produces unexpected test effects, which can fully reveal the real performance of the control mechanism in the dynamic working condition conversion process.

[0071] The introduction of the dynamic simulation model of the fan realizes high consistency of the detection environment and the real running environment, signal modulation is performed through the simulation model, so that the test signal is closer to the actual wind condition characteristics. Compared with the traditional static signal test, this simulation-based test method can capture the subtle changes of the control system in the dynamic response process, and provides a more reliable technical foundation for accurately evaluating the PLC performance. BRIEF DESCRIPTION OF DRAWINGS

[0072] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0073] Fig. 1 A general flowchart of a fan master control PLC detection method provided by an embodiment of the present application.

[0074] Fig. 2 A gradual excitation and sudden excitation signal combination schematic diagram of a fan master control PLC detection method provided by an embodiment of the present application.

[0075] Fig. 3 A structure diagram of a fan master control PLC detection system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0076] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0077] Embodiment 1, refer to Figs. 1-2 For an embodiment of the present application, the embodiment provides a fan master control PLC detection method, including the following steps S1-S5:

[0078] S1, establish the Ethernet communication connection between the test controller and the PLC to be tested;

[0079] In this embodiment, the test controller adopts an industrial-grade embedded controller, which is configured with a dual-network card interface. The IP address of the main network card is set to 192.168.1.100, and the subnet mask is 255.255.255.0. The PLC to be tested is connected to the test controller through a standard RJ45 network cable. The connection topology adopts a point-to-point direct connection mode to avoid communication delay and interference that may be introduced by network switching equipment.

[0080] The test controller first executes a network initialization program to detect the network connectivity and the hardware state of the network card. By sending an ICMP ping message to scan the 192.168.1.1 to 192.168.1.254 network segment, the IP address of the PLC to be tested is found. When the PLC response is detected, the test controller records the IP address and performs a TCP connection test to verify the accessibility of the 502 port (the default port of Modbus TCP).

[0081] To ensure communication stability, the test controller sets the TCP connection parameters as follows: connection timeout time is 5 seconds, read / write timeout time is 3 seconds, and the maximum number of retries is 3. The test controller also monitors network quality parameters, including round-trip delay time, packet loss rate, and connection stability. When the network quality does not meet the test requirements, the user will be prompted to check the network connection.

[0082] S2, detecting the manufacturer information, model information and communication protocol information of the PLC to be tested, and generating a test parameter configuration table according to the identification result;

[0083] In this embodiment, the generation step of the test parameter configuration table includes S2.1~S2.6:

[0084] S2.1, sending a standardized device description request;

[0085] The test controller sends a standardized device description request to the PLC to be tested through the established Ethernet connection. First, it attempts to send a Modbus TCP function code 43 (read device identification) request to read basic device information such as object ID 0x00 (manufacturer name), 0x01 (product code), 0x02 (main version number). If the PLC supports the EtherNet / IP protocol, it sends a CIP (Common Industrial Protocol) Get Attribute Single service request targeting the IdentityObject (category code 0x01) to read manufacturer ID, device type, product code, etc. information. At the same time, the test controller also sends an OPC UA Browse service request to try to obtain detailed description information of the device node.

[0086] S2.2, analyze the structured device description information corresponding to the device description request returned by the PLC under test;

[0087] After receiving the response data of the PLC, the test controller performs corresponding data analysis according to the protocol type. For Modbus TCP response, the return data of function code 43 is analyzed to extract the manufacturer name string, product code and version information. For EtherNet / IP response, the CIP encapsulated data packet is analyzed to extract the manufacturer ID (such as Schneider 0x0800), device type, product code and version information from the attributes of Identity Object. For OPC UA response, the XML format node description information is analyzed to obtain the detailed specification parameters of the device. The test controller uses the multi-protocol parallel query method to improve the success rate and completeness of device information acquisition.

[0088] S2.3, extract the manufacturer information, model information, and hardware configuration information of the PLC under test from the structured device description information;

[0089] From the analyzed structured data, the test controller extracts key information and performs standardized processing. The manufacturer information is identified by the manufacturer ID or manufacturer name string, such as "Schneider Electric", "Siemens", "ABB", etc. The model information is extracted from the product code and model string, such as "M580", "S7-1500", "AC500-eCo", etc. The hardware configuration information includes digital input and output point numbers (such as 32DI / 16DO), analog input and output point numbers (such as 8AI / 4AO), communication interface types (such as 2 Ethernet ports, 1 serial port), memory capacity and processor type, etc.

[0090] S2.4, according to the manufacturer information and model information, match and obtain the corresponding fan technical parameters from the built-in fan master PLC parameter database;

[0091] The built-in fan master PLC parameter database of the test controller uses manufacturer and model as index keys to store technical parameters of various fans. Taking Schneider M580 PLC as an example, the fan technical parameters matched in the database include: suitable fan power level (1.5MW-3.0MW), variable pitch system type (electric variable pitch), rated wind speed (12m / s), cut-in wind speed (3m / s), cut-out wind speed (25m / s), variable pitch angle range (0-90°), yaw accuracy requirement (±5°), power control mode (maximum power point tracking + constant power control) and other key parameters.

[0092] S2.5, determine the interface test parameters through the hardware configuration information, and establish the control logic verification parameter set through the fan technical parameters;

[0093] Based on the hardware configuration information, the test controller determines the interface test parameters: the digital interface test voltage is 24VDC, the test frequency range is 1Hz-1000Hz; the analog interface test range is 4-20mA / 0-10VDC, the accuracy requirement is 0.1%; the communication interface test data transmission rate is 100Mbps, and the Modbus TCP and EtherNet / IP protocols are supported. Based on the fan technical parameters, the control logic verification parameter set is established: the wind speed signal range is 3-25m / s, the variable pitch angle control range is 0-90°, the yaw angle range is ±180°, the power control range is 0-3000kW, and the response time requirement is <2s for variable pitch, <10s for yaw, and <1s for power regulation.

[0094] S2.6, integrating the interface test parameters and the control logic verification parameter set to generate a test parameter configuration table;

[0095] The test controller integrates the interface test parameters and the control logic verification parameter set into a structured test parameter configuration table, which is stored in JSON format. The configuration table includes three main parts: device basic information section, interface test parameter section, and control verification parameter section. The device basic information section records the PLC manufacturer, model, and software and hardware versions; the interface test parameter section includes the test voltage, frequency, and accuracy requirements of various interfaces; and the control verification parameter section includes simulation model parameters, excitation signal range, and control algorithm reference values. The generated configuration table is automatically saved and displayed on the human-machine interaction interface, and the user can check and confirm the rationality of the test parameters.

[0096] S3, performing the interface function test of the PLC to be tested, including digital input and output interface test, analog input and output interface test, and communication interface test;

[0097] In the embodiment, the step of performing the interface function test of the PLC to be tested includes S3.1-S3.4:

[0098] S3.1, according to the test parameter configuration table, testing the digital interface input signal of the PLC to be tested and detecting its output response;

[0099] The test controller configures the digital output module to send test signals to the digital input interface of the PLC to be tested according to the 24VDC voltage level in the test parameter configuration table. First, static level testing is performed, high level (24V) and low level (0V) are respectively input to each channel of DI1-DI32 of the PLC, each state is maintained for 3 seconds, the corresponding digital state register in the PLC is read through the communication interface to verify the correctness of signal recognition. Then, dynamic response testing is performed, a square wave signal with a frequency of 10Hz is input to the DI1 channel for 10 seconds, the response delay time of the PLC is monitored, and the response time should be less than 10ms under normal circumstances.

[0100] For digital output interface testing, the test controller sends control instructions to the PLC through the communication interface to control the output of high and low levels of each channel of DO1-DO16, and measures the actual output voltage value using a digital multimeter. Taking the DO1 channel as an example, when the PLC outputs a high level, the measured voltage should be 24V±1V; when the PLC outputs a low level, the voltage should be less than 2V. At the same time, the load capacity is tested, a 200mA standard load is connected to the DO1 output end to verify the stability of the output voltage, and the voltage drop should be less than 1V.

[0101] S3.2, input different voltage values to the analog input interface of the PLC to be tested and detect the output precision;

[0102] The test controller configures a precision voltage source and a current source to send standard test signals to the analog input interface of the PLC to be tested. For voltage type analog input (0-10V), 0V, 2.5V, 5V, 7.5V and 10V are input in turn, each point is maintained for 5 seconds, and the A / D conversion value in the PLC is read through the communication interface. Taking 5V input as an example, the corresponding digital value in the PLC should be 50% of 32767, i.e. about 16384, and the allowable error range is ±33 (corresponding to 0.1% accuracy). For current type analog input (4-20mA), similar testing is performed by inputting 4mA, 8mA, 12mA, 16mA and 20mA in turn.

[0103] For analog output interface testing, the test controller sends D / A control instructions to the PLC through the communication interface to control each channel of AO1-AO4 to output a specified value, and measures the actual output using a digital multimeter. When a 50% full scale instruction is sent to the PLC, 5V±0.01V should be measured for the 0-10V output channel, and 12mA±0.02mA should be measured for the 4-20mA output channel. At the same time, linearity testing is performed, the actual measurement value at each point is recorded within the range of 0-100% with 10% step output, the linearity error is calculated, and the requirement is less than 0.2%.

[0104] S3.3, send test data to the communication interface of the PLC under test and verify whether the communication is normal;

[0105] The test controller conducts a comprehensive communication performance test on the Ethernet communication interface of the PLC under test. First, a basic connectivity test is performed, a Modbus TCP read-hold register instruction (function code 03) is sent, and the system status register inside the PLC is read to verify the correctness of the communication protocol. Then, a data transmission rate test is performed, 1000 read-write instructions are continuously sent, each containing 100 register data, the average response time and data throughput are calculated, and under normal circumstances, the single read-write response time should be less than 50 ms, and the data transmission rate should reach more than 10 Mbps.

[0106] A communication stability test is performed, read-write instructions are continuously sent for 30 minutes, 10 times per second, and the communication success rate and error type are calculated. Network delay changes and packet loss are monitored during the test, and any communication abnormalities and recovery time are recorded. For PLCs that support redundant communication, the switching function of the primary and backup communication links is also tested, the primary link is simulated to fail, and the automatic switching time and data continuity of the backup link are verified.

[0107] S3.4, record the test results of each interface;

[0108] The test controller records all the interface test data in the test report database. The digital interface test results include: the correct recognition rate of each channel (32 input channels all reach 100%), the response delay time (average 6 ms), and the output voltage accuracy (high level 24.1V, low level 0.2V). The analog interface test results include: A / D conversion accuracy (maximum error 0.08%), D / A output linearity (0.15%), and temperature drift coefficient (50ppm / ℃). The communication interface test results include: protocol compatibility (supporting Modbus TCP and EtherNet / IP), average response time (35ms), 30-minute stability test success rate (99.9%), and maximum data transmission rate (15Mbps).

[0109] All test data is stored in a structured format, including test timestamp, test conditions, measured values, and determination results. The interface function test report is generated, and various performance indicators are displayed in the form of charts and compared with technical specification requirements. Any abnormal conditions found during the test are recorded in detail, including abnormal type, occurrence time, impact range, and possible causes.

[0110] S4, perform fan control logic verification, verify the accuracy of the pitch control mechanism, yaw control mechanism, and power control mechanism of the PLC under test by inputting fan operation characteristic signals;

[0111] The step of verifying the fan control logic includes S4.1-S4.4:

[0112] S4.1, a fan dynamic simulation model is established according to the control logic verification parameter set in the test parameter configuration table;

[0113] The test controller establishes a comprehensive simulation model containing the aerodynamic characteristics of the wind wheel, the dynamics of the transmission chain, and the electromagnetic characteristics of the generator based on the fan technical parameters in the configuration table. Taking a 1.5 MW fan as an example, the wind wheel model uses the blade element momentum theory, inputs the blade geometric parameters (blade length 35 m, chord length distribution, twist angle distribution) and aerodynamic coefficient database, and establishes a nonlinear mapping relationship between wind speed, wind wheel torque and power. The transmission chain model considers factors such as gear box transmission ratio (1:97), bearing friction, elastic coupling, etc., and establishes the power transmission equation from the low speed shaft to the high speed shaft. The generator model is based on the mathematical model of a permanent magnet synchronous generator, including d-q axis inductance parameters, flux linkage coefficients and torque constants.

[0114] The simulation model runs on a real-time simulation platform and uses a fixed step size of 0.01s for numerical integration calculation. The model inputs include wind speed signals, wind direction signals, variable pitch angle commands, yaw angle commands, etc., and the outputs include generator speed, output power, cabin vibration, tower load, etc. Physical quantities. The simulation model also integrates the theoretical algorithms of the fan control system as a comparison benchmark, including the optimal variable pitch angle lookup table, the yaw-to-wind algorithm and the maximum power point tracking algorithm.

[0115] S4.2, a combination of gradually changing excitation signals and suddenly changing excitation signals is used to generate fan operating characteristic signals, and the signals are modulated through the fan dynamic simulation model;

[0116] The combination of gradually changing excitation signals and suddenly changing excitation signals includes A1-A4:

[0117] It is known that the gradually changing excitation signal uses a linear ramp function is generated, and the mathematical expression is:

[0118] ;

[0119] where, is the starting value, is the slope coefficient; the suddenly changing excitation signal uses a step function, and the amplitude is set according to the system steady-state gain.

[0120] A1, generate a gradually changing excitation signal and input it to the PLC under test, and when the output of the PLC under test is stable, superimpose a suddenly changing excitation signal;

[0121] The test controller first generates a wind speed ramping excitation signal, starting from a cut-in wind speed of 3 m / s and linearly increasing to a rated wind speed of 12 m / s at a rate of 0.2 m / s per second, lasting for 45 seconds. At the same time, a wind direction ramping excitation signal is generated, slowly turning from the north direction (0°) to the northeast direction (45°) at a rate of 1° per second, lasting for 45 seconds. The corresponding generator speed, output power and other parameters are calculated through the dynamic simulation model of the fan, and these signals are sent to the corresponding input channels of the PLC under test through the analog output module.

[0122] The test controller continuously monitors the pitch angle output, yaw angle output and power control output of the PLC. When the output change is less than 0.1% for 5 consecutive seconds, it is determined that the output is stable. Taking the pitch control as an example, when the wind speed reaches 12 m / s, the PLC should output a pitch angle of 15°. At this time, the pitch angle output is detected to be stable at 15.2±0.1°.

[0123] A2, after the end of the mutation excitation signal, continue to input the ramping excitation signal to form a combined test sequence;

[0124] When the PLC output is detected to be stable, the test controller immediately superimposes a mutation excitation signal. The wind speed signal jumps from 12 m / s to 18 m / s instantaneously, simulating a sudden gust situation; the wind direction signal jumps from 45° to 90° instantaneously, simulating a sharp change in wind direction. The mutation excitation lasts for 10 seconds and then ends, and the ramping excitation signal is continued. The wind speed decreases from 18 m / s to 8 m / s at a rate of 0.3 m / s per second, and the wind direction turns from 90° to 30° at a rate of 2° per second.

[0125] The entire combined test sequence forms a complete test procedure of "ramping (45s) → mutation (10s) → ramping (30s)", totaling 85 seconds. The PLC should respond quickly during the mutation excitation phase, adjusting the pitch angle from 15.2° to 8.5° and the yaw angle from 45° to 90°, with response times of 1.8 seconds and 8.2 seconds, respectively.

[0126] A3, by adjusting the change rate of the ramping excitation signal and the jump amplitude of the mutation excitation signal, combined with the combined test sequence, a combined excitation mode of different intensities is constructed;

[0127] The test controller constructs three different intensity combined excitation modes. Mild excitation mode: ramp speed 0.1 m / s per second, sudden change amplitude 3 m / s; moderate excitation mode: ramp speed 0.2 m / s per second, sudden change amplitude 6 m / s; intensity excitation mode: ramp speed 0.5 m / s per second, sudden change amplitude 10 m / s. The wind direction excitation intensity of each mode is also adjusted accordingly, the wind direction ramp of the mild mode is 0.5° per second, sudden change is 15°, the moderate mode is 1° per second, sudden change is 30°, the intensity mode is 2° per second, sudden change is 60°.

[0128] A4, sequentially test the to-be-tested PLC with the different intensity combined excitation modes, and record the control mechanism response characteristics of the to-be-tested PLC under various excitation intensities;

[0129] The test controller sequentially executes the three excitation modes in the order of mild, moderate, and intensity, with a 5-minute interval between each mode to ensure that the PLC is fully reset. Under the mild excitation mode, the response time of the PLC's variable pitch control is 2.1 seconds, and the control accuracy error is 0.3°; under the moderate excitation mode, the response time is 1.8 seconds, and the control accuracy error is 0.5°; under the intensity excitation mode, the response time is 1.5 seconds, and the control accuracy error is 0.8°.

[0130] Among them, the analysis steps of the control mechanism response characteristics include A4.1~A4.4:

[0131] A4.1, respectively measure the response time and control accuracy of the to-be-tested PLC in the ramp excitation stage and the sudden change excitation stage;

[0132] In the ramp excitation stage, the test controller records the response of the PLC's variable pitch control during the process of the wind speed gradually changing from 8 m / s to 12 m / s. When the wind speed reaches 10 m / s, the theoretical optimal variable pitch angle should be 25°, and the actual output of the PLC is 25.3°, with a control accuracy error of 0.3°; from the time the PLC receives the wind speed signal to the time the variable pitch angle output reaches 90% of the target value, it takes 1.85 seconds, i.e. the response time is 1.85 seconds. In the sudden change excitation stage, the wind speed jumps from 12 m / s to 18 m / s instantaneously, and the theoretical optimal variable pitch angle should be adjusted from 15° to 5°, and the actual output of the PLC is 5.7°, with a control accuracy error of 0.7°; from the sudden change signal input to the time the variable pitch angle reaches 90% of the new target value, it takes 1.42 seconds.

[0133] The measurement results of the yaw control mechanism show that in the ramp excitation stage, the wind direction gradually changes from 30° to 60°, the PLC yaw angle output adjusts from 30.5° to 59.2°, the control accuracy error is 0.8°, and the response time is 7.3 seconds; in the sudden change excitation stage, the wind direction jumps from 60° to 90° instantaneously, the PLC yaw angle adjusts from 59.2° to 89.1°, the control accuracy error is 0.9°, and the response time is 6.8 seconds.

[0134] A4.2, calculate the control output fluctuation amplitude of the to-be-tested PLC at the moment of excitation signal switching;

[0135] At the moment of gradual excitation switching to sudden excitation (45th second), the pitch control output fluctuates from 15.2° to 13.8° and then rises to the target value 5.7° within 0.2 seconds, with a maximum fluctuation amplitude of . The yaw control output fluctuates from 45.3° to 42.1° and then adjusts to the target value 89.1° within 0.5 seconds, with a maximum fluctuation amplitude of . The power control output fluctuates from 1.5 MW to 1.38 MW and then stabilizes to the target value 2.8 MW, with a maximum fluctuation amplitude of .

[0136] A4.3, compare the response time, control accuracy and output fluctuation amplitude with the preset control mechanism performance benchmark value;

[0137] The test controller compares and analyzes the measured results with the preset control mechanism performance benchmark value. The pitch control benchmark value: response time ≤ 2.0 seconds, control accuracy ≤ ± 1.0°, output fluctuation amplitude ≤ 2.0°; the measured value: response time 1.42-1.85 seconds, control accuracy ± 0.3-0.7°, output fluctuation amplitude 1.4°, all meet the benchmark requirements. The yaw control benchmark value: response time ≤ 10.0 seconds, control accuracy ≤ ± 2.0°, output fluctuation amplitude ≤ 5.0°; the measured value: response time 6.8-7.3 seconds, control accuracy ± 0.8-0.9°, output fluctuation amplitude 3.2°, all meet the benchmark requirements.

[0138] A4.4, when any parameter deviates from the benchmark value by more than the preset threshold value, determine that the control mechanism is abnormal;

[0139] Since all measured parameters are within the preset threshold value, it is determined that the pitch control mechanism, yaw control mechanism and power control mechanism are all working normally. Then a green state indication is generated, and “control mechanism performance is normal” is displayed on the human-computer interaction interface. If the yaw control response time is detected to be 12.5 seconds in a certain test, which exceeds the 25% threshold value of the benchmark value 10.0 seconds, the control mechanism abnormality alarm will be automatically triggered, and the deep diagnosis program will be started.

[0140] It is also necessary to know that the deep diagnosis of the abnormal control mechanism includes B1-B4:

[0141] B1, for the abnormal control mechanism, activate the corresponding control loop alone and shield the interference of other control loops;

[0142] When yaw control abnormality is detected, the test controller sends control commands to the PLC through the communication interface, sets the pitch control loop to manual mode and locks at the current angle 15°, sets the power control loop to constant output mode and locks at 1.5 MW. Only the yaw control loop is kept in automatic mode to ensure that other control loops do not interfere with the yaw control. At the same time, the wind speed and power and other input signals that may affect the yaw control are disconnected, and only the wind direction signal input is retained.

[0143] B2, input a standard step signal to the control loop and measure its dynamic response parameters;

[0144] The test controller inputs a standard 30° step signal to the yaw control loop, i.e. the wind direction signal jumps from the current 60° to 90°. The encoder is used to monitor the change process of the yaw angle in real time, and the sampling frequency is 100 Hz. The measured dynamic response parameters include: delay time (the time from inputting the step signal to the output starting to change) is 0.8 seconds, rise time (the time from 10% to 90% of the output) is 8.5 seconds, regulation time (the time from the start of step response to entering the ±2% error band) is 15.2 seconds, overshoot (the percentage of the maximum overshoot value to the steady-state value) is 6.8%, and steady-state error (the deviation of the steady-state output value from the target value) is 1.3°.

[0145] B3, match the dynamic response parameters with the factory standard parameters of the PLC of this type;

[0146] The factory standard parameters of the yaw control loop of the PLC of this type are obtained from the technical documents provided by the PLC manufacturer: delay time 0.5 seconds, rise time 6.0 seconds, regulation time 10.0 seconds, overshoot 5.0%, steady-state error 0.5°. The deviation degrees of each parameter are calculated as follows:

[0147] Delay time deviation degree Rise time deviation degree Regulation time deviation degree Overshoot deviation degree Steady-state error deviation degree .

[0148] B4, determine the performance degradation of the control mechanism according to the matching degree calculation results;

[0149] The overall matching degree is calculated by weighted average method, and the weights of each parameter are as follows: delay time 15%, rise time 25%, regulation time 30%, overshoot 15%, steady-state error 15%.

[0150] The overall matching degree is According to the performance degradation degree classification standard: matching degree > 80% is slight degradation, 50%-80% is moderate degradation, and < 50% is serious degradation. The matching degree of the yaw control mechanism is 30.9%, which is determined as serious performance degradation, and it is suggested to immediately stop the yaw motor and the reducer for maintenance.

[0151] S4.3, input the fan operating characteristic signal into the pitch control input end, the yaw control input end and the power control input end of the to-be-tested PLC respectively, synchronously collect the response data of each control output end, for the pitch control, the yaw control and the power control three subsystems, apply a unit step excitation to each control input and measure the corresponding output change, and a three-by-three interaction influence matrix M is constructed through a formula, which is specifically represented as:

[0152] ;

[0153] Among them, is the relative influence gain of the jth control input to the ith control output, is the change of the ith output, is the change of the jth input, and are the corresponding nominal values respectively;

[0154] In the embodiment of the application, the test controller inputs the composite signal modulated by the fan dynamic simulation model into the three control input channels of the to-be-tested PLC at the same time: the wind speed signal is connected to the pitch control analog input AI1 (corresponding to the pitch control), the wind direction signal is connected to the yaw control analog input AI2 (corresponding to the yaw control), and the power demand signal is connected to the power control analog input AI3 (corresponding to the power control). The test controller collects the three control outputs of the PLC in real time through the Ethernet communication interface: the pitch angle output AO1, the yaw angle output AO2 and the power control output AO3, and the sampling frequency is set to 100Hz to ensure that the dynamic response process of the control system can be captured.

[0155] In order to construct the interaction influence matrix M, the test controller applies a unit step test to the three control inputs one by one. First, a unit step excitation is applied to the pitch control input: the wind speed signal is instantaneously changed from the current steady-state value 10 m / s to 11 m / s ( ), and the other two input signals remain unchanged, and the output data is continuously collected for 60 seconds. The measurement result shows that the pitch angle output changes from 18.5° to 16.2° ( ), the yaw angle output changes from 45.0° to 45.1° ( ), and the power control output changes from 1.8 MW to 2.1 MW ( ).

[0156] Then a unit step excitation is applied to the yaw control input: the wind direction signal is jumped from the current steady state value 60° to 61° ( ), while the wind speed and power demand signals are kept constant. The measured results show that the pitch angle output changes from 16.2° to 16.3° ( ), the yaw angle output changes from 45.1° to 46.1° ( ), and the power control output changes from 2.1 MW to 2.15 MW ( ).

[0157] Finally a unit step excitation is applied to the power control input: the power demand signal is jumped from the current steady state value 2.0 MW to 2.1 MW ( ), while the wind speed and wind direction signals are kept constant. The measured results show that the pitch angle output changes from 16.3° to 15.8° ( ), the yaw angle output changes from 46.1° to 46.0° ( ), and the power control output changes from 2.15 MW to 2.25 MW ( ).

[0158] According to the test data, the nominal values are used for normalization, U1, nom = 12 m / s (rated wind speed), U2, nom = 180° (yaw range), U3, nom = 3.0 MW (rated power); Y1, nom = 45° (pitch median angle), Y2, nom = 180° (yaw range), Y3, nom = 3.0 MW (rated power).

[0159] Then the elements of the interaction matrix are calculated according to the formula, which are denoted as: , the influence of the pitch input on the pitch output; , the influence of the yaw input on the pitch output; , the influence of the power input on the pitch output, and so on.

[0160] Finally, the 3x3 interaction matrix M is obtained:

[0161] ;

[0162] The matrix reflects the coupling relationship between the three control subsystems of the wind turbine PLC: the diagonal elements M11, M22, M33 represent the main control gains of each control loop, respectively; the non-diagonal elements represent the cross-coupling strength, in which M32 = 3.0 indicates that there is a strong coupling effect of the yaw control on the power output, which is due to the fact that the yaw error will directly affect the effective wind energy received by the wind wheel. The test controller stores this interaction matrix in the test database, providing basic data for subsequent coupling degree analysis and stability evaluation.

[0163] S4.4, calculating a multivariable coupling degree evaluation index according to the interaction influence matrix M , when greater than 0.3 is determined as a strong coupling system, and the calculation formula is represented as:

[0164] ;

[0165] For the strong coupling system, the interaction influence matrix M is calculated according to the step S4.3. As the system steady-state gain matrix, the frequency domain transfer function matrix is constructed in combination with the dynamic characteristic parameters of each control loop of the to-be-tested PLC and , wherein the interaction influence matrix M is and The value at zero frequency is analyzed for stability by the generalized Nyquist stability criterion, and is represented by a mathematical formula as:

[0166] ;

[0167] In the formula, det (M) is the determinant of the matrix M, is the determinant of the matrix M, is the unit matrix, is the transfer function matrix of the fan controlled object, is the transfer function matrix of the PLC controller, is a complex frequency domain variable, is true for all frequencies;

[0168] When there is any frequency point that makes the determinant equal to zero, the system is determined to be unstable, and when the determinant of all frequency points is not equal to zero, the system is determined to be stable;

[0169] In the embodiment of the application, the test controller calculates the multivariable coupling degree evaluation index according to the interaction influence matrix M constructed in the step S4.3 and according to the formula. First, the sum of the absolute values of the non-diagonal elements is calculated: . Then, the sum of the absolute values of the diagonal elements is calculated: .

[0170] Therefore, the coupling degree evaluation index CI is , and greater than 0.3 is the determination threshold, indicating that the fan PLC control system is a strong coupling system, and further stability analysis is required. The test controller displays the state information "strong coupling system detected, CI = 1.897, stability analysis is in progress..." on the human-computer interaction interface.

[0171] For the strong coupling system, the test controller takes the interaction matrix M as the steady-state gain matrix of the system, and combines the dynamic characteristic parameters of each control loop obtained from the PLC technical document to construct the frequency domain transfer function matrix. The transfer function of the pitch control loop is a first-order inertia link where , ; the transfer function of the yaw control loop is a second-order under-damped link where , , ; the transfer function of the power control loop is an integral plus inertia link where , .

[0172] The transfer function matrix of the wind turbine controlled object is obtained through simulation model identification. The pitch control object is , the yaw control object is , and the power control object is . The cross-coupling terms are fitted through measured data: , , , , , .

[0173] The test controller constructs the complete frequency domain transfer function matrix , and samples 1000 frequency points at a logarithmic interval within the frequency range of 0.01 Hz to 100 Hz, and calculates the value of at each point. At , the calculation result is:

[0174] ;

[0175] ;

[0176] The determinant of this matrix is calculated: , and its modulus is .

[0177] The test controller performs similar calculations for all 1000 frequency points, and finds that the modulus of the determinant reaches a minimum value of 0.087 at , but is still greater than zero; another minimum value of 0.156 appears at . The determinant of all frequency points is not equal to zero, meeting the requirements of the generalized Nyquist stability criterion, and determining that the system is stable.

[0178] Further analysis finds that although the system is stable as a whole, the pitch control loop is unstable at The low margin value of 0.087 nearby indicates that the system has a potential risk of oscillation at this frequency. The test controller calculates that the minimum singular value margin of the system is 6.8 dB, and the phase margin is 28.5°, both of which meet the engineering stability requirements, but the phase margin is close to the critical value of 30°.

[0179] Finally, a stability analysis report is generated: the system is stable overall under the current control parameters, but the strong coupling between yaw control and power control (M32 = 3.0) may cause system oscillation under certain working conditions, and it is recommended to add a feedforward decoupling link in the PLC control algorithm or appropriately reduce the gain coefficient of the yaw control to improve the robust stability of the system. The test controller displays the analysis results in the form of charts on the human-computer interaction interface, including frequency response curves, Nyquist diagrams, and stability margin indicators.

[0180] S5, display the interface function test results and control logic verification results on the human-computer interaction interface.

[0181] Embodiment 2, refer to Fig. 3 As shown in the figure, an embodiment of the present application provides a fan master control PLC detection system, which comprises:

[0182] A test controller is used to establish an Ethernet communication connection with the PLC to be tested, detect the device information of the PLC to be tested, and generate a test parameter configuration table;

[0183] A signal generation module is used to generate digital test signals, analog test signals, and communication test data according to the test parameter configuration table;

[0184] A fan simulation module is used to establish a dynamic simulation model of the fan and generate fan operation characteristic signals;

[0185] A data acquisition module is used to acquire interface response data and control mechanism response data of the PLC to be tested;

[0186] An analysis and processing module is used to analyze and process the acquired data, establish an interactive influence matrix between the control mechanisms, and perform stability analysis;

[0187] A human-computer interaction interface is used to display the interface function test results and control logic verification results.

[0188] Embodiment 3, the present embodiment also provides an electronic device suitable for a fan master control PLC detection method, which comprises a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to realize a fan master control PLC detection method as proposed in the above embodiments.

[0189] The embodiment further provides a storage medium, which stores a computer program, and the computer program is executed by a processor to implement a fan master control PLC detection method according to the above embodiment.

[0190] The storage medium according to the embodiment and the fan master control PLC detection method according to the above embodiment belong to the same inventive concept, and the technical details not described in the embodiment can be referred to the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.

[0191] Through the above description of the embodiments, those skilled in the art can clearly understand that the present application can be realized by means of software and necessary universal hardware, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a FLASH, a hard disk or an optical disk, etc., including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of various embodiments of the present application.

[0192] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A fan master PLC detection method, characterized in that: The method comprises the following steps: establishing an Ethernet communication connection between a test controller and a PLC to be tested; detecting manufacturer information, model information and communication protocol information of the PLC to be tested, and generating a test parameter configuration table according to the identification result; performing interface function testing of the PLC to be tested, including digital quantity input and output interface testing, analog quantity input and output interface testing and communication interface testing; performing fan control logic verification by inputting fan operation characteristic signals to verify the accuracy of the pitch control mechanism, yaw control mechanism and power control mechanism of the PLC to be tested; displaying the interface function testing result and the control logic verification result on a man-machine interactive interface; the fan control logic verification step comprises: establishing a fan dynamic simulation model according to a control logic verification parameter set in the test parameter configuration table; generating fan operation characteristic signals in a combination of gradual excitation signals and sudden excitation signals, and modulating the signals through the fan dynamic simulation model; inputting the fan operation characteristic signals into the pitch control input end, yaw control input end and power control input end of the PLC to be tested respectively, synchronously collecting response data of each control output end, for the pitch control, yaw control and power control three subsystems, applying a unit step excitation to each control input and measuring the corresponding output change, and constructing a three-by-three interaction influence matrix M through a formula, which is specifically represented as: ； wherein, is the relative influence gain of the jth control input on the ith control output, is the change in the ith output, is the change in the jth input, and are the corresponding nominal values, respectively. Calculate the multivariate coupling evaluation index based on the interaction matrix M. ,when A value greater than 0.3 indicates a strongly coupled system, and the calculation formula is as follows: ； For the strongly coupled system, the interaction matrix M is constructed As the system steady-state gain matrix, the frequency domain transfer function matrix is constructed in combination with the dynamic characteristic parameters of each control loop of the PLC to be tested And Wherein the interaction matrix M is And The value at zero frequency is analyzed for stability by the generalized Nyquist stability criterion, which is mathematically expressed as: ； wherein is the determinant of the matrix, is the identity matrix, is the transfer function matrix of the fan controlled object, is the transfer function matrix of the PLC controller, is the complex frequency domain variable, is true for all frequencies; when there is any frequency point making the determinant equal to zero, it is determined that the system is unstable, and when the determinant of all frequency points is not equal to zero, it is determined that the system is stable.

2. The fan master PLC detection method of claim 1, wherein: the generation step of the test parameter configuration table comprises: sending a standardized device description request; parsing structured device description information corresponding to the device description request returned by the PLC to be tested; extracting manufacturer information, model information and hardware configuration information of the PLC to be tested from the structured device description information; according to the manufacturer information and model information, matching and obtaining corresponding fan technical parameters from a built-in fan master control PLC parameter database; determining interface testing parameters through the hardware configuration information, and establishing a control logic verification parameter set through the fan technical parameters; integrating the interface testing parameters and the control logic verification parameter set to generate a test parameter configuration table.

3. The fan master PLC detection method of claim 2, wherein: the step of performing interface function testing of the PLC to be tested comprises: according to the test parameter configuration table, inputting test signals to the digital quantity interface of the PLC to be tested and detecting the output response of the PLC to be tested; inputting different voltage values to the analog quantity interface of the PLC to be tested and detecting the output accuracy of the PLC to be tested; sending test data to the communication interface of the PLC to be tested and verifying whether the communication is normal; recording the test results of each interface.

4. The fan master PLC detection method of claim 3, wherein: the combination step of the gradual excitation signal and the sudden excitation signal comprises: The gradual excitation signal adopts a linear ramp function is generated, mathematically expressed as: ； wherein is the initial value, is the slope coefficient; the mutation excitation signal takes a step function, the amplitude of which is set according to the system steady-state gain; generating a gradual excitation signal and inputting it to the PLC to be tested, and when the output of the PLC to be tested is stable, superimposing a sudden excitation signal; after the sudden excitation signal ends, continue to input the gradual excitation signal to form a combined test sequence; by adjusting the change speed of the gradual excitation signal and the jump amplitude of the sudden excitation signal, combining the combined test sequence, a combined excitation mode with different intensities is constructed; The different intensity combination excitation modes are used in sequence to test the to-be-tested PLC, and the control mechanism response characteristics of the to-be-tested PLC are recorded.

5. The fan master PLC detection method of claim 4, wherein: The analysis step of the control mechanism response characteristics comprises: The response time and control accuracy of the to-be-tested PLC in the gradual excitation stage and the sudden excitation stage are measured respectively; The control output fluctuation amplitude of the to-be-tested PLC at the excitation signal switching moment is calculated; The response time, control accuracy and output fluctuation amplitude are compared with preset control mechanism performance benchmark values; When any parameter deviates from the benchmark value by more than a preset threshold value, it is determined that the control mechanism is abnormal.

6. The fan master PLC detection method of claim 5, wherein: The deep diagnosis of the abnormal control mechanism comprises: For the abnormal control mechanism, the corresponding control loop is activated alone, and the interference of other control loops is shielded; A standard step signal is input to the control loop corresponding to the abnormal control mechanism, and the dynamic response parameters of the control loop are measured; The dynamic response parameters are matched with the factory standard parameters of the to-be-tested PLC for matching degree analysis; The performance degradation of the control mechanism is determined according to the matching degree calculation result.

7. A fan master PLC detection system, applying the fan master PLC detection method according to any one of claims 1-6, characterized in that, Comprise: A test controller is configured to establish an Ethernet communication connection with the to-be-tested PLC, detect the device information of the to-be-tested PLC and generate a test parameter configuration table; A signal generation module is configured to generate digital test signals, analog test signals and communication test data according to the test parameter configuration table; A fan simulation module is configured to establish a fan dynamic simulation model and generate fan operation characteristic signals; A data acquisition module is configured to acquire interface response data and control mechanism response data of the to-be-tested PLC; An analysis processing module is configured to analyze and process the acquired data, establish an interaction influence matrix between control mechanisms and perform stability analysis; A human-computer interaction interface is configured to display interface function test results and control logic verification results.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to realize the steps of the fan main control PLC detection method in any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the fan main control PLC detection method in any one of claims 1 to 6.

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