Control loop steady-state condition step response identification method and system

Abstract

The application provides a kind of control loop steady state condition step response identification method and system, belong to DCS control system technical field.The method includes: based on the operation sequence corresponding to each control loop, determine the corresponding operation time point and duration;Based on the operation time point, duration and the observation sequence after time filtering processing corresponding to each control loop, determine the end time of corresponding step response;Based on the operation time point, duration, end time of step response and the observation sequence after time filtering processing corresponding to each control loop, calculate the corresponding step response credibility;Based on the step response credibility calculation result corresponding to each control loop, determine the corresponding step response curve.Thereby automatically identify the step response curve in the steady state condition of the historical operation data of each control loop, provide technical support for the identification and analysis of the controlled object for PID parameter optimization setting.

Description

Technical Field

[0001] This invention relates to the field of DCS control system technology, specifically to a method for identifying the steady-state step response of a control loop, a system for identifying the steady-state step response of a control loop, a machine-readable storage medium, and an electronic device. Background Technology

[0002] In the DCS control system of a refining and chemical plant, a large number of control loops are typically established to ensure the stable operation of the entire DCS system. These control loops can precisely control various process parameters, such as temperature, pressure, and liquid level. These control loops play a crucial role in the refining and chemical plant, improving production efficiency, reducing energy consumption, and minimizing human error through automated control, thereby ensuring production safety and product quality. However, in actual production, due to equipment aging and process adjustments, the performance of some loops deteriorates, resulting in the inability to fully utilize all control loops, usually requiring PID parameter optimization.

[0003] PID parameter optimization methods include: experience-based PID tuning methods, which tune PID parameters based on device characteristics and human experience; process model-based PID tuning methods, which analyze the control loop manually or with the aid of professional PID tuning tools to calculate process model parameters such as model gain and time constant, and then calculate PID parameters using process model-based tuning methods; and data analysis-based PID tuning methods, which require certain data from the control loop, analyze the control loop manually or with the aid of professional PID tuning tools to establish a process data model, and provide initial PID parameters or improve the current PID parameters based on the analysis results.

[0004] The primary condition for PID parameter tuning is providing a clear stimulus, such as obtaining a step response curve, to identify the controlled object or analyze the regulation process. Existing control loops primarily obtain step responses by giving an operation and then manually observing the trend or directly tuning the PID parameters, without assessing the reliability of the step response. Since refining and chemical plants often experience numerous disturbances in actual production, failing to assess steady-state conditions will affect the accuracy of the controlled object model identification. However, during the operation of refining and chemical plants, it is usually impossible to conduct large-scale stimulus tests to avoid control runaway. Historical control loop data contains regulation processes that can serve as step response curves.

[0005] Therefore, how to automatically identify the step response curves under steady-state conditions in the historical operating data of each control loop, so as to provide data support for PID parameter tuning, is an urgent problem to be solved. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for identifying the step response under steady-state conditions of a control loop, so as to at least solve the problem of how to automatically identify the step response curve under steady-state conditions in the historical operating data of each control loop, so as to provide data support for PID parameter tuning.

[0007] To achieve the above objectives, a first aspect of the present invention provides a method for identifying the step response of a control loop under steady-state conditions, comprising:

[0008] Based on the historical operating data of each control loop, determine the corresponding operation sequence and observation sequence for each control loop;

[0009] Based on the operation sequence corresponding to each control loop, determine the operation time point and duration corresponding to each control loop;

[0010] Based on the operation time point, duration, and observation sequence after time filtering for each control loop, the end time of the step response for each control loop is determined.

[0011] Based on the operation time point, duration, end time of step response, and observation sequence after time filtering for each control loop, the confidence level of the step response for each control loop is calculated.

[0012] Based on the calculation results of the step response reliability of each control loop, the step response curve of each control loop is determined.

[0013] Optionally, the above-mentioned determination of the operation sequence and observation sequence corresponding to each control loop based on the historical operating data of each control loop includes:

[0014] Based on the historical operating data of each control loop, an operating data sequence corresponding to each preset relevant parameter of each control loop is established; wherein, the operating data sequence corresponding to each preset relevant parameter includes the control mode time sequence Mode[I], the output value sequence MV[I], the measured value sequence PV[I], and the set value sequence SP[I]; wherein, I = {1, 2, ..., n}, and n is the number of data acquisitions;

[0015] Based on the control state reflected by each data point in the control mode time series Mode[I], a corresponding assignment scheme is matched to assign values ​​to the corresponding operation sequence and observation sequence; among which,

[0016] The assignment schemes include manual state assignment schemes and automatic state assignment schemes;

[0017] The manual state assignment scheme is used to assign values ​​to the corresponding operation sequence and observation sequence when the control state reflected by each data in the control mode time series Mode[I] is manual.

[0018] The automatic state assignment scheme is used to assign values ​​to the corresponding operation sequence and observation sequence when the control state reflected by each data in the control mode time series Mode[I] is automatic.

[0019] Optionally, based on the control state reflected by each data point in the control mode time series Mode[I], the corresponding assignment scheme is matched to assign values ​​to the corresponding operation sequence and observation sequence, including:

[0020] If the control states reflected by each data in the control mode time series Mode[I] include manual and automatic states, then the first sequence range is obtained by identifying the longest continuous sequence range in the control mode time series Mode[I] that belongs to the same control state.

[0021] When the control state reflected by each data in the first sequence range is manual, the operation sequence and observation sequence corresponding to the first sequence range are assigned values ​​using the manual state assignment scheme;

[0022] When the control state reflected by the data in the first sequence range is automatic, the operation sequence and observation sequence corresponding to the first sequence range are assigned values ​​using the automatic state assignment scheme.

[0023] Optionally, the above manual state assignment schemes include:

[0024] The output value sequence MV[I] is used as the operation sequence Opreates[I], and the measurement value sequence PV[I] is used as the observation sequence Observes[I].

[0025] Optionally, the above automatic state assignment scheme includes:

[0026] The setpoint sequence SP[I] is used as the operation sequence Opreates[I], and the deviation between the measured value sequence PV[I] and the setpoint sequence SP[I] is used as the observation sequence Observes[I].

[0027] Optionally, the above determination of the operation time point and duration corresponding to each control loop based on the operation sequence corresponding to each control loop includes:

[0028] Determine the threshold XL for the number of consecutive no-operation data in the operation sequence corresponding to each control loop;

[0029] For each control loop, based on the corresponding threshold XL of the number of consecutive no-operation data, from time point XL+1 to time point n, the corresponding operation sequence Opreates[N1] is traversed to determine the corresponding operation time point; where N1={XL+1,...,n}, n is the number of data acquisitions, in the operation sequence Opreates[N1], the XL data before the operation time point are all the first value and the XL data after the operation time point are all the second value, and the first value and the second value are not equal;

[0030] For each control loop, from the operation time point to time point n, the corresponding operation sequence Opreates[N2] is traversed to determine the corresponding duration; where N2 = {Ti, ..., n}, Ti represents the operation time point, and the data of the time point in the operation sequence Opreates[N2] between the operation time point Ti and the end time point Ts of the duration are all second values.

[0031] Optionally, the time filtering rules for the above observation sequences include:

[0032] Based on the filtering time FilterTime and the preset sampling time interval SampleTime, the observation sequence is subjected to time filtering to obtain the time-filtered observation sequence NObserves[i]; where...

[0033]

[0034] NObserves[i] = Observes[i] * (1 - Filter) + Filter * Observes[i - 1], FilterTime > SampleTime, i ∈ I = {1, 2, ..., n}, where n is the number of data collections.

[0035] Optionally, the above determination of the end time of the step response corresponding to each control loop, based on the corresponding operation time point, duration, and observation sequence after time filtering, includes:

[0036] For each control loop, based on the corresponding time-filtered observation sequence, the corresponding fluctuation sequence Steady[I] is calculated; where, K represents the time range for calculating the fluctuation of the observed sequence, Ts represents the cutoff point of the duration, and Ti represents the operation time point;

[0037] For each control loop, from the corresponding time point Ti-1 to the corresponding end time point Ts of the duration, traverse the corresponding fluctuation sequence and determine the time corresponding to the maximum value of the corresponding fluctuation sequence as the end time of the corresponding step response; where Steady[Te]≥Steady[i], i∈I={Ti-1,Ti,Ti+1,...,Ts}, and Te represents the time corresponding to the maximum value of the fluctuation sequence.

[0038] Optionally, the confidence level of the step response for each control loop is calculated based on the corresponding operating time point, duration, end time of the step response, and time-filtered observation sequence, including:

[0039] Based on the operating time point and the end time of the step response corresponding to each control loop, calculate the steady-state operating time point Tes after the step response corresponding to each control loop; where Tes = 2Te - Ti + 1, Te is the end time of the step response corresponding to each control loop, and Ti is the operating time point corresponding to each control loop.

[0040] According to the formula Determine the stable operating conditions of each control loop before the start of the step response and at the end of the step response to obtain the first stable operating condition judgment value Rel_se corresponding to each control loop; where Steady[Ti-1] represents the data of the fluctuation sequence Steady[I] at time point Ti-1, and Steady[Tes] represents the data of the fluctuation sequence Steady[I] at the steady-state operating condition time point Tes after the step response.

[0041] According to the formula Determine the stable operating condition of each control loop after the step response, and obtain the second stable operating condition judgment value Rel_sd corresponding to each control loop;

[0042] According to the formula Determine the excitation level of the step response of each control loop to obtain the excitation level judgment value Rel_sf corresponding to each control loop;

[0043] Based on the first stable condition judgment value Rel_se, the second stable condition judgment value Rel_sd, and the step response excitation degree judgment value Rel_sf corresponding to each control loop, the reliability of the step response corresponding to each control loop is determined.

[0044] Optionally, the formula for calculating the confidence level of the step response for each control loop is as follows:

[0045]

[0046] Here, Rel represents the confidence level of the step response.

[0047] Optionally, after calculating the steady-state operating time point Tes following the step response of each control loop, the method further includes:

[0048] For each control loop, if the steady-state condition time point after the corresponding step response is greater than the end time point of the duration and the value of the end time point of the duration is the same as the value of the number of data acquisitions, the acquired historical operating data is supplemented. Based on the supplemented historical operating data, the corresponding operation sequence, observation sequence, operation time point, duration, and end time of the step response are re-determined.

[0049] If the steady-state condition time point after the corresponding step response is greater than the end time point of the duration, and the value of the end time point of the duration is less than the value of the number of data acquisitions, then the corresponding control loop cannot be used to determine the reliability of the step response.

[0050] Optionally, based on the calculation results of the step response reliability of each control loop, the step response curve corresponding to each control loop is determined, including:

[0051] For each control loop, when the calculated confidence result of the corresponding step response is greater than the preset threshold, the data from the operation time point Ti to the end time Te of the step response in the corresponding historical operation data is determined as the corresponding step response curve.

[0052] Optionally, the above-mentioned method for identifying the step response of the control loop under steady-state conditions further includes:

[0053] According to the preset sampling time interval, the historical operating data of the control loop is acquired through the data acquisition interface; the historical operating data of the control loop includes measured values, set values, control mode (MODE) values, and output values.

[0054] A second aspect of the present invention provides a control loop steady-state step response identification system, comprising:

[0055] The processing sequence determination module is used to determine the operation sequence and observation sequence corresponding to each control loop based on the historical operation data of each control loop;

[0056] The operation sequence processing module is used to determine the operation time point and duration of each control loop based on the operation sequence corresponding to each control loop.

[0057] The step response end time determination module is used to determine the end time of the step response for each control loop based on the operation time point, duration, and observation sequence after time filtering.

[0058] The step response confidence calculation module is used to calculate the confidence of the step response of each control loop based on the operation time point, duration, end time of the step response, and the observation sequence after time filtering.

[0059] The step response curve determination module is used to determine the step response curve corresponding to each control loop based on the step response reliability calculation results corresponding to each control loop.

[0060] In a third aspect, the present invention provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the control loop steady-state step response identification method described above.

[0061] In a fourth aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for identifying the step response of a control loop in steady-state conditions.

[0062] The above technical solution provides a method and system for identifying the step response of a control loop under steady-state conditions. By analyzing historical operating data of each control loop, the system determines the operation time of each loop to identify the corresponding operation sequence and observation sequence. Combining the fluctuations reflected in the operation and observation sequences, the system assesses the steady-state condition of each control loop, identifying the operation time point, duration, and end time of the step response for each loop. After identification, the system calculates the reliability of the step response for each control loop based on the operation time point, duration, end time of the step response, and the time-filtered observation sequence, thus evaluating the reliability of the step response. Furthermore, based on the calculated reliability of the step response for each control loop, the system determines the step response curve for each loop, ensuring the data reliability of the step response curve. This provides technical support for the identification and analysis of the controlled object in PID parameter optimization tuning, facilitating the optimization of PID parameters in the control loop. This method and system can automatically identify the step response curves under steady-state conditions in the historical operating data of each control loop, providing data support for PID parameter tuning. It can also avoid scenarios where step response tests are not applicable, and can evaluate the reliability of step response curves. This is beneficial for optimizing and improving the control loops of refining and chemical plants, and improving the stable operation of the plants.

[0063] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0064] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0065] Figure 1 This is a flowchart of a method for identifying the step response of a control loop under steady-state conditions, provided by one embodiment of the present invention.

[0066] Figure 2 This is a flowchart of another method for identifying the steady-state step response of a control loop provided by one embodiment of the present invention;

[0067] Figure 3 This is a schematic diagram of a step response curve provided in one embodiment of the present invention;

[0068] Figure 4 This is a block diagram of a control loop steady-state step response identification system provided by one embodiment of the present invention;

[0069] Figure 5 This is a schematic diagram of an electronic device structure provided by a preferred embodiment of the present invention.

[0070] Explanation of reference numerals in the attached figures

[0071] 10 - Electronic device, 100 - Processor, 101 - Memory, 102 - Computer program. Detailed Implementation

[0072] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0073] Example 1

[0074] Figure 1 This is a flowchart of a method for identifying the steady-state step response of a control loop according to one embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a method for identifying the step response of a control loop under steady-state conditions, comprising:

[0075] S110: Based on the historical operating data of each control loop, determine the corresponding operation sequence and observation sequence for each control loop;

[0076] In detail, the above-mentioned determination of the operation sequence and observation sequence corresponding to each control loop based on the historical operating data of each control loop includes: establishing the operation data sequence corresponding to each preset relevant parameter of each control loop based on the historical operating data of each control loop; wherein, the operation data sequence corresponding to each preset relevant parameter includes the control mode time sequence Mode[I], the output value sequence MV[I], the measured value sequence PV[I], and the setpoint sequence SP[I]; wherein, I = {1, 2, ..., n}, and n is the number of data acquisitions; the control state reflected by each data in the control mode time sequence Mode[I] is judged one by one. Based on the control state reflected by each data point in the control mode time series Mode[I], a corresponding assignment scheme is matched to assign values ​​to the corresponding operation sequence and observation sequence. The assignment scheme includes a manual state assignment scheme and an automatic state assignment scheme. The manual state assignment scheme is used to assign values ​​to the corresponding operation sequence and observation sequence when the control state reflected by each data point in the control mode time series Mode[I] is in manual state. The automatic state assignment scheme is used to assign values ​​to the corresponding operation sequence and observation sequence when the control state reflected by each data point in the control mode time series Mode[I] is in automatic state.

[0077] Furthermore, the above-mentioned matching of the corresponding assignment scheme based on the control state reflected by each data in the control mode time series Mode[I] to assign values ​​to the corresponding operation sequence and observation sequence includes: if the control state reflected by each data in the control mode time series Mode[I] includes manual state and automatic state, then the sequence range in the control mode time series Mode[I] that belongs to the same control state and has the longest continuous time is identified to obtain the first sequence range; if the control state reflected by each data in the first sequence range is manual state, the operation sequence and observation sequence corresponding to the first sequence range are assigned values ​​using the manual state assignment scheme; if the control state reflected by each data in the first sequence range is automatic state, the operation sequence and observation sequence corresponding to the first sequence range are assigned values ​​using the automatic state assignment scheme.

[0078] The above manual state assignment scheme includes: using the output value sequence MV[I] as the operation sequence Opreates[I], and using the measurement value sequence PV[I] as the observation sequence Observes[I].

[0079] The above-mentioned automatic state assignment scheme includes: using the set value sequence SP[I] as the operation sequence Opreates[I], and using the deviation between the measured value sequence PV[I] and the set value sequence SP[I] as the observation sequence Observes[I].

[0080] Specifically, in manual mode, the control loop requires manual operation of the output value (MV value) to adjust the controlled variable. In automatic mode, the control loop requires manual operation of the setpoint (SP value) to adjust the controlled variable. Therefore, it is first necessary to determine the control mode (MODE value) to identify the required time series of operating values ​​(i.e., the operating sequence) and the observation sequence. The specific process for identifying the operating sequence and the observation sequence is as follows:

[0081] The first step is to determine the control state: the control state of each control mode time series Mode[I] (I = {1, 2, ..., n}) is determined one by one, where n is the total number of sequences.

[0082] The second step is to determine the operation sequence and observation sequence based on the control state of each data point in the control mode time series Mode[I]. The specific process is as follows:

[0083] (1) If Mode[I] is in manual mode, then the output value sequence MV[I] is used as the operation sequence Opreates[I], and the measurement value sequence PV[I] is used as the observation sequence Observes[I], that is, Opreates[I] = MV[I], Observes[I] = PV[I];

[0084] (2) If Mode[I] is in automatic mode, then the set value sequence SP[I] is used as the operation sequence Opreates[I], and the deviation between the measured value sequence PV[I] and the set value sequence SP[I] is used as the observation sequence Observes[I], that is, Opreates[I] = SP[I], Observes[I] = PV[I] - SP[I];

[0085] (3) If Mode[I] has manual and automatic states, identify the longest continuous sequence range of the same state, and then assign values ​​to the operation sequence and observation sequence in the manner of (1) and (2).

[0086] S120: Based on the operation sequence corresponding to each control loop, determine the operation time point and duration corresponding to each control loop;

[0087] In detail, the above-mentioned determination of the operation time point and duration for each control loop based on the operation sequence corresponding to each control loop includes:

[0088] Determine the threshold XL for the number of consecutive no-operation data in the operation sequence corresponding to each control loop; for each control loop, based on the corresponding threshold XL for the number of consecutive no-operation data, traverse the corresponding operation sequence Opreates[N1] from time point XL+1 to time point n to determine the corresponding operation time point; where N1={XL+1,...,n}, n is the number of data acquisitions, and in the operation sequence Opreates[N1], the XL data before the operation time point are all the first value and the XL data after the operation time point are all the second value, and the first value and the second value are not equal;

[0089] Specifically, first, a threshold XL is defined for the number of consecutive no-operation data in the operation sequence corresponding to each control loop. Then, the operation time point Ti is identified. The specific process is as follows: For each control loop, from time point XL+1 to time point n, the corresponding operation sequence Opreates[N1] is traversed. If the XL cycles of data before time point Ti are all the value OldValve (i.e., the first value) and the XL cycles of data after time point Ti are all the value NewValve (i.e., the second value), and OldValve is not equal to NewValve, then time point Ti is the operation time point. That is: Opreates[Ti-XL]~Opreates[Ti-1]=OldValve, Opreates[Ti]~Opreates[Ti+XL-1]=NewValve, OldValve!=NewValve.

[0090] For each control loop, from the operation time point to time point n, the corresponding operation sequence Opreates[N2] is traversed to determine the corresponding duration; where N2 = {Ti, ..., n}, Ti represents the operation time point, and the data of the time point in the operation sequence Opreates[N2] between the operation time point Ti and the end time point Ts of the duration are all second values.

[0091] Specifically, from Ti to the total number of sequences n, traverse all operation sequences Opreates[N2]. If the value from operation time point Ti to time point Ts is NewValve, then Ts is the end time point of the duration, and Ts has a maximum value of n. That is: Opreates[Ti] ~ Opreates[Ts] = NewValve.

[0092] S130: Based on the operation time point, duration, and observation sequence after time filtering for each control loop, determine the end time of the step response for each control loop.

[0093] In some embodiments of this example, the time filtering rules for the above-mentioned observation sequence include: performing time filtering on the observation sequence according to the filtering time FilterTime and the preset sampling time interval SampleTime to obtain the time-filtered observation sequence NObserves[i]; wherein, NObserves[1] = Observes[1], NObserves[i] = Observes[i] * (1 - Filter) + Filter * Observes[i - 1], FilterTime > SampleTime, i ∈ I = {1, 2, ..., n}, where n is the number of data collections.

[0094] Specifically, since the controlled parameters of the process control are continuous, in order to avoid interference from abnormal data, the observed sequence data is subjected to time filtering based on the filtering time FilterTime and the sampling time SampleTime to obtain the processed data NObserves[i].

[0095] In some embodiments of this example, determining the end time of the step response corresponding to each control loop based on the operation time point, duration, and observation sequence after time filtering for each control loop includes:

[0096] For each control loop, based on the corresponding time-filtered observation sequence, the corresponding fluctuation sequence Steady[I] is calculated; where, K represents the time range for calculating the fluctuation of the observed sequence, Ts represents the cutoff point of the duration, and Ti represents the operation time point;

[0097] Specifically, firstly, the fluctuation calculation time range K of the observation sequence of each control loop is defined, and then the fluctuation sequence is calculated. The specific process is as follows: from Ti-K to Ts, each data of the fluctuation sequence Steady[i] (i = Ti-1, Ti, Ti+1, ..., Ts) is calculated one by one according to NObserves[i].

[0098] For each control loop, from the corresponding time point Ti-1 to the corresponding end time point Ts of the duration, traverse the corresponding fluctuation sequence and determine the time corresponding to the maximum value of the corresponding fluctuation sequence as the end time of the corresponding step response; where Steady[Te]≥Steady[i], i∈I={Ti-1,Ti,Ti+1,...,Ts}, and Te represents the time corresponding to the maximum value of the fluctuation sequence.

[0099] Specifically, from Ti-1 to Ts, according to the wave sequence Steady[I], when time Te is the maximum value of the wave sequence, it is marked as the end time of the step response. Therefore, time Te is recorded as the end time of the step response.

[0100] S140: Calculate the confidence level of the step response for each control loop based on the operation time point, duration, end time of the step response, and the observation sequence after time filtering.

[0101] In detail, based on the operating time point, duration, end time of the step response, and time-filtered observation sequence corresponding to each control loop, the reliability of the step response for each control loop is calculated, including:

[0102] Based on the operating time point and the end time of the step response corresponding to each control loop, calculate the steady-state operating time point Tes after the step response corresponding to each control loop; where Tes = 2Te - Ti + 1, Te is the end time of the step response corresponding to each control loop, and Ti is the operating time point corresponding to each control loop.

[0103] Determine the stable operating conditions of each control loop before the start of the step response and at the end of the step response to obtain the first stable operating condition judgment value Rel_se corresponding to each control loop; where Steady[Ti-1] represents the data of the fluctuation sequence Steady[I] at time point Ti-1, and Steady[Tes] represents the data of the fluctuation sequence Steady[I] at the steady-state operating condition time point Tes after the step response.

[0104] Specifically, the rules for judging the stable operating conditions before and after the step response are as follows: when Steady[Ti-1]≈Steady[Tes], it means that it is at least one order of magnitude. That is, when Rel_se is close to 1, it means that the operating conditions before the step response starts are basically the same as the operating conditions after the step response is resolved. This indicates that the current step response is carried out under stable operating conditions and is less affected by or consistent with external disturbances.

[0105] According to the formula Determine the stable operating condition of each control loop after the step response, and obtain the second stable operating condition judgment value Rel_sd corresponding to each control loop;

[0106] Specifically, the rule for determining the stable operating condition after a step response is as follows: when When Rel_sd is close to 1, it indicates that there is no sudden change in the operating conditions after the step response ends.

[0107] According to the formula Determine the excitation level of the step response of each control loop to obtain the excitation level judgment value Rel_sf corresponding to each control loop;

[0108] Specifically, the rule for judging the excitation level of the step response is: when Steady[Te] is much greater than Steady[Ti-1], that is, when Rel_sf is close to 1, it means that the excitation level of the step response is greater, the impact of data interference on the model is smaller, and the model identification is more accurate.

[0109] Based on the first stable condition judgment value Rel_se, the second stable condition judgment value Rel_sd, and the step response excitation level judgment value Rel_sf corresponding to each control loop, the confidence level of the step response corresponding to each control loop is determined. The calculation formula for the confidence level of the step response corresponding to each control loop is as follows: Here, Rel represents the confidence level of the step response.

[0110] Specifically, the confidence level of the step response is determined based on the stable operating conditions before and after the step response, the stable operating conditions after the step response, and the excitation level of the step response. When the confidence level Rel is close to 100%, it indicates that the step response curve is easier to identify by the model. When Rel < 80%, it indicates that there is too much interference in the step response curve, and the model identification results may be distorted.

[0111] In some embodiments of this example, after calculating the steady-state operating time point Tes following the step response of each control loop, the method further includes:

[0112] For each control loop, if the steady-state condition time point after the corresponding step response is greater than the end time point of the duration and the value of the end time point of the duration is the same as the value of the number of data acquisitions, the acquired historical operating data is supplemented. Based on the supplemented historical operating data, the corresponding operation sequence, observation sequence, operation time point, duration, and end time of the step response are re-determined.

[0113] Specifically, when Tes>Ts and Ts=n, it indicates that the steady-state operating condition time series after the step response stabilizes is insufficient. The total number of samples n should be supplemented with subsequent operating data, at least Tes-Ts sequence period data should be supplemented, and the process from S110 to S130 should be repeated to redetermine the corresponding operation sequence, observation sequence, operation time point, duration and end time of the step response.

[0114] If the steady-state condition time point after the corresponding step response is greater than the end time point of the duration, and the value of the end time point of the duration is less than the value of the number of data acquisitions, then the corresponding control loop cannot be used to determine the reliability of the step response.

[0115] Specifically, when Tes > Ts and Ts < n, it indicates that a state transition has occurred under insufficient regulation of the steady-state working condition time series after the step response stabilizes. In this case, the batch of historical operation data cannot be used to judge the credibility of the step response.

[0116] S150: Determine the step response curve corresponding to each control loop based on the calculation results of the credibility of the step response corresponding to each control loop.

[0117] In some embodiments of this embodiment, the above-mentioned method of determining the step response curve corresponding to each control loop based on the calculation results of the credibility of the step response corresponding to each control loop includes: for each control loop, when the calculation result of the corresponding credibility of the step response is greater than a preset threshold, determine the data from the operation time point Ti to the end time Te of the step response in the corresponding historical operation data as the corresponding step response curve. Thus, the purpose of determining the data time range of the step response curve is achieved.

[0118] Specifically, this method analyzes the historical operation data of each control loop, judges the operation time of each control loop to determine the corresponding operation sequence and observation sequence of each control loop, evaluates the steady-state condition of the current working condition of each control loop by combining the fluctuation conditions of the corresponding data reflected in the operation sequence and the observation sequence, identifies the operation time point, duration, and end time of the step response corresponding to each control loop. After identification, according to the operation time point, duration, end time of the step response, and the observation sequence after time filtering processing corresponding to each control loop, calculate the credibility of the step response corresponding to each control loop, so as to evaluate the credibility of the step response. Furthermore, based on the calculation results of the credibility of the step response corresponding to each control loop, determine the step response curve corresponding to each control loop, ensuring the data credibility of the step response curve, providing technical support for the identification and analysis of the controlled object for PID parameter optimization tuning, and facilitating the PID parameter tuning optimization of the control loop. This method realizes the automatic identification of the step response curve under the steady-state working condition in the historical operation data of each control loop, provides data support for PID parameter tuning, avoids scenarios where the step response test is not applicable, and can evaluate the credibility of the step response curve, which is beneficial to the optimization and improvement of the control loop of the refining device and improves the smooth operation of the device.

[0119] In some embodiments of this embodiment, the above-mentioned method for identifying the step response of the steady-state working condition of the control loop further includes: obtaining the historical operation data of the control loop through the data acquisition interface at a preset sampling time interval; wherein, the historical operation data of the control loop includes the measured value, set value, control mode MODE value, and output value.

[0120] For example, for each control loop, every 30 seconds, the operating data of the control loop is collected, including the measured value (PV value), set value (SP value), control mode (MODE value), and output value (MV value), for a total of 70 sets of data, to establish the operating data sequence of the relevant parameters of each control loop.

[0121] Example 2

[0122] Please refer to Figure 2 and Figure 3 , Figure 2 This is a flowchart of another method for identifying the steady-state step response of a control loop according to one embodiment of the present invention. Figure 3 This is a schematic diagram of a step response curve provided by one embodiment of the present invention. The present invention provides a method for identifying the step response of a control loop under steady-state conditions, including: acquiring historical operating data of the control loop; identifying the operation sequence and observation sequence based on the control state; determining the operation time point and duration based on the operation sequence; processing the observation sequence data; calculating the fluctuation sequence; identifying the end time of the step response; determining the confidence level of the step response; and determining the step response curve.

[0123] 1. Acquire the operating data of the control loop through the data acquisition interface;

[0124] Specifically, every 30 seconds, the operating data of the control loop is collected, including measured values ​​(PV value), setpoint values ​​(SP value), control mode (MODE value), and output values ​​(MV value), totaling 70 sets of data, to establish an operating data sequence of relevant parameters of the control loop.

[0125] 2. Identify the operation sequence and observation sequence based on the control state;

[0126] 1) Control State Judgment: The control state of each control mode time series Mode[i] (i = 1, 2, ..., 70) is judged, where 70 is the total number of sequences. Since Mode[i] is always 0, i.e., manual mode, the output value sequence MV[i] is used as the operation sequence Opreates[i], and the measurement value sequence PV[i] is used as the observation sequence Observes[i]. That is: Opreates[i] = MV[i] (i = 1, 2, ..., 70); Observes[i] = PV[i] (i = 1, 2, ..., 70);

[0127] 3. Determine the operation time point Ti and duration Ts based on the operation sequence;

[0128] 1) Define a threshold of XL = 10 for the number of consecutive data without operations;

[0129] 2) Identify the operation time point Ti = 24: From 11 to the total number of sequences 70, traverse all operation sequences Opreates. If the data in the 10 cycles before time point 24 is all 50 and the data in the 10 cycles after time point 24 is all 60, then time point 24 is the operation time point. That is:

[0130] Opreates

[14] ~Opreates

[23] =50; Opreates

[24] ~Opreates

[33] =60;

[0131] 3) Identification duration Ts = 70: From 24 to the total number of sequences 70, traverse all operation sequences Opreates. If the value from operation time point 24 to 70 is 60, then Ts is 70. That is:

[0132] Opreates

[24] ~Opreates

[70] =60;

[0133] 4. Perform data processing on the observed sequence data;

[0134] Since the controlled parameters in the process control are continuous, to avoid interference from abnormal data, and given that the sampling time is 30s, the filtering time FilterTime = 240s is set to perform time filtering on the observed sequence data, resulting in the processed NObserves[i]. Then: NObserves[1] = Observes[1],

[0135] NObserves[i]=Observes[i]*(1-0.22)+0.22*Observes[i-1];

[0136] 5. Calculate the fluctuation sequence;

[0137] 1) Define the fluctuation calculation time range as K = 20;

[0138] 2) Calculate the fluctuation sequence: From 4 to 70, calculate the fluctuation sequence Steady[i] (i = 23, 24, 25, ..., 70) one by one according to NObserves[i]. For example:

[0139] 6. Identify the end time Te of the step response;

[0140] From time point 23 to 70, according to the fluctuation sequence Steady[i], when time 39 is the maximum value of the fluctuation sequence, it is marked as the end time Te = 39 of the step response. That is: Steady

[39] ≥ Steady[i] (i = 23, 34, ..., 70);

[0141] 7. Determine the reliability of the step response;

[0142] 1) Define the steady-state operating time Tes after the step response: Tes = 2 * 39 - 24 + 1 = 55;

[0143] 2) Calculate the confidence level of the step response:

[0144] (1) Determining the stable operating condition at the beginning and end: When Steady[Ti-1]≈Steady[Tes], it is at least one order of magnitude larger, i.e., Rel_se is close to 1, indicating that the operating condition at the beginning of the step response is basically the same as the operating condition after the step response is resolved. That is:

[0145] (2) Determining the stable operating condition after the step response, when

[0146] When Rel_sd approaches 1, it indicates that there is no sudden change in the operating conditions after the step response ends. That is:

[0147] (3) Determining the excitation level of the step response: When Steady[Te] is much larger than Steady[Ti] (at least one order of magnitude difference), i.e., Rel_sf is close to 1, it indicates that the excitation level of the step response is greater, the impact of data interference on the model is smaller, and the model identification is more accurate. That is:

[0148] (4) Calculate the confidence level of the step response: Determine the confidence level of the step response based on the steady-state conditions at the beginning and end, the steady-state conditions after the step response, and the excitation level of the step response. That is: The step response confidence level Rel is 91.06%, indicating that the step response curve is reliable.

[0149] 8. Determine the step response curve;

[0150] Based on the calculation process in 2-7, when the confidence level Rel is 91.06%, which is greater than the critical value, it can be determined that the data from time 24 to 39 in the original running data are step response curves.

[0151] Example 3

[0152] Figure 4 This is a block diagram of a control loop steady-state step response identification system according to one embodiment of the present invention. Figure 4 As shown, an embodiment of the present invention provides a step response identification system for steady-state operation of a control loop, comprising:

[0153] The processing sequence determination module is used to determine the operation sequence and observation sequence corresponding to each control loop based on the historical operation data of each control loop;

[0154] The operation sequence processing module is used to determine the operation time point and duration of each control loop based on the operation sequence corresponding to each control loop.

[0155] The step response end time determination module is used to determine the end time of the step response for each control loop based on the operation time point, duration, and observation sequence after time filtering.

[0156] The step response confidence calculation module is used to calculate the confidence of the step response of each control loop based on the operation time point, duration, end time of the step response, and the observation sequence after time filtering.

[0157] The step response curve determination module is used to determine the step response curve corresponding to each control loop based on the step response reliability calculation results corresponding to each control loop.

[0158] Specifically, the system analyzes historical operating data of each control loop to determine its operation time, thereby identifying the corresponding operation sequence and observation sequence. It then assesses the steady-state condition of each control loop by combining the fluctuations reflected in the operation and observation sequences. This process identifies the operation time point, duration, and step response end time of each control loop. After identification, the system calculates the step response reliability of each control loop based on the operation time point, duration, step response end time, and time-filtered observation sequence, thus evaluating the reliability of the step response. Furthermore, based on the calculated step response reliability of each control loop, the system determines the step response curve for each control loop, ensuring the data reliability of the step response curves. This provides technical support for the identification and analysis of the controlled object in PID parameter optimization tuning, facilitating the optimization of PID parameters for control loops. This system can automatically identify the step response curves under steady-state conditions in the historical operating data of each control loop, providing data support for PID parameter tuning. It can also avoid scenarios where step response tests are not applicable and perform reliability assessment of step response curves, which is beneficial for optimizing and improving the control loops of refining and chemical plants and improving the stable operation of the plants.

[0159] Example 4

[0160] The present invention provides a machine-readable storage medium storing instructions that, when executed by a processor 100, configure the processor 100 to perform the above-described control loop steady-state step response identification method.

[0161] Machine-readable storage media include both permanent and non-permanent, removable and non-removable media, which can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0162] The present invention also provides an electronic device 10, which includes a memory 101, a processor 100, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, it implements the above-described method for identifying the step response of the control loop steady-state condition.

[0163] like Figure 5 The diagram shown is a schematic representation of an electronic device according to an embodiment of the present invention. Figure 5 As shown, the electronic device 10 of this embodiment includes a processor 100, a memory 101, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, it implements the steps in the method embodiment described above. Alternatively, when the processor 100 executes the computer program 102, it implements the functions of each module / unit in the device embodiment described above.

[0164] For example, computer program 102 can be divided into one or more modules / units, one or more of which are stored in memory 101 and executed by processor 100 to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of computer program 102 in electronic device 10. For example, computer program 102 can be divided into a processing sequence determination module, an operation sequence processing module, a step response end time determination module, a step response confidence calculation module, and a step response curve determination module.

[0165] Electronic device 10 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Electronic device 10 may include, but is not limited to, processor 100 and memory 101. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 10 and does not constitute a limitation on electronic device 10. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device may also include input / output devices, network access devices, buses, etc.

[0166] The processor 100 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0167] The memory 101 can be an internal storage unit of the electronic device 10, such as a hard disk or RAM of the electronic device 10. The memory 101 can also be an external storage device of the electronic device 10, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the electronic device 10. Furthermore, the memory 101 can include both internal and external storage units of the electronic device 10. The memory 101 is used to store computer programs and other programs and data required by the electronic device 10. The memory 101 can also be used to temporarily store data that has been output or will be output.

[0168] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0169] Those skilled in the art will understand that embodiments of this application can be provided as a method, system, or computer program 102 product. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program 102 product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0170] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program 102 products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program 102 instructions. These computer program 102 instructions can be provided to a processor 100 of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor 100 of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0171] These computer program 102 instructions may also be stored in a computer-readable storage medium 101 that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium 101 produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0172] These computer program 102 instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0173] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0174] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for identifying the step response of a control loop under steady-state operating conditions, characterized in that, include: Based on the historical operating data of each control loop, determine the corresponding operation sequence and observation sequence for each control loop; Based on the operation sequence corresponding to each control loop, determine the operation time point and duration corresponding to each control loop; Based on the operation time point, duration, and observation sequence after time filtering for each control loop, the end time of the step response for each control loop is determined. Based on the operation time point, duration, end time of step response, and observation sequence after time filtering for each control loop, the confidence level of the step response for each control loop is calculated. Based on the calculation results of the step response reliability of each control loop, the step response curve of each control loop is determined. The step of determining the operation time point and duration corresponding to each control loop based on the operation sequence corresponding to each control loop includes: Determine the threshold XL for the number of consecutive no-operation data in the operation sequence corresponding to each control loop; For each control loop, based on the corresponding threshold XL of the number of consecutive no-operation data, from time point XL+1 to time point n, the corresponding operation sequence Opreates[N1] is traversed to determine the corresponding operation time point; where N1={XL+1,...,n}, the XL data before the operation time point in the operation sequence Opreates[N1] are all first values ​​and the XL data after the operation time point are all second values, and the first value and the second value are not equal; For each control loop, from the operation time point to time point n, the corresponding operation sequence Opreates[N2] is traversed to determine the corresponding duration; where N2 = {Ti, ..., n}, Ti represents the operation time point, and the data of the time point in the operation sequence Opreates[N2] between the operation time point Ti and the end time point Ts of the duration are all second values.

2. The method for identifying the step response of a control loop under steady-state conditions according to claim 1, characterized in that, The process of determining the operation sequence and observation sequence for each control loop based on historical operating data includes: Based on the historical operating data of each control loop, an operating data sequence corresponding to each preset relevant parameter of each control loop is established; wherein, the operating data sequence corresponding to each preset relevant parameter includes the control mode time sequence Mode[I], the output value sequence MV[I], the measured value sequence PV[I], and the set value sequence SP[I]; wherein, I={1,2,...,n}; Based on the control state reflected by each data point in the control mode time series Mode[I], a corresponding assignment scheme is matched to assign values ​​to the corresponding operation sequence and observation sequence; among which, The assignment scheme includes a manual state assignment scheme and an automatic state assignment scheme; The manual state assignment scheme is used to assign values ​​to the corresponding operation sequence and observation sequence when the control state reflected by each data in the control mode time series Mode[I] is manual. The automatic state assignment scheme is used to assign values ​​to the corresponding operation sequence and observation sequence when the control state reflected by each data in the control mode time series Mode[I] is automatic.

3. The method for identifying the step response of a control loop under steady-state conditions according to claim 2, characterized in that, The control state reflected by each data point in the control mode time series Mode[I] is matched with a corresponding assignment scheme to assign values ​​to the corresponding operation sequence and observation sequence, including: If the control states reflected by each data in the control mode time series Mode[I] include manual and automatic states, then the first sequence range is obtained by identifying the longest continuous sequence range in the control mode time series Mode[I] that belongs to the same control state. When the control state reflected by each data in the first sequence range is manual, the operation sequence and observation sequence corresponding to the first sequence range are assigned values ​​using the manual state assignment scheme; When the control state reflected by the data in the first sequence range is automatic, the operation sequence and observation sequence corresponding to the first sequence range are assigned values ​​using the automatic state assignment scheme.

4. The method for identifying the step response of a control loop under steady-state conditions according to claim 2, characterized in that, The manual status assignment scheme includes: The output value sequence MV[I] is used as the operation sequence Opreates[I], and the measurement value sequence PV[I] is used as the observation sequence Observes[I].

5. The method for identifying the step response of a control loop under steady-state conditions according to claim 2, characterized in that, The automatic status assignment scheme includes: The setpoint sequence SP[I] is used as the operation sequence Opreates[I], and the deviation between the measured value sequence PV[I] and the setpoint sequence SP[I] is used as the observation sequence Observes[I].

6. The method for identifying the step response of a control loop under steady-state conditions according to claim 1, characterized in that, The time filtering rules for the observation sequence include: Based on the filtering time FilterTime and the preset sampling time interval SampleTime, the observation sequence is subjected to time filtering to obtain the time-filtered observation sequence NObserves[i]; where... ,NObserves[1] = Observes[1],NObserves[i]=Observes[i] (1-Filter)+Filter Observes[i-1],FilterTime>SampleTime,i∈I={1,2,...,n}。 7. The method for identifying the step response of a control loop under steady-state conditions according to claim 1, characterized in that, The determination of the end time of the step response for each control loop, based on the operation time point, duration, and time-filtered observation sequence for each control loop, includes: For each control loop, based on the corresponding time-filtered observation sequence, calculate the corresponding fluctuation sequence Steady[i]; where, , , i∈I, i={Ti-1, Ti, Ti+1, ..., Ts}, K represents the time range for calculating the fluctuation of the observed sequence, Ts represents the cutoff point of the duration, and Ti represents the operation time point; For each control loop, from the corresponding time point Ti-1 to the corresponding duration's end time Ts, traverse the corresponding fluctuation sequence and determine the time corresponding to the maximum value of the fluctuation sequence as the end time of the corresponding step response; where, , i∈I, i={Ti-1, Ti, Ti+1,..., Ts}, This indicates the time corresponding to the maximum value of the fluctuation sequence.

8. The method for identifying the step response of a control loop under steady-state conditions according to claim 7, characterized in that, The calculation of the step response reliability for each control loop, based on the operation time point, duration, end time of the step response, and time-filtered observation sequence corresponding to each control loop, includes: Based on the operating time point and the end time of the step response for each control loop, calculate the steady-state operating time point Tes after the step response for each control loop; where Tes = 2Te - Ti + 1, and Ti is the operating time point. According to the formula The system determines the stable operating conditions of each control loop before and after the step response begins, obtaining the first stable operating condition judgment value Rel_se for each control loop; where, This represents the fluctuation sequence Steady[i] at time point Data, This represents the data of the fluctuation sequence Steady[i] at the steady-state time point Tes after the step response; According to the formula Determine the stable operating condition of each control loop after the step response, and obtain the second stable operating condition judgment value corresponding to each control loop. ; According to the formula Determine the excitation level of the step response of each control loop to obtain the excitation level judgment value of the step response for each control loop. ; Based on the first stable condition judgment value Rel_se and the second stable condition judgment value corresponding to each control loop And step response excitation degree judgment value Determine the reliability of the step response corresponding to each control loop.

9. The method for identifying the step response of a control loop under steady-state conditions according to claim 8, characterized in that, The formulas for calculating the reliability of the step response for each control loop are as follows: ； in, This indicates the confidence level of the step response.

10. The method for identifying the step response of a control loop under steady-state conditions according to claim 8, characterized in that, After calculating the steady-state operating time point Tes corresponding to the step response of each control loop, the following is also included: For each control loop, if the steady-state condition time point after the corresponding step response is greater than the end time point of the duration and the value of the end time point of the duration is the same as the value of the number of data acquisitions, the acquired historical operating data is supplemented. Based on the supplemented historical operating data, the corresponding operation sequence, observation sequence, operation time point, duration, and end time of the step response are re-determined. If the steady-state condition time point after the corresponding step response is greater than the end time point of the duration, and the value of the end time point of the duration is less than the value of the number of data acquisitions, then the corresponding control loop cannot be used to determine the reliability of the step response.

11. The method for identifying the step response of a control loop under steady-state conditions according to claim 1, characterized in that, The step response curve for each control loop is determined based on the step response reliability calculation results for each control loop, including: For each control loop, when the calculated confidence result of the corresponding step response is greater than the preset threshold, the data from the operation time point Ti to the end time Te of the step response in the corresponding historical operation data is determined as the corresponding step response curve.

12. The method for identifying the step response of a control loop under steady-state conditions according to claim 1, characterized in that, Also includes: According to the preset sampling time interval, the historical operating data of the control loop is acquired through the data acquisition interface; wherein, the historical operating data of the control loop includes measured values, set values, control mode (MODE) values ​​and output values.

13. A step response identification system for steady-state operation of a control loop, characterized in that, The method for identifying the steady-state step response of a control loop as described in any one of claims 1 to 12 includes: The processing sequence determination module is used to determine the operation sequence and observation sequence corresponding to each control loop based on the historical operation data of each control loop; The operation sequence processing module is used to determine the operation time point and duration of each control loop based on the operation sequence corresponding to each control loop. The step response end time determination module is used to determine the end time of the step response for each control loop based on the operation time point, duration, and observation sequence after time filtering. The step response confidence calculation module is used to calculate the confidence of the step response of each control loop based on the operation time point, duration, end time of the step response, and the observation sequence after time filtering. The step response curve determination module is used to determine the step response curve corresponding to each control loop based on the step response reliability calculation results corresponding to each control loop.

14. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by the processor, the instruction causes the processor to be configured to perform the step response identification method for steady-state conditions of the control loop as described in any one of claims 1 to 12.

15. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the step response identification method for steady-state operation of the control loop as described in any one of claims 1 to 12.

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