Situation awareness servo driver operation monitoring system and method based on artificial intelligence

Abstract

The invention belongs to the field of driver operation monitoring, relates to a data analysis technology, is used for solving the problem that the operation control requirements of a driver in different application environments cannot be met in the prior art, and particularly relates to a situation awareness servo driver operation monitoring system and method based on artificial intelligence. The processor is in communication connection with an external acquisition module, an internal balance module, a controller and a database, the internal balance module is also in communication connection with a verification processing module, and the external acquisition module is used for acquiring external parameters of the situation awareness servo driver and acquiring an external parameter set of a monitored object at a monitoring time point; according to the method, data support is provided for the internal parameter configuration process through the external parameters, numerical calculation is carried out on all the parameters in the external parameter set to obtain a plurality of screening ranges, and therefore different standards can be adopted to analyze the internal parameters in the configuration data to obtain the configuration standard.

Description

Technical Field

[0001] The present invention belongs to the field of driver operation monitoring and relates to data analysis technology, and specifically to an artificial intelligence-based situation awareness servo driver operation monitoring system and method. Background Art

[0002] The operation monitoring system of the servo drive realizes comprehensive monitoring and management of motor equipment by real-time monitoring of various electrical parameter data of the motor circuit and the distribution circuit and centralized monitoring of the access equipment, thereby improving energy utilization efficiency and reducing energy waste.

[0003] However, the situational awareness servo drive operation monitoring system in the prior art can only monitor the operation of the drive from the perspective of energy saving. However, the drives in different application environments have different requirements for the operation parameter configuration. For example, when the drive is used in a harsh outdoor environment, its most core requirement is not energy-saving performance, but to reduce the probability of its operation failure or reduce the processing time cost when it fails through operation parameter configuration. Therefore, the prior art cannot meet the operation control requirements of the drive in different application environments.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an artificial intelligence-based situational awareness servo drive operation monitoring system and method, which is used to solve the problem in the prior art that the operation control requirements of the drive in different application environments cannot be met.

[0006] The technical problem to be solved by the present invention is: how to provide an artificial intelligence-based situational awareness servo drive operation monitoring system and method that can meet the operation control requirements of the drive in different application environments.

[0007] The object of the present invention can be achieved by the following technical solutions: A situational awareness servo drive operation monitoring system based on artificial intelligence, comprising a processor, the processor is communicatively connected to an external acquisition module, an internal balancing module, a controller and a database, and the internal balancing module is also communicatively connected to a verification processing module;

[0008] The external acquisition module is used to collect external parameters of the situation awareness servo drive: mark the situation awareness servo drive as a monitoring object, set a number of monitoring time points with the same time interval, and obtain the external parameter set of the monitoring object at the monitoring time point; send the external parameter set to the internal balancing module through the processor;

[0009] The internal balancing module is used to perform configuration analysis on the internal operating parameters of the situation awareness servo drive according to the external parameter set: retrieve the historical operating data of the monitored object through the database, and filter the historical operating data through the external parameter set to obtain the configuration data;

[0010] The user selects a configuration mode to configure the internal operating parameters to obtain the speed configuration range and the torque configuration range. The speed configuration range and the torque configuration range constitute the internal configuration parameters. The configuration modes include energy-saving priority mode, fault priority mode and processing priority mode;

[0011] The verification processing module is used to verify and analyze the internal parameter configuration state of the situation awareness servo driver and obtain the verification coefficient JY of the internal configuration parameters, and to determine whether the coverage accuracy of the internal configuration parameters meets the requirements through the verification coefficient JY.

[0012] Furthermore, the process of acquiring the external parameter set includes: acquiring the output voltage value and current value of the monitored object connected to the power grid and marking them as the output voltage value YC and the output flow value LC, acquiring the operating load of the monitored object and marking it as the load display value ZX, and marking the output voltage value YC, the output flow value LC and the load display value ZX as the external parameter set of the monitored object.

[0013] Further, the configuration parameter acquisition process includes: historical operation data including the output voltage value, output current value, load value, operating speed value, operating torque value and energy consumption value of the monitored object when connected to the power grid at the corresponding monitoring time point; marking the period formed from the corresponding monitoring time point to the next monitoring time point of the historical operation data as the operation period; marking the total energy consumption of the monitored object in the operation period as the energy consumption value; obtaining the high pressure value YCmax and the low pressure value YCmin through the formula YCmax=t1*YC and YCmin=t2*YC, and the high pressure value YCmax and the low pressure value YCmin constitute the pressure screening range;

[0014] The outflow high value LCmax and the outflow low value LCmin are obtained by the formula LCmax=t1*LC and LCmin=t2*LC, and the outflow high value LCmax and the outflow low value LCmin constitute the outflow screening range;

[0015] The high value ZXmax and the low value ZXmin of the load display are obtained by the formula ZXmax=t1*ZX and ZXmin=t2*ZX, wherein t1 and t2 are both proportional coefficients, and 1.05≤t1≤1.15, 0.85≤t2≤0.95; the high value ZXmax and the low value ZXmin of the load display constitute the load display screening range;

[0016] The historical operation data whose output voltage value, output current value and load value are respectively within the pressure-out screening range, the outflow screening range and the load display screening range are marked as configuration data.

[0017] Furthermore, the specific process of using the energy-saving priority mode to configure the internal operating parameters includes: arranging the configuration data in order of energy consumption values ​​from small to large to obtain an energy-saving priority sequence, marking the top L1 configuration data in the energy-saving priority sequence as energy-saving priority data, forming a speed configuration range by the maximum operating speed value and the minimum operating speed value in the energy-saving priority data, forming a torque configuration range by the maximum operating torque value and the minimum operating torque value in the energy-saving priority data, and sending the speed configuration range and the torque configuration range as internal configuration parameters to the verification processing module.

[0018] Furthermore, the specific process of using the fault priority mode to configure the internal operating parameters includes: arranging the configuration data in order of the operating speed value from large to small to obtain a speed sequence, decomposing the speed sequence into several speed intervals, the number of configuration data in each speed interval is L1, marking the configuration data that fails during the operating period as fault data, marking the number of fault data in the speed interval as the fault value of the speed interval, the speed configuration range is composed of the maximum boundary value and the minimum boundary value of the speed interval with the smallest fault value, and the torque configuration range is composed of the maximum value and the minimum value of the operating torque of the configuration data in the speed interval with the smallest fault value; the speed configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters.

[0019] Furthermore, the specific process of using the processing priority mode to configure the internal operating parameters includes: marking the fault processing time of the fault data in the speed range after the fault occurs as the processing value of the fault data, summing and averaging the processing values ​​of all fault data in the speed range to obtain the timely value, the speed configuration range is composed of the maximum boundary value and the minimum boundary value of the speed range with the smallest timely value, and the torque configuration range is composed of the maximum value and the minimum value of the operating torque of the configuration data in the extrusion range with the smallest timely value; the torque configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters.

[0020] Furthermore, the process of obtaining the verification coefficient JY of the internal configuration parameters includes: marking the difference between the maximum boundary value and the minimum boundary value of the torque configuration range as the torque range value JF, marking the difference between the maximum boundary value and the minimum boundary value of the speed configuration range as the speed range value SF, and performing numerical calculation on the torque range value JF and the speed range value SF to obtain the verification coefficient JY.

[0021] Furthermore, the specific process of determining whether the coverage accuracy of the internal configuration parameters meets the requirements includes: comparing the verification coefficient JY with the preset verification threshold JYmax: if the verification coefficient JY is less than the verification threshold JYmax, it is determined that the coverage accuracy of the internal configuration parameters meets the requirements, and the internal configuration parameters are sent to the controller of the monitored object through the processor; if the verification coefficient JY is greater than or equal to the verification threshold JYmax, it is determined that the coverage accuracy of the internal configuration parameters does not meet the requirements, and the internal configuration parameters are indented: L1=L1-1 is set, the internal configuration parameters are re-acquired through the corresponding configuration mode and the verification coefficient JY is calculated, and so on, until the verification coefficient JY is less than the verification threshold JYmax.

[0022] The present invention also proposes a situation awareness servo drive operation monitoring method based on artificial intelligence, comprising the following steps:

[0023] Step 1: Collect external parameters of the situation awareness servo driver to obtain an external parameter set;

[0024] Step 2: Analyze the internal operating parameters of the situation awareness servo drive according to the external parameter set and filter the configuration data;

[0025] Step 3: Perform internal operation parameter configuration according to the configuration mode selected by the user to obtain internal configuration parameters;

[0026] Step 4: Verify and analyze the internal parameter configuration status of the situation awareness servo driver and determine whether the coverage accuracy of the internal configuration parameters meets the requirements. If the requirements are not met, the internal configuration parameters are indented.

[0027] Additionally, a computer storage medium stores a computer program, which, when executed by a processor, implements an artificial intelligence-based situational awareness servo drive operation monitoring method.

[0028] The present invention has the following beneficial effects:

[0029] 1. The external parameters of the situation awareness servo drive can be collected through the external acquisition module, and the external parameters can provide data support for the internal parameter configuration process. All parameters in the external parameter set are numerically calculated to obtain multiple screening ranges, and then the historical operation data is screened according to the multiple screening ranges to obtain configuration data. The configuration data represents the historical operation data with similar external parameters to the monitored object. Therefore, different standards can be used to analyze the internal parameters in the configuration data to obtain the configuration standard;

[0030] 2. Through the energy-saving priority mode, fault priority mode and processing priority mode, different configuration logics can be used to configure the internal operating parameters. The different internal configuration parameters obtained can be suitable for different application environments and meet different user needs, thereby improving the applicability of the internal configuration parameters;

[0031] 3. The verification processing module can be used to verify and analyze the internal parameter configuration status of the situation awareness servo driver, and the boundary values ​​of the speed configuration range and the torque configuration range can be numerically calculated to obtain the verification coefficient. The coverage accuracy of the internal configuration parameters can be fed back through the verification coefficient, thereby ensuring the accuracy of the configuration range of the internal configuration parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only 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.

[0033] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0034] Figure 2 Flow chart of the verification analysis process of the verification processing module in the first embodiment of the present invention;

[0035] Figure 3 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0036] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0037] The situation awareness driver uses the magnetic pole pair signal of the rotor rotation of the motor structure as the sampled sinusoidal acquisition signal, reads the pole pair number of the motor through the decoder as reference feedback, and upgrades and optimizes the original closed-loop servo to resolve the output sinusoidal wave into a digital signal as feedback, and uses the principle of resolver encoding to achieve situation awareness soft servo control.

[0038] Embodiment 1: Figure 1-Figure 2 As shown, the artificial intelligence-based situational awareness servo drive operation monitoring system includes a processor, the processor is communicatively connected to an external acquisition module, an internal balancing module, a controller and a database, and the internal balancing module is also communicatively connected to a verification processing module.

[0039] The external acquisition module is used to collect the external parameters of the situation awareness servo drive: mark the situation awareness servo drive as a monitoring object, set several monitoring time points with the same time interval, obtain the output voltage value and current value of the monitored object connected to the power grid at the monitoring time point and mark them as the output value YC and the output value LC, obtain the operating load of the monitored object and mark it as the load display value ZX, mark the output value YC, the output value LC and the load display value ZX as the external parameter set of the monitored object; send the external parameter set to the internal balancing module through the processor; provide data support for the internal parameter configuration process through external parameters, perform numerical calculations on all parameters in the external parameter set to obtain multiple screening ranges, and then filter the historical operation data according to the multiple screening ranges to obtain configuration data. The configuration data represents the historical operation data whose external parameters are similar to the monitored object. Therefore, different standards can be adopted to analyze the internal parameters in the configuration data to obtain the configuration standard.

[0040] The internal balancing module is used to configure and analyze the internal operating parameters of the situation awareness servo drive according to the external parameter set: the historical operating data of the monitored object is retrieved through the database, and the historical operating data includes the output voltage value, output current value, load value, operating speed value, operating torque value and energy consumption value of the monitored object when connected to the power grid at the corresponding monitoring time point; the period formed from the corresponding monitoring time point to the next monitoring time point of the historical operating data is marked as the operating period, and the total energy consumption of the monitored object in the operating period is marked as the energy consumption value; the high pressure value YCmax and the low pressure value YCmin are obtained by the formula YCmax=t1*YC and YCmin=t2*YC, and the flow is obtained by the formula LCmax=t1*LC and LCmin=t2*LC. The high value of the output LCmax and the low value of the output LCmin are obtained by the formula ZXmax=t1*ZX and ZXmin=t2*ZX, where t1 and t2 are both proportional coefficients, and 1.05≤t1≤1.15, 0.85≤t2≤0.95; the high value of the output YCmax and the low value of the output YCmin constitute the output screening range, the high value of the output LCmax and the low value of the output LCmin constitute the outflow screening range, and the high value of the load display ZXmax and the low value of the load display ZXmin constitute the load display screening range; the historical operation data where the output voltage value, the output current value and the load value are respectively within the output screening range, the outflow screening range and the load display screening range are marked as configuration data;

[0041] The user selects a configuration mode to configure internal operating parameters. The configuration modes include energy saving priority mode, fault priority mode and processing priority mode.

[0042] The specific process of configuring internal operating parameters using the energy-saving priority mode includes: arranging the configuration data in order of energy consumption values ​​from small to large to obtain an energy-saving priority sequence, marking the top L1 configuration data in the energy-saving priority sequence as energy-saving priority data, L1 is a numerical constant, and the specific value of L1 is set by the management personnel; the speed configuration range is composed of the maximum operating speed value and the minimum operating speed value in the energy-saving priority data, and the torque configuration range is composed of the maximum operating torque value and the minimum operating torque value in the energy-saving priority data, and the speed configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters.

[0043] The specific process of configuring the internal operating parameters using the fault priority mode includes: arranging the configuration data in order of the operating speed value from large to small to obtain a speed sequence, decomposing the speed sequence into several speed intervals, the number of configuration data in each speed interval is L1, marking the configuration data that fails during the operating period as fault data, marking the number of fault data in the speed interval as the fault value of the speed interval, the speed configuration range is composed of the maximum boundary value and the minimum boundary value of the speed interval with the smallest fault value, and the torque configuration range is composed of the maximum value and the minimum value of the operating torque value of the configuration data in the speed interval with the smallest fault value; the speed configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters.

[0044] The specific process of configuring the internal operating parameters using the processing priority mode includes: marking the fault processing time of the fault data in the speed range after the fault occurs as the processing value of the fault data, summing and averaging the processing values ​​of all the fault data in the speed range to obtain the timely value, the speed configuration range is composed of the maximum boundary value and the minimum boundary value of the speed range with the smallest timely value, and the torque configuration range is composed of the maximum operating torque value and the minimum operating torque value of the configuration data in the extrusion range with the smallest timely value; the torque configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters; different configuration logics can be adopted to configure the internal operating parameters through the energy-saving priority mode, the fault priority mode and the processing priority mode, and the different internal configuration parameters obtained can be suitable for different application environments and meet different user needs, thereby improving the applicability of the internal configuration parameters.

[0045] The verification processing module is used to verify and analyze the internal parameter configuration status of the situation awareness servo driver: the difference between the maximum boundary value and the minimum boundary value of the torque configuration range is marked as the torque range value JF, and the difference between the maximum boundary value and the minimum boundary value of the speed configuration range is marked as the speed range value SF. The verification coefficient JY of the internal configuration parameters is obtained by the formula JY=k1*JF+k2*SF, where k1 and k2 are both proportional coefficients, and k1>k2>1; the verification coefficient JY is compared with the preset verification threshold JYmax: if the verification coefficient JY is less than the verification threshold JYmax, it is determined that the coverage accuracy of the internal configuration parameters meets the requirements, and the internal configuration parameters are processed. The processor sends the information to the controller of the monitored object; if the verification coefficient JY is greater than or equal to the verification threshold JYmax, it is determined that the coverage accuracy of the internal configuration parameters does not meet the requirements, and the internal configuration parameters are indented: L1=L1-1 is set, the internal configuration parameters are re-acquired through the corresponding configuration mode and the verification coefficient JY is calculated, and so on, until the verification coefficient JY is less than the verification threshold JYmax; the internal parameter configuration status of the situation awareness servo drive is verified and analyzed, the boundary values ​​of the speed configuration range and the torque configuration range are numerically calculated to obtain the verification coefficient, and the coverage accuracy of the internal configuration parameters is fed back through the verification coefficient, thereby ensuring the accuracy of the configuration range of the internal configuration parameters.

[0046] Embodiment 2: Figure 3 As shown, the present invention also proposes a situation awareness servo drive operation monitoring method based on artificial intelligence, which includes the following steps:

[0047] Step 1: Collect external parameters of the situation awareness servo driver to obtain an external parameter set;

[0048] Step 2: Analyze the internal operating parameters of the situation awareness servo drive according to the external parameter set and filter the configuration data;

[0049] Step 3: Perform internal operation parameter configuration according to the configuration mode selected by the user to obtain internal configuration parameters;

[0050] Step 4: Verify and analyze the internal parameter configuration status of the situation awareness servo driver and determine whether the coverage accuracy of the internal configuration parameters meets the requirements. If the requirements are not met, the internal configuration parameters are indented.

[0051] The present invention also includes a readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned situational awareness servo drive operation monitoring method based on artificial intelligence is implemented. Ordinary technicians in this field can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiments, and the aforementioned storage medium includes: ROM, RAM, disk or CD-ROM and other media that can store program codes.

[0052] The present invention also relates to a terminal, specifically comprising: a processor and a memory; the memory is used to store a computer program, the processor is connected to the memory, and is used to execute the computer program stored in the memory, so that the terminal executes any artificial intelligence-based situation awareness servo drive operation monitoring method, specifically, the memory includes: ROM, RAM, disk, U disk, memory card or CD and other media that can store program codes.

[0053] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc., and can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0054] When the present invention is working, an external parameter set is collected for the external parameters of the situation awareness servo driver, historical operation data is screened through the external parameter set to obtain configuration data, a configuration mode is selected according to user needs to configure internal operation parameters to obtain a speed configuration range and a torque configuration range, boundary values ​​of the speed configuration range and the torque configuration range are numerically calculated to obtain a calibration coefficient, and whether the coverage accuracy of the internal configuration parameters meets the requirements is determined through the calibration coefficient, and if the requirements are not met, the internal configuration parameters are indented.

[0055] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0056] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula JY = k1*JF+k2*SF; technicians in this field collect multiple groups of sample data and set corresponding calibration coefficients for each group of sample data; substitute the set calibration coefficients and the collected sample data into the formula, any two formulas constitute a set of two-variable linear equations, screen the calculated coefficients and take the average, and obtain the values ​​of k1 and k2 as 2.83 and 2.15 respectively;

[0057] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding calibration coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the calibration coefficient is proportional to the value of the speed range value.

[0058] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0059] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The situational awareness servo drive operation monitoring system based on artificial intelligence is characterized by: It includes a processor, the processor is communicatively connected to an external acquisition module, an internal balancing module, a controller and a database, and the internal balancing module is also communicatively connected to a verification processing module; The external acquisition module is used to collect external parameters of the situation awareness servo drive: mark the situation awareness servo drive as a monitoring object, set a number of monitoring time points with the same time interval, and obtain the external parameter set of the monitoring object at the monitoring time point; send the external parameter set to the internal balancing module through the processor; The internal balancing module is used to perform configuration analysis on the internal operating parameters of the situation awareness servo drive according to the external parameter set: retrieve the historical operating data of the monitored object through the database, and filter the historical operating data through the external parameter set to obtain the configuration data; The user selects a configuration mode to configure the internal operating parameters to obtain the speed configuration range and the torque configuration range. The speed configuration range and the torque configuration range constitute the internal configuration parameters. The configuration modes include energy-saving priority mode, fault priority mode and processing priority mode. The verification processing module is used to verify and analyze the internal parameter configuration state of the situation awareness servo driver and obtain the verification coefficient JY of the internal configuration parameters, and to determine whether the coverage accuracy of the internal configuration parameters meets the requirements through the verification coefficient JY.

2. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 1 is characterized in that: The process of acquiring the external parameter set includes: acquiring the output voltage value and current value of the monitored object connected to the power grid and marking them as the output voltage value YC and the output flow value LC, acquiring the operating load of the monitored object and marking it as the load display value ZX, and marking the output voltage value YC, the output flow value LC and the load display value ZX as the external parameter set of the monitored object.

3. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 2 is characterized in that: The configuration parameter acquisition process includes: the historical operation data includes the output voltage value, output current value, load value, operating speed value, operating torque value and energy consumption value of the monitored object when connected to the power grid at the corresponding monitoring time point; the period formed from the corresponding monitoring time point to the next monitoring time point of the historical operation data is marked as the operation period; the total energy consumption of the monitored object in the operation period is marked as the energy consumption value; the high pressure value YCmax and the low pressure value YCmin are obtained by the formula YCmax=t1*YC and YCmin=t2*YC, and the pressure screening range is formed by the high pressure value YCmax and the low pressure value YCmin; The outflow high value LCmax and the outflow low value LCmin are obtained by the formula LCmax=t1*LC and LCmin=t2*LC, and the outflow high value LCmax and the outflow low value LCmin constitute the outflow screening range; The high value ZXmax and the low value ZXmin of the load display are obtained by the formula ZXmax=t1*ZX and ZXmin=t2*ZX, wherein t1 and t2 are both proportional coefficients, and 1.05≤t1≤1.15, 0.85≤t2≤0.95; the high value ZXmax and the low value ZXmin of the load display constitute the load display screening range; The historical operation data whose output voltage value, output current value and load value are respectively within the pressure-out screening range, the outflow screening range and the load display screening range are marked as configuration data.

4. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 3 is characterized in that: The specific process of configuring internal operating parameters using the energy-saving priority mode includes: arranging the configuration data in order of energy consumption values ​​from small to large to obtain an energy-saving priority sequence, marking the top L1 configuration data in the energy-saving priority sequence as energy-saving priority data, forming a speed configuration range from the maximum operating speed value and the minimum operating speed value in the energy-saving priority data, forming a torque configuration range from the maximum operating torque value and the minimum operating torque value in the energy-saving priority data, and sending the speed configuration range and the torque configuration range as internal configuration parameters to the verification processing module.

5. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 3 is characterized in that: The specific process of configuring the internal operating parameters using the fault priority mode includes: arranging the configuration data in order of the operating speed value from large to small to obtain a speed sequence, decomposing the speed sequence into several speed intervals, the number of configuration data in each speed interval is L1, marking the configuration data that fails during the operating period as fault data, marking the number of fault data in the speed interval as the fault value of the speed interval, the speed configuration range is composed of the maximum boundary value and the minimum boundary value of the speed interval with the smallest fault value, and the torque configuration range is composed of the maximum value and the minimum value of the operating torque value of the configuration data in the speed interval with the smallest fault value; the speed configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters.

6. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 5 is characterized in that: The specific process of configuring internal operating parameters using the processing priority mode includes: marking the fault processing time of the fault data in the speed range after the fault occurs as the processing value of the fault data, summing and averaging the processing values ​​of all fault data in the speed range to obtain the timely value, the speed configuration range is composed of the maximum boundary value and the minimum boundary value of the speed range with the smallest timely value, and the torque configuration range is composed of the maximum value and the minimum value of the operating torque of the configuration data in the extrusion range with the smallest timely value; the torque configuration range and the torque configuration range are sent to the verification processing module as internal configuration parameters.

7. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 1 is characterized in that: The process of obtaining the verification coefficient JY of the internal configuration parameters includes: marking the difference between the maximum boundary value and the minimum boundary value of the torque configuration range as the torque range value JF, marking the difference between the maximum boundary value and the minimum boundary value of the speed configuration range as the speed range value SF, and performing numerical calculation on the torque range value JF and the speed range value SF to obtain the verification coefficient JY.

8. The artificial intelligence-based situational awareness servo drive operation monitoring system according to claim 7 is characterized in that: The specific process of determining whether the coverage accuracy of the internal configuration parameters meets the requirements includes: comparing the verification coefficient JY with the preset verification threshold JYmax: if the verification coefficient JY is less than the verification threshold JYmax, it is determined that the coverage accuracy of the internal configuration parameters meets the requirements, and the internal configuration parameters are sent to the controller of the monitored object through the processor; if the verification coefficient JY is greater than or equal to the verification threshold JYmax, it is determined that the coverage accuracy of the internal configuration parameters does not meet the requirements, and the internal configuration parameters are indented: L1=L1-1 is set, the internal configuration parameters are re-acquired through the corresponding configuration mode and the verification coefficient JY is calculated, and so on, until the verification coefficient JY is less than the verification threshold JYmax.

9. A situational awareness servo drive operation monitoring method based on artificial intelligence, characterized in that: The artificial intelligence-based situation awareness servo drive operation monitoring system applied to any one of claims 1 to 8 comprises the following steps: Step 1: Collect external parameters of the situation awareness servo driver to obtain an external parameter set; Step 2: Analyze the internal operating parameters of the situation awareness servo drive according to the external parameter set and filter the configuration data; Step 3: Perform internal operation parameter configuration according to the configuration mode selected by the user to obtain internal configuration parameters; Step 4: Verify and analyze the internal parameter configuration status of the situation awareness servo driver and determine whether the coverage accuracy of the internal configuration parameters meets the requirements. If the requirements are not met, the internal configuration parameters are indented.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for monitoring the operation of a servo drive based on situational awareness based on artificial intelligence as described in claim 9 is implemented.

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