A method and related equipment for oscillation detection in a control loop system

Abstract

This application provides a method and related equipment for oscillation detection in a control loop system. The method includes: acquiring time-series data of process variables of the control loop system; performing band-pass filtering on the time-series data of process variables to obtain multiple frequency band data; for each 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 based on the oscillation index; if at least one frequency band data meets the oscillation condition, then it is determined that the control loop system oscillates. In other words, this application can accurately identify whether the system is oscillating.

Description

Technical Field

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

[0002] Industrial process control is a key technology for ensuring the 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 practical industrial applications, control loops may exhibit oscillating behavior, which typically leads to decreased production efficiency, increased equipment wear and tear, and fluctuations in product quality. Therefore, accurately detecting and handling oscillation phenomena is crucial for maintaining the normal operation of industrial production.

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

[0004] In view of this, this 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 solution is as follows:

[0005] An oscillation detection method for a control loop system, comprising:

[0006] Acquire the timing data of process variables in the control loop system;

[0007] The time-series data of the process variables are subjected to bandpass filtering to obtain data in multiple frequency bands;

[0008] For each frequency band data, calculate the autocorrelation function sequence of the frequency band data, determine the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence, and determine whether the frequency band data meets the preset oscillation conditions based on the oscillation index;

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

[0010] Optionally, after determining that the control loop system oscillates, the above method further includes:

[0011] Determine the system type of the control loop system, which is either linear or nonlinear.

[0012] When the system type is linear, the oscillation source of the control loop system is determined based on 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 satisfies the oscillation condition.

[0013] When the system type is nonlinear, the time difference sequence of the controller output value and the target frequency band data in the control loop system 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] Optionally, the method described above may include determining the system type of the control loop system, including:

[0015] Calculate the bispectral data of the time series data of the process variables;

[0016] The squared bicoherence degree is calculated based on the bispectral data of the process variable time series data.

[0017] The nonlinear index of the control loop system is determined based on the squared biphase coherence.

[0018] If the nonlinear exponent is not greater than a preset exponent threshold, the system type of the control loop system is determined to be linear.

[0019] If the nonlinear exponent is greater than a preset exponent threshold, the system type of the control loop system is determined to be nonlinear.

[0020] Optionally, in the above method, determining the oscillation source of the control loop system based on the target frequency band data and the autocorrelation function sequence of the target frequency band data includes:

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

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

[0023] The oscillation source of the control loop system is determined based on the judgment result.

[0024] Optionally, in the above method, determining the oscillation source of the control loop system based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data includes:

[0025] Based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data, determine the time proportion of the viscous motion mode of the valve in the control loop system;

[0026] The oscillation source of the control loop system is determined based on the time proportion of the viscous motion mode of the valve.

[0027] Optionally, in the above method, the oscillation index includes the attenuation ratio, the zero-axis crossover interval regularity factor, the oscillation energy ratio, and the oscillation amplitude. The step of determining the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence includes:

[0028] The oscillation period is determined based on the intersection of the autocorrelation function sequence with the zero axis;

[0029] The zero-axis crossover interval regularity factor of the frequency band data is determined based on the oscillation period.

[0030] The oscillation energy percentage of the frequency band data is calculated based on the power spectral density of the frequency band data and the oscillation period.

[0031] The attenuation ratio corresponding to the frequency band data is calculated based on the peak and valley points of the autocorrelation function sequence.

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

[0033] Optionally, the above method may involve determining whether the frequency band data meets preset oscillation conditions based on the oscillation index, including:

[0034] If the attenuation ratio is greater than a preset attenuation ratio threshold, the zero-axis cross-interval regularity factor is greater than a preset factor threshold, the oscillation energy ratio is greater than a preset proportion threshold, and the oscillation amplitude is greater than a preset amplitude threshold, then the frequency band data is determined to meet the preset oscillation conditions.

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

[0036] The acquisition unit is used to acquire the timing data of process variables in the control loop system.

[0037] The processing unit is used to perform bandpass filtering on the time-series data of the process variables to obtain data in multiple frequency bands;

[0038] The first determining unit is configured to, for each frequency band data, calculate the autocorrelation function sequence of the frequency band data, determine the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence, and determine whether the frequency band data meets the preset oscillation conditions based on the oscillation index;

[0039] The second determining unit is used to determine that the control loop system is oscillating if at least one of the frequency band data satisfies the oscillation condition.

[0040] A storage medium comprising stored instructions, wherein, when the instructions are executed, the device in which the storage medium is located executes the oscillation detection method of the control loop system described above.

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

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

[0043] This application provides a method and related equipment for oscillation detection in a control loop system. The method includes: acquiring time-series data of process variables of the control loop system; performing band-pass filtering on the time-series data of process variables to obtain multiple frequency band data; for each 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 based on the oscillation index; if at least one frequency band data meets the oscillation condition, then it is determined that the control loop system oscillates. Applying the method provided in this application, it is possible to accurately identify whether the system is oscillating. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0045] Figure 1 A flowchart of a method for detecting oscillations in a control loop system provided in this application embodiment;

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

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

[0048] Figure 4 A flowchart illustrating a process for determining an oscillation source, as provided in this application embodiment;

[0049] Figure 5 An example diagram of a three-dimensional quadratic bicoherence function provided for embodiments of this application;

[0050] Figure 6 A diagram illustrating a viscous motion mode provided in an embodiment of this application;

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

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

[0053] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

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

[0056] S101: Obtain the timing data of process variables in the control loop system.

[0057] In this embodiment, the controller output data MV and process variable PV of the control loop system can be collected according to a preset sampling period ts. MV is a signal issued by the controller to adjust the process variable. PV is the actual measured value of the controlled object, representing the current state of the system. Optionally, the control loop system is as follows: Figure 2 As shown, it can include controllers, actuators, controlled systems, and sensors, etc.

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

[0059] S102: Perform bandpass filtering on the time series data of process variables 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. It is particularly suitable for focusing on oscillation behavior at certain specific frequencies. It can perform bandpass filtering on time-series data of process variables, dividing the data into multiple frequency bands, each with the following range:

[0061]

[0062] The first three frequency bands are those of interest to the industrial process, distributed sequentially from high frequency to low frequency. The start and end frequencies of the last two frequency bands are the average of the start and end frequencies of adjacent frequency bands in the first three frequency bands.

[0063] In this embodiment, three main industrial frequency bands are first defined, arranged sequentially from high to low frequency, to cover typical oscillation behaviors in industrial processes. The subsequent two auxiliary frequency bands are determined based on the average of the adjacent boundary frequencies of the first three bands. This helps fill the gaps between the main frequency bands, ensuring effective monitoring of the entire spectrum. This design allows for precise capture of signal characteristics across different frequency ranges to meet specific industrial needs.

[0064] Considering that actual industrial processes tend to focus on low-frequency oscillations with periods exceeding 1 minute (i.e., frequencies below 1 / 60Hz), even with a data sampling interval of 10 seconds (corresponding to a frequency of 1 / 10Hz), these low-frequency components can be effectively separated by applying a bandpass filter. Decomposing the original signal into multiple independent frequency bands not only facilitates the analysis of coexisting different frequency oscillation modes but also significantly improves the accuracy and efficiency of locating multi-frequency oscillation sources, thereby better supporting fault diagnosis and system optimization.

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

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

[0067] In this embodiment, the autocorrelation function sequence (ACF) of the data for each frequency band can be calculated, where each value in the sequence is... The details are as follows:

[0068]

[0069] in, The current frequency band data PV; for Total number of data points ; The standard deviation of PV; This represents the average value of PV. This represents the lag time, with a maximum of 0.5N. Push forward the data for the current frequency band. The time data is a time series data; For the current frequency band data with a lag time of The value of the autocorrelation function at that time.

[0070] In this embodiment, the oscillation indices include attenuation ratio, zero-axis crossover interval regularity factor, oscillation energy ratio, and oscillation amplitude. The oscillation indices corresponding to the frequency band data are determined based on the autocorrelation function sequence, including:

[0071] The oscillation period is determined by the intersection of the autocorrelation function sequence with the zero axis;

[0072] The zero-axis crossover interval regularity factor of the frequency band data is determined based on the oscillation period.

[0073] The proportion of oscillation energy in the frequency band data is calculated based on the power spectral density and oscillation period of the frequency band data.

[0074] The attenuation ratio corresponding to the frequency band data is calculated based on the peak and valley points of the autocorrelation function sequence.

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

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

[0077] Specifically, identification Intersection with the zero axis ,Right now hour, Then, estimate the oscillation period T as follows: Twice the mean:

[0078]

[0079] Where n is the intersection point of the zero axis. Quantity; Adjacent The time interval.

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

[0081]

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

[0083] In this embodiment, calculation Zero-axis cross-interval regularity factor :

[0084]

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

[0086]

[0087] in, For discrete-time signal PV at frequency , The power spectral density at that time.

[0088] Autocorrelation function attenuation ratio calculate:

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

[0090] Peak point definition: at time [time missing] At that time, the autocorrelation coefficient of PV value Greater than the time period All moments within Value, coordinates are ;

[0091] Valley point definition: at time 10:00 At that time, the autocorrelation coefficient of PV value Greater than the time period All moments within Value, coordinates are ;

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

[0093]

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

[0095] Where 'a' is the distance from the first peak coordinate point to the straight line connecting the first two valley values, and 'b' is the distance from the first valley coordinate point to the straight line connecting the [0,1] point and the first peak value, as shown below. Figure 3 As shown.

[0096] Oscillation amplitude calculation:

[0097]

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

[0099] S104: If at least one frequency band of data satisfies the oscillation condition, then it is determined that the control loop system is oscillating.

[0100] In this embodiment, determining whether the frequency band data meets the preset oscillation conditions based on the oscillation index includes:

[0101] If the attenuation ratio is greater than the preset attenuation ratio threshold, the zero-axis cross-interval regularity factor is greater than the preset factor threshold, the oscillation energy ratio is greater than the preset proportion threshold, and the oscillation amplitude is greater than the preset amplitude threshold, then the frequency band data is determined to meet the preset oscillation conditions.

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

[0103] In one embodiment provided in this application, based on the above-described solution, optionally, after determining that the control loop system experiences oscillations, as follows: Figure 4 As shown, it also includes:

[0104] S401: Determine the system type of the control loop system, which can be either linear or nonlinear.

[0105] In one embodiment provided in this application, based on the above-described scheme, optionally, determining the system type of the control loop system includes:

[0106] Calculate the bispectral data of time series process variables;

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

[0108] The nonlinear index of the control loop system is determined based on the squared biphase coherence.

[0109] If the nonlinear exponent is not greater than a preset exponent threshold, the system type of the control loop system is determined to be linear.

[0110] If the nonlinearity index is greater than a preset index threshold, the system type of the control loop system is determined to be nonlinear.

[0111] In this embodiment, the bispectral data of the process variable time series are calculated. It is the statistical measure of the signal of the process variable time series data in the third-order frequency domain:

[0112]

[0113] in, For discrete-time signal PV ( At a frequency of Fourier transform at time; For discrete-time signal PV ( At a frequency of The conjugate complex number of the Fourier transform at time; therefore, It can plot two independent frequency variables , A 3D diagram.

[0114] Calculate the biphase coherence function It is a bispectral Normalization results:

[0115]

[0116] in, It is the squared bicoherence, with a value between [0,1], which can be plotted against two independent frequency variables. , 3D diagram, such as Figure 5 As shown, a simple way to confirm the linearity of a system is to observe the flatness of the three-dimensional squared bicoherence plot; the flatter the plot, the more linear the system.

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

[0118]

[0119] in, It 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, with Q value chosen as 10.

[0121] if Then the control loop system is a linear system, if If so, the control loop system is a nonlinear system.

[0122] S402: When the system type is linear, determine the oscillation source of the control loop system based on 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 satisfies the oscillation condition.

[0123] In one embodiment provided in this application, based on the above-described scheme, optionally, the oscillation source of the control loop system is determined according to the target frequency band data and the autocorrelation function sequence of the target frequency band data, including:

[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 condition of oscillating behavior, and obtain the determination result;

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

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

[0128]

[0129] judge and Whether oscillation exists can be determined by referring to the description in section S103 above, and will not be repeated here.

[0130] like If oscillation behavior exists, then external oscillation disturbances are one of the causes of oscillation in that frequency range of the control loop; if the conditions are not met, then external oscillation disturbances are not the cause of oscillation.

[0131] like If oscillation behavior exists, then controller over-tuning is one of the reasons for oscillation in that frequency range of the control loop; if the conditions are not met, then controller over-tuning is not the cause of oscillation.

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

[0133] In one embodiment provided in this application, based on the above-described scheme, optionally, the oscillation source of the control loop system is determined according to the time difference sequence of the controller output value and the time difference sequence of the target frequency band data, including:

[0134] Based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data, determine the time proportion of the viscous motion mode of the valve in the control loop system.

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

[0136] In this embodiment, the time difference between the controller output value and the target frequency band data can be calculated separately, and the value of the difference 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 difference 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 mode in the xy plane.

[0138] Remove the SS symbols from the sequence and merge identical consecutive symbols to further simplify the symbol sequence. For example, [II,IS,IS,SS,DI,DI,DI,DD] is modified to: [II,IS2,SS,DI3,DD];

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

[0140]

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

[0142] and These represent the total number of patterns IS and DS, respectively.

[0143] Valve stickiness diagnosis: If the signal is random, the value of r1 is approximately 0.25, as r1 represents two of the eight modes. Therefore, if the exponential value of r1 is greater than 0.25, valve stickiness is considered the source of oscillation. If the exponential value of r1 is less than 0.25, valve stickiness is not considered the source of oscillation.

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

[0145] If no source of oscillation is detected (valve stickiness, external disturbances, improper controller tuning), then the oscillation originates from other nonlinear factors in the control loop system besides valve stickiness, such as excessive valve dead zone, valve output oversaturation, sensor failure, or severe nonlinearity of the controlled object itself.

[0146] See Figure 7 This application provides a flowchart of an oscillation tracing process for an industrial process control loop system. First, MV and PV data from the control loop system are collected. Then, the collected data undergoes preprocessing. After preprocessing the PV data, a pass-through filter is applied to the preprocessed PV data to obtain multiple frequency band data. For each frequency band data, an autocorrelation function sequence is calculated. Based on the autocorrelation function sequence, an oscillation index corresponding to the frequency band data is determined. The oscillation index is used to determine whether the frequency band data meets a preset oscillation condition. If at least one frequency band data satisfies the oscillation condition, it is determined that the control loop system oscillates, and the frequency band data satisfying the oscillation condition is identified as the target frequency band data. The system type of the industrial process control loop system is further evaluated; the system type is either a linear system type or a nonlinear system type. The oscillation tracing method corresponding to this system type is selected to perform oscillation tracing on the industrial process control loop system.

[0147] and Figure 1 Corresponding to the method, embodiments of this application also provide an oscillation detection device for a control loop system, used for... Figure 1 The specific implementation of the method is shown in the following structural diagram. Figure 8 As shown, it includes:

[0148] Acquisition unit 801 is used to acquire the timing data of process variables of the control loop system;

[0149] 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 determining unit 803 is configured to, for each frequency band data, calculate the autocorrelation function sequence of the frequency band data, determine the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence, and determine whether the frequency band data meets the preset oscillation conditions based on the oscillation index;

[0151] The second determining unit 804 is used to determine that the control loop system is oscillating if at least one of the frequency band 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 embodiments of this application are the same as those of the oscillation detection method of the control loop system disclosed in the above embodiments of this application. Please refer to the corresponding parts of the oscillation detection method of the control loop system provided in the above embodiments of this application, and they will not be repeated here.

[0153] This application embodiment also provides a storage medium, which includes stored instructions, wherein, when the instructions are executed, the device where the storage medium is located executes the oscillation detection method of the control loop system described above.

[0154] This application also provides an electronic device, the structural schematic diagram of which is shown below. Figure 9 As shown, it specifically includes a memory 901 and one or more instructions 902, wherein one or more instructions 902 are stored in the memory 901 and configured to be executed by one or more processors 903 to perform the following operations:

[0155] Acquire the timing data of process variables in the control loop system;

[0156] The time-series data of the process variables are subjected to bandpass filtering to obtain data in multiple frequency bands;

[0157] For each frequency band data, calculate the autocorrelation function sequence of the frequency band data, determine the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence, and determine whether the frequency band data meets the preset oscillation conditions based on the oscillation index;

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

[0159] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

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

[0161] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0162] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0163] The above provides a detailed description of the oscillation detection method for a control loop system provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and its core ideas. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for detecting oscillations in a control loop system, characterized in that, include: Acquire the timing data of process variables in the control loop system; The time-series data of the process variables are subjected to bandpass filtering to obtain data in multiple frequency bands; For each frequency band data, calculate the autocorrelation function sequence of the frequency band data, determine the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence, and determine whether the frequency band data meets the preset oscillation conditions based on the oscillation index; If at least one of the frequency band data satisfies the oscillation condition, then it is determined that the control loop system is oscillating; After determining that the control loop system oscillates, the process further includes: Determine the system type of the control loop system, which is either linear or nonlinear. When the system type is linear, the oscillation source of the control loop system is determined based on 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 satisfies the oscillation condition. When the system type is nonlinear, the time difference sequence of the controller output value and the target frequency band data in the control loop system are calculated respectively; the oscillation source of the control loop system is determined based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data. The step of determining the oscillation source of the control loop system based on the target frequency band data and the autocorrelation function sequence of the target frequency band data includes: determining the sequence difference between the first part and the second part of the autocorrelation function sequence; determining whether the second part of the autocorrelation function sequence and the sequence difference satisfy the existence of oscillation behavior, and obtaining a determination result; and determining the oscillation source of the control loop system based on the determination result. Determining the oscillation source of the control loop system based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data includes: determining the time proportion of the viscous motion mode of the valve in the control loop system based on the time difference sequence of the controller output value and the time difference sequence of the target frequency band data; and determining the oscillation source of the control loop system based on the time proportion of the viscous motion mode of the valve.

2. The method according to claim 1, characterized in that, Determining the system type of the control loop system includes: Calculate the bispectral data of the time series data of the process variables; The squared bicoherence degree is calculated based on the bispectral data of the process variable time series data. The nonlinear index of the control loop system is determined based on the squared biphase coherence. If the nonlinear exponent is not greater than a preset exponent threshold, the system type of the control loop system is determined to be linear. If the nonlinear exponent is greater than a preset exponent threshold, the system type of the control loop system is determined to be nonlinear.

3. The method according to claim 1, characterized in that, The oscillation indices include attenuation ratio, zero-axis crossover interval regularity factor, oscillation energy ratio, and oscillation amplitude. Determining the oscillation indices corresponding to the frequency band data based on the autocorrelation function sequence includes: The oscillation period is determined based on the intersection of the autocorrelation function sequence with the zero axis; The zero-axis crossover interval regularity factor of the frequency band data is determined based on the oscillation period. The oscillation energy percentage of the frequency band data is calculated based on the power spectral density of the frequency band data and the oscillation period. The attenuation ratio corresponding to the frequency band data is calculated based on the peak and valley points of the autocorrelation function sequence. The oscillation amplitude of the frequency band data, the zero-axis crossover interval regularity factor, the oscillation energy ratio, and the attenuation ratio are used as the oscillation indicators corresponding to the frequency band data.

4. The method according to claim 3, characterized in that, Determining whether the frequency band data meets the preset oscillation conditions based on the oscillation index includes: If the attenuation ratio is greater than a preset attenuation ratio threshold, the zero-axis cross-interval regularity factor is greater than a preset factor threshold, the oscillation energy ratio is greater than a preset proportion threshold, and the oscillation amplitude is greater than a preset amplitude threshold, then the frequency band data is determined to meet the preset oscillation conditions.

5. An oscillation detection device for a control loop system, characterized in that, include: The acquisition unit is used to acquire the timing data of process variables in the control loop system. The processing unit is used to perform bandpass filtering on the time-series data of the process variables to obtain data in multiple frequency bands; The first determining unit is configured to, for each frequency band data, calculate the autocorrelation function sequence of the frequency band data, determine the oscillation index corresponding to the frequency band data based on the autocorrelation function sequence, and determine whether the frequency band data meets the preset oscillation conditions based on the oscillation index; The second determining unit is used to determine that the control loop system is oscillating if at least one of the frequency band data satisfies the oscillation condition. The oscillation detection device is also used for: Determine the system type of the control loop system, which is either linear or nonlinear. When the system type is linear, the target frequency band data and the sequence difference between the first and second parts of the autocorrelation function sequence of the target frequency band data are determined; it is determined whether the second part of the autocorrelation function sequence and the sequence difference satisfy the existence of oscillatory behavior, and the determination result is obtained; the oscillation source of the control loop system is determined based on the determination result. The target frequency band data is the frequency band data that satisfies the oscillation condition; When the system type is nonlinear, the time difference sequence of the controller output value and the target frequency band data in the control loop system 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 time proportion of the viscous motion mode of the valve in the control loop system is determined; based on the time proportion of the viscous motion mode of the valve, the oscillation source of the control loop system is determined.

6. A storage medium, characterized in that, The storage medium includes stored instructions, wherein, when the instructions are executed, the device containing the storage medium is controlled to perform the oscillation detection method of the control loop system as described in any one of claims 1 to 4.

7. An electronic device, characterized in that, It includes a memory and one or more instructions, wherein one or more instructions are stored in the memory and configured to be executed by one or more processors as described in any one of claims 1 to 4, the method for detecting oscillations in the control loop system.

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