Oscillation detection method of control loop system and related equipment

Abstract

The invention provides an oscillation detection method of a control loop system and related equipment. The method comprises the following steps: acquiring process variable time sequence data of the control loop system; performing band-pass filtering processing on the process variable time sequence data to obtain multiple frequency band data; for each piece of frequency band data, calculating an autocorrelation function sequence of the frequency band data, and determining an oscillation index corresponding to the frequency band data based on the autocorrelation function sequence; determining whether the frequency band data meets a preset oscillation condition or not according to the oscillation index; and if at least one piece of frequency band data meeting the oscillation condition exists, it is determined that oscillation exists in the control loop system. According to the method and the device, whether the system oscillates or not can be accurately identified.

Description

Technical Field

[0001] The present application relates to the field of control technology, and more specifically, to an oscillation detection method for a control loop system and related equipment. Background Art

[0002] Industrial process control is a key technology to ensure stable, efficient and safe operation of industrial production processes. Through real-time monitoring and adjustment of process variables, control systems can maintain product quality, improve energy efficiency and reduce costs. As the basic unit of industrial process control, the performance of the control loop directly affects the stability and reliability of the entire production system. In actual industrial applications, the control loop may exhibit oscillatory behavior, which often leads to problems such as reduced production efficiency, increased equipment loss, and product quality fluctuations. Therefore, accurate detection and processing of oscillation phenomena are essential to maintain the normal operation of industrial production.

[0003] Although existing oscillation detection technologies have been successful in some applications, they still have significant limitations in complex and changeable real-world environments, especially in noisy environments. The sensitivity of traditional methods to noise is a major problem: on the one hand, they may misjudge random noise in the environment as oscillation signals, leading to unnecessary alarms and adjustments; on the other hand, in the presence of high noise backgrounds, these methods may not accurately identify the true oscillation signal, thus delaying necessary corrective measures. These problems not only increase the maintenance cost of the system, but may also cause more serious production accidents. Summary of the invention

[0004] In view of this, the present application provides an oscillation detection method and related equipment for a control loop system, which can accurately identify whether the system is oscillating. The specific scheme is as follows:

[0005] A method for detecting oscillation of a control loop system, comprising:

[0006] Obtaining process variable timing data of the control loop system;

[0007] Performing bandpass filtering on the process variable time series data to obtain data in multiple frequency bands;

[0008] For each of the frequency segment data, an autocorrelation function sequence of the frequency segment data is calculated, and an oscillation index corresponding to the frequency segment data is determined based on the autocorrelation function sequence; and whether the frequency segment data meets a preset oscillation condition is determined according to the oscillation index;

[0009] If at least one of the frequency band data satisfies the oscillation condition, it is determined that oscillation exists in the control loop system.

[0010] The above method, optionally, after determining that the control loop system has oscillation, further includes:

[0011] Determine the system type of the control loop system, the system type being a linear type and a nonlinear type;

[0012] In the case where the system type is a linear type, determining the oscillation source of the control loop system according to target frequency band data and an autocorrelation function sequence of the target frequency band data; the target frequency band data is frequency band data that satisfies the oscillation condition;

[0013] In the case where the system type is a nonlinear type, the controller output value in the control loop system and the time difference sequence of the target frequency band data are calculated respectively; based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data, the oscillation source of the control loop system is determined.

[0014] The above method, optionally, determines the system type of the control loop system, including:

[0015] Calculating a bispectrum of the process variable time series data;

[0016] Calculating the squared bicoherence according to the bispectrum of the process variable time series data;

[0017] determining a nonlinear index of the control loop system according to the squared bicoherence;

[0018] When the nonlinear index is not greater than a preset index threshold, determining that the system type of the control loop system is a linear type;

[0019] When the nonlinear index is greater than a preset index threshold, it is determined that the system type of the control loop system is a nonlinear type.

[0020] Optionally, the above method, determining the oscillation source of the control loop system according to the target frequency band data and the autocorrelation function sequence of the target frequency band data, comprises:

[0021] Determine a sequence difference between a first part and a second part of the autocorrelation function sequence;

[0022] Determine whether the latter part of the autocorrelation function sequence and the sequence difference satisfy the existence of oscillation behavior, and obtain a determination result;

[0023] An oscillation source of the control loop system is determined according to the determination result.

[0024] Optionally, the above method, determining the oscillation source of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency band data, comprises:

[0025] Determining the time proportion of the viscous motion mode of the valve of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency segment data;

[0026] An oscillation source of the control loop system is determined according to a time proportion of the viscous motion mode of the valve.

[0027] In the above method, optionally, the oscillation index includes an attenuation ratio, a zero axis crossing interval regularity factor, an oscillation energy ratio, and an oscillation amplitude, and determining the oscillation index corresponding to the frequency segment data based on the autocorrelation function sequence includes:

[0028] Determining the oscillation period according to the intersection point between the autocorrelation function sequence and the zero axis;

[0029] Determine a zero axis crossing interval regularity factor of the frequency band data according to the oscillation period;

[0030] Calculating the oscillation energy ratio of the frequency band data according to the power spectrum density of the frequency band data and the oscillation period;

[0031] According to the peak points and valley points of the autocorrelation function sequence, the attenuation ratio corresponding to the frequency band data is calculated;

[0032] The oscillation amplitude of the frequency band data, the zero axis crossing interval regularity factor, the oscillation energy proportion and the attenuation ratio are used as oscillation indicators corresponding to the frequency band data.

[0033] The above method may optionally include determining whether the frequency band data meets a preset oscillation condition according to the oscillation index, including:

[0034] When the attenuation ratio is greater than a preset attenuation ratio threshold, the zero-axis crossing interval regularity factor is greater than a preset factor threshold, the oscillation energy proportion is greater than a preset proportion threshold, and the oscillation amplitude is greater than a preset amplitude threshold, it is determined that the frequency band data meets the preset oscillation condition.

[0035] An oscillation detection device for a control loop system, comprising:

[0036] An acquisition unit, used for acquiring time series data of process variables of a control loop system;

[0037] A processing unit, used for performing bandpass filtering on the process variable time series data to obtain data in multiple frequency bands;

[0038] A first determination unit is configured to calculate, for each frequency segment data, an autocorrelation function sequence of the frequency segment data, determine an oscillation index corresponding to the frequency segment data based on the autocorrelation function sequence; and determine whether the frequency segment data meets a preset oscillation condition according to the oscillation index;

[0039] The second determining unit is configured to determine that oscillation exists in the control loop system if at least one of the frequency segment data satisfies the oscillation condition.

[0040] A storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the oscillation detection method of the control loop system as described above.

[0041] An electronic device includes a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be used by one or more processors to execute the oscillation detection method of the control loop system as described above.

[0042] Compared with the prior art, this application has the following beneficial effects:

[0043] The present application provides an oscillation detection method and related equipment for a control loop system, the method comprising: obtaining the process variable time series data of the control loop system; performing bandpass filtering on the process variable time series data to obtain multiple frequency band data; for each frequency band data, calculating the autocorrelation function sequence of the frequency band data, and determining the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence; determining whether the frequency band data meets the preset oscillation condition according to the oscillation index; if there is at least one frequency band data that meets the oscillation condition, determining that the control loop system has oscillation. Applying the method provided in the embodiment of the present application can accurately identify whether the system is oscillating. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application 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 embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0045] Figure 1 A method flow chart of an oscillation detection method for a control loop system provided in an embodiment of the present application;

[0046] Figure 2A schematic diagram of the structure of a control loop system provided in an embodiment of the present application;

[0047] Figure 3 An example graph of an autocorrelation function curve provided in an embodiment of the present application;

[0048] Figure 4 A flowchart of a process for determining an oscillation source provided in an embodiment of the present application;

[0049] Figure 5 An example diagram of a three-dimensional squared bicoherence function provided in an embodiment of the present application;

[0050] Figure 6 A viscous motion mode diagram provided in an embodiment of the present application;

[0051] Figure 7 A flowchart of an oscillation tracing process of an industrial process control loop system provided in an embodiment of the present application;

[0052] Figure 8 A schematic diagram of the structure of an oscillation detection device for a control loop system provided in an embodiment of the present application;

[0053] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0055] The present application also provides an oscillation detection method for a control loop system, which can be applied to electronic equipment. The flowchart of the method is as follows: Figure 1 As shown, specifically including:

[0056] S101: Acquire process variable timing data of the control loop system.

[0057] In this embodiment, the controller output data MV and the process variable PV of the control loop system can be collected according to the preset sampling period ts, where MV is the signal sent by the controller to adjust the process variable. PV is the actual measurement value of the controlled object, representing the current state of the system. Optionally, the control loop system Figure 2 As shown, it may include a controller, an actuator, a controlled system, a sensor, etc.

[0058] Optionally, the collected data is normalized, and then the normalized data is detrended to obtain a controller output data sequence and a process variable time series data sequence.

[0059] S102: Perform bandpass filtering on the process variable time series data to obtain data in multiple frequency bands.

[0060] In this embodiment, the bandpass filter is used to extract signal components within a specific frequency range, and is particularly suitable for focusing on oscillation behaviors at certain specific frequencies. The process variable time series data can be bandpass filtered to divide the data into multiple frequency segments, and the range of each frequency segment is:

[0061]

[0062] Among them, the first three frequency bands are the frequency bands of concern in industrial processes, distributed sequentially from high frequency band to low frequency band, and the start and end frequencies of the last two frequency bands are the average of the start and end frequencies of adjacent frequency bands of the first three frequency bands.

[0063] In this embodiment, in terms of frequency band division, three main industrial frequency bands are first defined. These frequency bands are arranged in order from high frequency to low frequency, aiming to cover the typical oscillation behavior in industrial processes. The subsequent two auxiliary frequency bands are determined based on the average value of the adjacent boundary frequencies of the first three frequency bands, which helps to fill the gaps between the main frequency bands and ensure effective monitoring of the entire spectrum. Such a design can accurately capture signal characteristics in different frequency ranges for specific industrial needs.

[0064] Considering that the actual industrial process focuses more on low-frequency oscillation phenomena with a period of more than 1 minute (i.e., a frequency lower than 1 / 60Hz), even if the data sampling interval is 10 seconds (corresponding to a frequency of 1 / 10Hz), these low-frequency components can be effectively separated by applying a bandpass filter. After decomposing the original signal into multiple independent frequency segments, it is not only convenient to analyze the coexisting oscillation modes of different frequencies, but also can significantly improve the accuracy and efficiency of locating the multi-frequency oscillation source, thereby better supporting fault diagnosis and system optimization.

[0065] S103: For each frequency segment data, calculate the autocorrelation function sequence of the frequency segment data, determine the oscillation index corresponding to the frequency segment data based on the autocorrelation function sequence; and determine whether the frequency segment data meets a preset oscillation condition according to the oscillation index.

[0066] In this embodiment, the oscillation index includes at least one of an attenuation ratio, a zero-axis crossing interval regularity factor, an oscillation energy ratio, and an oscillation amplitude.

[0067] In this embodiment, the autocorrelation function sequence ACF of each frequency band data can be calculated, where each value in the sequence is , as follows:

[0068]

[0069] in, It is the current frequency band data PV; for The total number of data, ; is the standard deviation of PV; is the average value of PV; is the hysteresis time, the maximum is 0.5N; Push the current frequency band data back Time data is a time series data; The current frequency segment data is delayed by The autocorrelation function value at .

[0070] In this embodiment, the oscillation index includes attenuation ratio, zero axis crossing interval regularity factor, oscillation energy ratio and oscillation amplitude. The oscillation index corresponding to the frequency segment data is determined based on the autocorrelation function sequence, including:

[0071] The oscillation period is determined based on the intersection of the autocorrelation function sequence and the zero axis;

[0072] Determine the zero axis crossing interval regularity factor of the frequency band data according to the oscillation period;

[0073] According to the power spectrum density and oscillation period of the frequency band data, the oscillation energy ratio of the frequency band data is calculated;

[0074] According to the peak points and valley points of the autocorrelation function sequence, the attenuation ratio corresponding to the frequency band data is calculated;

[0075] The oscillation amplitude of the frequency band data, the zero-axis crossing interval regularity factor, the oscillation energy proportion and the attenuation ratio are used as the oscillation indicators corresponding to the frequency band data.

[0076] In this embodiment, the autocorrelation function sequence of the frequency segment data can be used The zero-axis crossing interval is used to detect oscillation.

[0077] Specific, identify Intersection point with zero axis ,Right now hour, , then, the oscillation period T is estimated as Twice the mean:

[0078]

[0079] Where n is the zero axis crossing point the number of For adjacent time interval.

[0080] In this embodiment, the error of the period T :

[0081]

[0082] in, for The standard deviation of , so the oscillation period is expressed as .

[0083] In this embodiment, the calculation Zero axis crossing interval regularity factor :

[0084]

[0085] In this embodiment, the oscillation energy ratio of the frequency band data can be calculated :

[0086]

[0087] in, The discrete time signal PV has a frequency of The power spectral density when .

[0088] Autocorrelation function Attenuation ratio calculate:

[0089] exist Find the peak and valley points in the trend graph, and set the time window to 0.5T:

[0090] Peak point definition: at time When PV autocorrelation coefficient value Greater than time period All the time Value, coordinates are ;

[0091] Valley point definition: at time When PV autocorrelation coefficient value Greater than time period All the time Value, coordinates are ;

[0092] In this embodiment, the attenuation ratio is calculated :

[0093]

[0094] The decay ratio is used as one of the oscillation indicators to determine whether there is oscillation behavior.

[0095] Among them, a is the distance from the first peak coordinate point to the straight line connecting the first two valley points, and b is the distance from the first valley coordinate point to the straight line connecting the [0,1] point and the first peak point, such as Figure 3 shown.

[0096] Oscillation amplitude calculation:

[0097]

[0098] in, , The maximum and minimum values ​​of the PV of the stable data segment respectively.

[0099] S104: If there is at least one frequency segment data that meets the oscillation condition, it is determined that the control loop system has oscillation.

[0100] In this embodiment, determining whether the frequency band data meets a preset oscillation condition according to the oscillation index includes:

[0101] When the attenuation ratio is greater than the preset attenuation ratio threshold, the zero-axis crossing interval regularity factor is greater than the preset factor threshold, the oscillation energy ratio is greater than the preset ratio threshold, and the oscillation amplitude is greater than the preset amplitude threshold, it is determined that the frequency band data meets the preset oscillation condition.

[0102] For example, if , it is determined that there is oscillation in the control loop system.

[0103] In an embodiment provided in the present application, based on the above solution, optionally, after determining that the control loop system has oscillation, such as Figure 4 As shown, it also includes:

[0104] S401: Determine the system type of the control loop system, which system type is a linear type or a nonlinear type.

[0105] In an embodiment provided in the present application, based on the above solution, optionally, determining the system type of the control loop system includes:

[0106] Calculate the bispectrum of process variable time series data;

[0107] The squared bicoherence is calculated based on the bispectrum of the process variable time series data;

[0108] Determine the nonlinear index of the control loop system according to the squared bicoherence;

[0109] When the nonlinear index is not greater than a preset index threshold, determining that the system type of the control loop system is a linear type;

[0110] When the nonlinear index is greater than a preset index threshold, it is determined that the system type of the control loop system is a nonlinear type.

[0111] In this embodiment, the bispectrum of the process variable time series data is calculated , is the statistic of the signal of the process variable time series data in the third-order frequency domain:

[0112]

[0113] in, is the discrete time signal PV ( ) at a frequency of Fourier transform at ; is the discrete time signal PV ( ) at a frequency of The conjugate complex number of the Fourier transform at ; therefore, It is possible to plot the two independent frequency variables , 3D illustration.

[0114] Calculate the bicoherence function , is a double spectrum Normalized results:

[0115]

[0116] in, is the squared bicoherence, which is between 0 and 1 and can be plotted against two independent frequency variables. , A three-dimensional graph of Figure 5 As shown, a simple way to confirm the linearity of the system is to observe the flatness of the three-dimensional squared bicoherence plot. The flatter the system, the more linear the system.

[0117] In this embodiment, the system nonlinearity index NLI is calculated to evaluate Flatness of the distribution in a 3D plot:

[0118]

[0119] in, is the maximum value of the squared bicoherence;

[0120] in, and , are the robust mean and robust standard deviation of the squared bicoherence, respectively. They are calculated by excluding the top Q% of the largest and smallest squared bicoherence, and the Q value is chosen to be 10.

[0121] if , then the control loop system is a linear system if , then the control loop system is a nonlinear system.

[0122] S402: When the system type is a linear type, determine the oscillation source of the control loop system according to the target frequency band data and the autocorrelation function sequence of the target frequency band data; the target frequency band data is the frequency band data that meets the oscillation condition.

[0123] In an embodiment provided in the present application, based on the above solution, optionally, determining the oscillation source of the control loop system according to the target frequency band data and the autocorrelation function sequence of the target frequency band data includes:

[0124] Determine the sequence difference between the first and second parts of the autocorrelation function sequence;

[0125] Determine whether the latter part of the autocorrelation function sequence and the sequence difference satisfy the existence of oscillation behavior, and obtain a determination result;

[0126] The oscillation source of the control loop system is determined based on the judgment result.

[0127] In this embodiment, a peak point close to the position in the autocorrelation function sequence can be selected. , the ACF curve is divided into two parts before and after this point , , and calculate the difference between the two :

[0128]

[0129] judge and Whether there is oscillation, the judgment method here can refer to the description of the above S103 part, which will not be repeated here.

[0130] like If there is oscillation behavior, then the external oscillation disturbance is one of the reasons that cause the control loop to oscillate in this frequency range; if the condition is not met, then the external oscillation disturbance is not the cause of the oscillation;

[0131] like If there is oscillation behavior, then controller over-tuning is one of the reasons that cause the control loop to oscillate in this frequency range; if the condition is not met, then controller over-tuning is not the cause of the oscillation.

[0132] S403: When the system type is a nonlinear type, respectively calculate the controller output value in the control loop system and the time difference sequence of the target frequency band data; determine the oscillation source of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency band data.

[0133] In an embodiment provided by the present application, based on the above solution, optionally, determining the oscillation source of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency band data includes:

[0134] Determine the time proportion of the viscous motion mode of the valve of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency band data;

[0135] The oscillation source of the control loop system is determined based on the time proportion of the viscous motion mode of the valve.

[0136] In this embodiment, the time difference between the controller output value and the target frequency band data can be calculated respectively, and the value of the differential sequence between the controller output value and the target frequency band data can be mapped to three symbols, I (value>1), D (value<-1), and S (-1≤value≤1). For example, the differential sequence of PV is: [2,3,-2,0,0.5,-1][I,I,D,S,S,S].

[0137] The controller output value is combined with the symbol sequence of the target frequency band data to form a two-dimensional symbol sequence. For example, the controller output value is: [I,I,S,D], the target frequency band data is: [S,I,I,D], and the integrated sequence is [IS, II, SI, DD], which describes the valve motion pattern on the xy plane.

[0138] Delete the SS symbol in the sequence and merge the same consecutive symbols to further simplify the symbol sequence. For example, [II, IS, IS, SS, DI, DI, DI, DD] is changed to: [II, IS2, SS, DI3, DD];

[0139] The time proportion of the sticking motion mode is calculated by finding the total duration of the IS and DS modes in the input-output diagram of the control valve. The sticking motion mode is as follows: Figure 6 As shown, the index r1 is calculated ( ):

[0140]

[0141] in, is the width of the total time window,

[0142] and are the total number of modes IS and DS respectively.

[0143] Valve sticking diagnosis: If the signal is random, the value of r1 is about 0.25, because r1 represents two of the eight modes. Therefore, if the index r1 value is greater than 0.25 or more, it is judged that valve sticking is the source of oscillation. If the index r1 value is less than 0.25, it is judged that valve sticking is not the source of oscillation.

[0144] The linear system oscillation source tracing method is continued to be used for the oscillation signal PV to identify the combination of two types of oscillation sources: external disturbance and improper controller setting.

[0145] If the source of oscillation is not detected (valve sticking, external disturbance, improper controller adjustment), the source of oscillation comes from other nonlinear factors in the control loop system besides valve sticking, such as excessive valve dead zone, valve output oversaturation, sensor failure, and severe nonlinearity of the controlled object itself.

[0146] See also Figure 7 , which is a flowchart of the oscillation tracing process of an industrial process control loop system provided by the present application, can first collect MV data and PV data in the control loop system, and then pre-process the collected data. After the pre-processing of the PV data is completed, the pre-processed PV data is subjected to a waiting filter to obtain multiple frequency band data, for each frequency band data, the autocorrelation function sequence of the frequency band data is calculated, and the oscillation index corresponding to the frequency band data is determined based on the autocorrelation function sequence; according to the oscillation index, it is determined whether the frequency band data meets the preset oscillation condition; if there is at least one of the frequency band data that meets the oscillation condition, it is determined that the control loop system has oscillation, and the frequency band data that meets the oscillation condition is determined as the target frequency band data, and the system type of the industrial process control loop system is further evaluated, and the system type is one of a linear system type and a nonlinear system type, and the oscillation tracing method corresponding to the system type is selected to perform oscillation tracing on the industrial process control loop system.

[0147] and Figure 1 Corresponding to the method, the embodiment of the present application also provides an oscillation detection device of a control loop system, for Figure 1 The specific implementation of the method is shown in the following diagram: Figure 8 As shown, including:

[0148] An acquisition unit 801 is used to acquire the time series data of the process variables of the control loop system;

[0149] The processing unit 802 is used to perform bandpass filtering on the process variable time series data to obtain multiple frequency band data;

[0150] The first determination unit 803 is used to calculate the autocorrelation function sequence of each frequency segment data, determine the oscillation index corresponding to the frequency segment data based on the autocorrelation function sequence; and determine whether the frequency segment data meets a preset oscillation condition according to the oscillation index;

[0151] The second determining unit 804 is configured to determine that oscillation exists in the control loop system if at least one of the frequency segment data satisfies the oscillation condition.

[0152] The specific principles and execution processes of each unit and module in the oscillation detection device of the control loop system disclosed in the above-mentioned embodiment of the present application are the same as the oscillation detection method of the control loop system disclosed in the above-mentioned embodiment of the present application. Please refer to the corresponding parts of the oscillation detection method of the control loop system provided in the above-mentioned embodiment of the present application, and will not be repeated here.

[0153] An embodiment of the present application further provides a storage medium, the storage medium including stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the above-mentioned oscillation detection method of the control loop system.

[0154] The present application also provides an electronic device, whose structural diagram is as follows: Fig. 9 As shown, it specifically includes a memory 901 and one or more instructions 902, wherein the one or more instructions 902 are stored in the memory 901 and are configured to be executed by one or more processors 903 to perform the following operations:

[0155] Obtaining process variable timing data of the control loop system;

[0156] Performing bandpass filtering on the process variable time series data to obtain data in multiple frequency bands;

[0157] For each of the frequency segment data, an autocorrelation function sequence of the frequency segment data is calculated, and an oscillation index corresponding to the frequency segment data is determined based on the autocorrelation function sequence; and whether the frequency segment data meets a preset oscillation condition is determined according to the oscillation index;

[0158] If at least one of the frequency band data satisfies the oscillation condition, it is determined that oscillation exists in the control loop system.

[0159] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0160] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0161] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0162] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0163] The above is a detailed introduction to the oscillation detection method of a control loop system provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for detecting oscillation of a control loop system, characterized in that: include: Obtaining process variable timing data of the control loop system; Performing bandpass filtering on the process variable time series data to obtain data in multiple frequency bands; For each of the frequency segment data, an autocorrelation function sequence of the frequency segment data is calculated, and an oscillation index corresponding to the frequency segment data is determined based on the autocorrelation function sequence; and whether the frequency segment data meets a preset oscillation condition is determined according to the oscillation index; If at least one of the frequency band data satisfies the oscillation condition, it is determined that oscillation exists in the control loop system.

2. The method according to claim 1, characterized in that After determining that the control loop system has oscillation, the method further includes: Determine the system type of the control loop system, the system type being a linear type and a nonlinear type; In the case where the system type is a linear type, determining the oscillation source of the control loop system according to target frequency band data and an autocorrelation function sequence of the target frequency band data; the target frequency band data is frequency band data that satisfies the oscillation condition; In the case where the system type is a nonlinear type, the controller output value in the control loop system and the time difference sequence of the target frequency band data are calculated respectively; based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data, the oscillation source of the control loop system is determined.

3. The method according to claim 2, characterized in that Determine the system type of the control loop system, including: Calculating a bispectrum of the process variable time series data; Calculating the squared bicoherence according to the bispectrum of the process variable time series data; determining a nonlinear index of the control loop system according to the squared bicoherence; When the nonlinear index is not greater than a preset index threshold, determining that the system type of the control loop system is a linear type; When the nonlinear index is greater than a preset index threshold, it is determined that the system type of the control loop system is a nonlinear type.

4. The method according to claim 2, characterized in that: The step of determining the oscillation source of the control loop system according to the target frequency band data and the autocorrelation function sequence of the target frequency band data comprises: Determine a sequence difference between a first part and a second part of the autocorrelation function sequence; Determine whether the latter part of the autocorrelation function sequence and the sequence difference satisfy the existence of oscillation behavior, and obtain a determination result; An oscillation source of the control loop system is determined according to the determination result.

5. The method according to claim 2, characterized in that: The determining the oscillation source of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency segment data comprises: Determining the time proportion of the viscous motion mode of the valve of the control loop system according to the time difference sequence of the controller output value and the time difference sequence of the target frequency segment data; An oscillation source of the control loop system is determined according to a time proportion of the viscous motion mode of the valve.

6. The method according to claim 1, characterized in that The oscillation index includes an attenuation ratio, a zero axis crossing interval regularity factor, an oscillation energy ratio, and an oscillation amplitude. The oscillation index corresponding to the frequency segment data is determined based on the autocorrelation function sequence, including: Determining the oscillation period according to the intersection point between the autocorrelation function sequence and the zero axis; Determine a zero axis crossing interval regularity factor of the frequency band data according to the oscillation period; Calculating the oscillation energy ratio of the frequency band data according to the power spectrum density of the frequency band data and the oscillation period; According to the peak points and valley points of the autocorrelation function sequence, the attenuation ratio corresponding to the frequency band data is calculated; The oscillation amplitude of the frequency band data, the zero axis crossing interval regularity factor, the oscillation energy proportion and the attenuation ratio are used as oscillation indicators corresponding to the frequency band data.

7. The method according to claim 6, characterized in that Determining whether the frequency band data meets a preset oscillation condition according to the oscillation index includes: When the attenuation ratio is greater than a preset attenuation ratio threshold, the zero-axis crossing interval regularity factor is greater than a preset factor threshold, the oscillation energy proportion is greater than a preset proportion threshold, and the oscillation amplitude is greater than a preset amplitude threshold, it is determined that the frequency band data meets the preset oscillation condition.

8. An oscillation detection device for a control loop system, characterized in that: include: An acquisition unit, used for acquiring time series data of process variables of a control loop system; A processing unit, used for performing bandpass filtering on the process variable time series data to obtain data in multiple frequency bands; A first determination unit is configured to calculate, for each frequency segment data, an autocorrelation function sequence of the frequency segment data, determine an oscillation index corresponding to the frequency segment data based on the autocorrelation function sequence; and determine whether the frequency segment data meets a preset oscillation condition according to the oscillation index; The second determining unit is configured to determine that oscillation exists in the control loop system if at least one of the frequency segment data satisfies the oscillation condition.

9. A storage medium, characterized in that: The storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the oscillation detection method for the control loop system according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The invention comprises a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the oscillation detection method of the control loop system as claimed in any one of claims 1 to 7.

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