CN114962305B - Online detection method, device, system, equipment and medium for instability of gas compressor - Google Patents
Online detection method, device, system, equipment and medium for instability of gas compressor Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/001—Testing thereof; Determination or simulation of flow characteristics; Stall or surge detection, e.g. condition monitoring
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Abstract
The application provides a method, a device, a system, equipment and a medium for online detection of instability of a gas compressor, wherein the method comprises the following steps: receiving a plurality of target pulsating pressure signals from different pressure measurement devices, wherein the different pressure measurement devices are respectively arranged at different positions of a target compressor; extracting a characteristic signal corresponding to each target pulsating pressure signal; traversing the characteristic signals by adopting a preset sliding window aiming at each characteristic signal to obtain N sections of characteristic signals, then acquiring the relative variation between the characteristic signals of the x section and the characteristic signals before the x section, and outputting corresponding surge indication signals when the relative variation is larger than a preset surge judgment threshold value; triggering a de-asthmatic operation when the number of the surge indication signals simultaneously output is greater than a predetermined number threshold. The application can avoid the problems of instability and missed judgment and erroneous judgment caused by completely depending on the single-point pressure sensor.
Description
Technical Field
The application relates to the field of compressors, in particular to a method, a device, a system, equipment and a medium for online detection of instability of a compressor.
Background
In the development process of the air compressor of the aeroengine, a large number of test verification is often required. In a scientific research test vehicle, in order to obtain a complete stable working margin of the compressor, a large number of stability tests are inevitably required to be carried out within a full rotation speed range.
In the process of approaching the compressor from the stable working condition to the unstable working condition, the flow field is gradually deteriorated: the flow is separated from the partial air flow to form a stall group, then the stall group reaches the rotating stall, and further the stall group continuously diffuses to the upstream and the downstream to finally evolve into surge, and axial high-amplitude low-frequency air flow oscillation is formed in the full flow passage, so that the flow continuity of the whole air compressor is destroyed and is accompanied with strong mechanical vibration, and the stall group is one of important factors affecting the development and test safety of the engine.
In order to ensure safe and stable operation of the compressor in the test run process, a quick and reliable online detection system for the instability of the compressor must be established. Based on considerations of test piece protection and project test cycle control, the following are typically required for a detection system:
firstly, surge leakage judgment cannot occur, after the engine enters surge, the pressure fluctuation degree of the air flow can be increased instantaneously in a very short time (millisecond level), the possibility of automatically exiting the surge state is very low, most of the surge state is not provided with a pre-sign signal before entering the surge state, so if surge judgment and surge relief operation are not in place, a large amount of low-frequency energy mass generated by surge can continuously and repeatedly oscillate in the axial direction of a flow passage of the compressor, the deformation or crack or even fracture of a blade of the compressor can be caused, the engine structure and a test bed are seriously damaged, and irrecoverable loss is caused.
Secondly, misjudging surge is avoided as much as possible, various rapid surge relief operations triggered after surge judgment can generate fatigue damage to the rotor blade of the compressor to a certain extent, and sometimes test hardware such as a test strain gauge and the like can be damaged, but the loss caused by surge of the compressor is smaller; in addition, the erroneous judgment can also affect the test period, so that the online detection system of the air compressor can avoid the erroneous judgment as far as possible under the condition of ensuring that the judgment is not missed.
Thirdly, the calculation time of the algorithm for judging the asthma should be as short as possible, and the time from the occurrence to the complete development of the surge is tens of milliseconds, so that the timely judgment of the asthma is important.
Based on the fact that the pressure is easy to measure compared with other parameters and is sensitive to the reaction of the pneumatic instability phenomenon, the traditional instability detection is generally characterized in that a total pressure or wall static pressure sensor is arranged at an outlet of the compressor, a pressure signal acquired by the sensor is used as an input signal, and whether the compressor enters a surge or stall state is judged through extraction of dynamic pressure characteristics.
Because the traditional instability detection system is completely dependent on the effectiveness of a single-point pressure sensor at the outlet of the compressor, the risk of missed judgment and misjudgment caused by the failure of a sensor measuring point exists. In addition, for the multistage compressor with the characteristics of multiple stages, superhigh pressure ratio and the like, in a high-rotation-speed working state of the compressor, as the design principle of the traditional instability detection system is to analyze single outlet pulsation pressure, the first stage of instability cannot be accurately positioned and alarm is given out in the earlier stage of diffusion, the compressor often enters deep surge during alarm, the effective acquisition of a surge boundary and the test run safety are seriously influenced, and certain missing report phenomenon exists for the scene with lower surge energy under the low-rotation-speed working condition.
Disclosure of Invention
The application provides an online detection method, device, system, equipment and medium for instability of a gas compressor, which are used for solving the problem that the instability is missed and misjudged due to the fact that the prior art completely depends on a single-point pressure sensor at the outlet of the gas compressor.
In order to achieve the above object, the present application provides an online detection method for instability of a compressor, including:
receiving a plurality of target pulsating pressure signals from different pressure measurement devices, wherein the different pressure measurement devices are respectively arranged at different positions of a target compressor;
extracting a characteristic signal corresponding to each target pulsating pressure signal;
traversing the characteristic signals by adopting a preset sliding window aiming at each characteristic signal to obtain N sections of characteristic signals, then acquiring the relative variation between the characteristic signals of the x section and the characteristic signals before the x section, and outputting corresponding surge indication signals when the relative variation is larger than a preset surge judgment threshold value, wherein N is more than or equal to 2, and x is less than or equal to N;
triggering a de-asthmatic operation when the number of the surge indication signals simultaneously output is greater than a predetermined number threshold.
In a preferred embodiment of the present application, the acquiring the characteristic signal corresponding to each of the target pulsating pressure signals includes:
and carrying out low-pass filtering on each target pulsating pressure signal by adopting a wavelet decomposition method to obtain a characteristic signal corresponding to each target pulsating pressure signal.
In a preferred embodiment of the present application, the acquiring the relative variation between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment includes:
calculating the average value PK of the peak-to-peak value or amplitude of the characteristic signal before the x-th segment according to the following formula (1) av,x-1 ：
Calculating the relative change R between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment according to the following formula (2) x ：
In formula (1) and formula (2), PK i Representing the peak-to-peak value or amplitude of the i-th segment characteristic signal.
In a preferred embodiment of the application, when the target compressor is a multi-stage compressor, the different pressure measuring devices are arranged on different stages of the target compressor.
In a preferred embodiment of the application, the method further comprises:
and outputting a corresponding stall indication signal when the relative variation is between a preset stall judgment threshold and the surge judgment threshold, wherein the stall judgment threshold is smaller than the surge judgment threshold.
In a preferred embodiment of the present application, to achieve the above object, the present application further provides an on-line detection device for compressor instability, including:
the signal receiving module is used for receiving a plurality of target pulsating pressure signals from different pressure measuring devices, and the different pressure measuring devices are respectively arranged at different positions of the target air compressor;
the characteristic extraction module is used for extracting characteristic signals corresponding to each target pulsating pressure signal;
the surge judging module is used for carrying out sectional processing on the characteristic signals by adopting a preset sliding window aiming at each characteristic signal to obtain N sections of characteristic signals, then obtaining the relative variation between the characteristic signals of the x section and the characteristic signals before the x section, and outputting corresponding surge indicating signals when the relative variation is larger than a preset surge judging threshold value, wherein N is more than or equal to 2, and x is less than or equal to N;
and the surge-relief triggering module is used for triggering surge-relief operation when the number of the surge indication signals which are simultaneously output is larger than a preset number threshold value.
In a preferred embodiment of the present application, the feature extraction module performs low-pass filtering on each of the target pulsating pressure signals by using a wavelet decomposition method, so as to obtain a feature signal corresponding to each of the target pulsating pressure signals.
In a preferred embodiment of the present application, the process of obtaining the relative variation between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment by the surge judging module is as follows:
calculating the average value PK of the peak-to-peak value or amplitude of the characteristic signal before the x-th segment according to the following formula (1) av,x-1 ：
Calculating the relative change R between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment according to the following formula (2) x ：
In formula (1) and formula (2), PK i Representing the peak-to-peak value or amplitude of the i-th segment characteristic signal.
In a preferred embodiment of the application, when the target compressor is a multi-stage compressor, the different pressure measuring devices are arranged on different stages of the target compressor.
In a preferred embodiment of the application, the device further comprises:
and the stall judgment module is used for outputting a corresponding stall indication signal when the relative variation is between a preset stall judgment threshold value and the surge judgment threshold value, wherein the stall judgment threshold value is smaller than the surge judgment threshold value.
In order to achieve the above object, the present application further provides an online detection system for compressor instability, including: the compressor instability on-line detection device and the pressure measurement equipment.
In a preferred embodiment of the application, the position of the pressure measuring device corresponds to the axial gap between the rotor and stator of the target compressor.
To achieve the above object, the present application also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which processor implements the steps of the aforementioned method when executing the computer program.
In order to achieve the above object, the present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the aforementioned method.
By adopting the technical scheme, the application has the following beneficial effects:
the method comprises the steps of firstly receiving a plurality of target pulsating pressure signals from different pressure measuring devices, wherein the different pressure measuring devices are respectively arranged at different positions of a target air compressor, and acquiring characteristic signals corresponding to each target pulsating pressure signal; then traversing the characteristic signals by adopting a preset sliding window aiming at each characteristic signal to obtain N sections of characteristic signals, acquiring the relative variation between the characteristic signals of the x section and the characteristic signals before the x section, and outputting corresponding surge indication signals when the relative variation is larger than a preset surge judgment threshold value; triggering a de-asthmatic operation when the number of the surge indication signals simultaneously output is greater than a predetermined number threshold. Therefore, the problem of instability and missed judgment and misjudgment caused by the fact that the prior art completely depends on a single-point pressure sensor at the outlet of the air compressor can be avoided.
Drawings
Fig. 1 is a flowchart of a compressor instability online detection method according to embodiment 1 of the present application;
fig. 2 is a schematic diagram of an online detection method for compressor instability in accordance with embodiment 1 of the present application;
FIG. 3 is a schematic diagram of a wavelet decomposition method employed in embodiment 1 of the present application;
FIG. 4 is a waveform diagram of the target pulsating pressure signal in example 1 of the present application;
FIG. 5 is a waveform diagram of a characteristic signal corresponding to a target pulsating pressure signal in embodiment 1 of the present application;
fig. 6 is an effect diagram of the compressor instability online detection method of embodiment 1 of the present application;
fig. 7 is a block diagram of the compressor instability online detection apparatus according to embodiment 2 of the present application;
fig. 8 is a hardware architecture diagram of an electronic device according to embodiment 4 of the present application.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
Example 1
The embodiment provides an online detection method for instability of a gas compressor, which is shown in fig. 1 and 2, and specifically comprises the following steps:
s1, receiving a plurality of target pulsating pressure signals from different pressure measuring devices, wherein the different pressure measuring devices are respectively arranged at different positions of a target compressor.
Specifically, the present embodiment arranges a plurality of pressure measurement devices, such as dynamic pressure probes or dynamic pressure sensors, at the outer casing of the target compressor. Wherein the number of pressure measuring devices is typically more than 2 times the number threshold required for a subsequent triggering of the de-asthmatic operation, e.g. if the number threshold is 3, the number of pressure measuring devices exceeds 6.
Preferably, the position of the pressure measuring device generally corresponds to the axial gap between the rotor and the stator of the target compressor, and the final outlet of the compressor exceeding the allowable temperature at high rotation speed is generally not arranged, so that the failure of the measuring point caused by the overhigh temperature of the outlet at high rotation speed in the process of asthma is avoided.
In the present embodiment, assuming that the received pulsating pressure signal is P (t), the data sampling frequency is Fs, and the discrete sequence of P (t) under Fs is P (m). As shown in fig. 2, each P (M) is truncated using a time window of length M to obtain a plurality of target pulsating pressure signals of length M.
S2, extracting characteristic signals corresponding to each target pulsating pressure signal.
Preferably, in this embodiment, a wavelet decomposition method is used to perform low-pass filtering on each target pulsating pressure signal, so as to obtain a characteristic signal corresponding to each target pulsating pressure signal. The specific process is as follows: first, a wavelet basis function is selected and a level n of wavelet decomposition is determined, the wavelet basis function decomposes an input target pulsating pressure signal into a low-frequency approximation signal A and a high-frequency detail signal D at different scales, and the different scales have different time and frequency resolutions. As shown in fig. 3, the signal is decomposed in n layers, each layer further decomposes the approximation signal a of the previous layer, but the detailed signal D is not considered, the decomposition relation being s=a n +D n +…+D 2 +D 1 The low frequency portion containing the main frequency component of the signal is analyzed, and on the basis of this, the peak-to-peak value or amplitude variation of the signal can be observed. FIG. 5 is a characteristic signal A obtained by 7 layers of wavelet decomposition of the pulse pressure signal of the compressor in FIG. 4 7 The frequency range is 0-40 Hz, including surge frequency. Therefore, after the signals are subjected to low-pass filtering and the high-frequency detail signals are removed, the most important approximate signals which are reserved in the surge frequency range are used as characteristic signals, and the singularity characteristics are more obvious.
S3, for each characteristic signal, respectively executing the following operations: carrying out sectional processing on the characteristic signal by adopting a preset sliding window to obtain an N (N is more than or equal to 2) section characteristic signal; and then, acquiring the relative variation between the characteristic signal of the x (x is less than or equal to N) section and the characteristic signal before the x section, and outputting a corresponding surge indicating signal when the relative variation is greater than a preset surge judging threshold value.
For example, the relative variation between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment is obtained by:
first, an average value PK of the peak-to-peak value or amplitude of the characteristic signal before the x-th segment is calculated according to the following formula (1) av,x-1 ：
Then, a relative change amount R between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment is calculated according to the following formula (2) x ：
In formula (1) and formula (2), PK i Representing the peak-to-peak value or amplitude of the i-th segment characteristic signal.
And S4, triggering the anti-surge operation when the number of the surge indicating signals which are simultaneously output is larger than a preset number threshold value.
According to the embodiment, the plurality of pressure measuring devices are arranged at different positions of the target compressor, and surge judgment is carried out according to the pulsation pressure signals acquired by all the pressure measuring devices, so that the problems of instability and missed judgment and misjudgment caused by the fact that the prior art completely depends on a single-point pressure sensor at the outlet of the compressor can be avoided.
In addition, the method of the embodiment further includes: and when the relative variation is between a preset stall judgment threshold value and the surge judgment threshold value, judging that the target compressor stalls, and outputting a corresponding stall indication signal, wherein the stall judgment threshold value is smaller than the surge judgment threshold value. When the relative variation is smaller than the stall judgment threshold, the target compressor is judged to have no stall and surge, and no indication signal is required to be output.
Preferably, when the target compressor is a multi-stage compressor, the different pressure measurement devices are disposed on different stages of the target compressor.
For example, when the target compressor includes a front stage, an intermediate stage and a rear stage, since the multistage compressor has different positions of the first stall stage at different rotational speeds, the rear stage is firstly flushed at a high rotational speed, and the front stage is flushed at a low rotational speed, the pressure measuring devices are respectively provided on the different stages of the target compressor, so that the first stall stage can be accurately positioned and alarmed at a diffusion early stage, thereby improving the accuracy and reliability of the settling.
The test result of a performance test piece of a multi-stage compressor is shown in fig. 6, fig. 6 is a time domain diagram of a pulsation pressure signal and a corresponding surge judging indication signal acquired by pressure measuring equipment arranged at a later stage at the surge inlet time, the surge indicating signal is sent out within 0.025s after the surge indicating signal by taking the starting time of the abrupt change of total pressure as the surge inlet time, and therefore the purpose of timely surge judging is achieved.
Example 2
The embodiment provides an on-line detection device for instability of a compressor, as shown in fig. 7, the device specifically includes: a signal receiving module 11, a feature extraction module 12, a surge judging module 13 and a surge relief triggering module 14.
The following describes each of the above modules in detail:
the signal receiving module 11 is configured to receive a plurality of target pulsating pressure signals from different pressure measurement devices, where the different pressure measurement devices are respectively disposed at different positions of the target compressor.
Specifically, the present embodiment arranges a plurality of pressure measurement devices, such as dynamic pressure probes or dynamic pressure sensors, at the outer casing of the target compressor. Wherein the number of pressure measuring devices is typically more than 2 times the number threshold required for a subsequent triggering of the de-asthmatic operation, e.g. if the number threshold is 3, the number of pressure measuring devices exceeds 6.
Preferably, the position of the pressure measuring device generally corresponds to the axial gap between the rotor and the stator of the target compressor, and the final outlet of the compressor exceeding the allowable temperature at high rotation speed is generally not arranged, so that the failure of the measuring point caused by the overhigh temperature of the outlet at high rotation speed in the process of asthma is avoided.
In the present embodiment, assuming that the received pulsating pressure signal is P (t), the data sampling frequency is Fs, and the discrete sequence of P (t) under Fs is P (m). As shown in fig. 2, each P (M) is truncated using a time window of length M to obtain a plurality of target pulsating pressure signals of length M.
The feature extraction module 12 is configured to extract a feature signal corresponding to each of the target pulsating pressure signals.
Preferably, in this embodiment, a wavelet decomposition method is used to perform low-pass filtering on each target pulsating pressure signal, so as to obtain a characteristic signal corresponding to each target pulsating pressure signal. The specific process is as follows: first, a wavelet basis function is selected and a level n of wavelet decomposition is determined, the wavelet basis function decomposes an input target pulsating pressure signal into a low-frequency approximation signal A and a high-frequency detail signal D at different scales, and the different scales have different time and frequency resolutions. As shown in fig. 3, the signal is decomposed in n layers, each layer further decomposes the approximation signal a of the previous layer, but the detailed signal D is not considered, the decomposition relation being s=a n +D n +…+D 2 +D 1 The low frequency portion containing the main frequency component of the signal is analyzed, and on the basis of this, the peak-to-peak value or amplitude variation of the signal can be observed. FIG. 5 is a characteristic signal A obtained by 7 layers of wavelet decomposition of the pulse pressure signal of the compressor in FIG. 4 7 The frequency range is 0-40 Hz, including surge frequency. Therefore, after the signals are subjected to low-pass filtering and the high-frequency detail signals are removed, the most important approximate signals which are reserved in the surge frequency range are used as characteristic signals, and the singularity characteristics are more obvious.
The surge judging module 13 is configured to perform the following operations for each of the characteristic signals: carrying out sectional processing on the characteristic signal by adopting a preset sliding window to obtain an N (N is more than or equal to 2) section characteristic signal; and then, acquiring the relative variation between the characteristic signal of the x (x is less than or equal to N) section and the characteristic signal before the x section, and outputting a corresponding surge indicating signal when the relative variation is greater than a preset surge judging threshold value.
For example, the relative variation between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment is obtained by:
first, an average value PK of the peak-to-peak value or amplitude of the characteristic signal before the x-th segment is calculated according to the following formula (1) av,x-1 ：
Then, a relative change amount R between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment is calculated according to the following formula (2) x ：
In formula (1) and formula (2), PK i Representing the peak-to-peak value or amplitude of the i-th segment characteristic signal.
The surge relief triggering module 14 is configured to trigger a surge relief operation when the number of surge indication signals that are simultaneously output is greater than a predetermined number threshold.
According to the embodiment, the plurality of pressure measuring devices are arranged at different positions of the target compressor, and surge judgment is carried out according to the pulsation pressure signals acquired by all the pressure measuring devices, so that the problems of instability and missed judgment and misjudgment caused by the fact that the prior art completely depends on a single-point pressure sensor at the outlet of the compressor can be avoided.
In addition, the device of this embodiment further includes: and the stall judging module is used for judging that the target compressor stalls when the relative variation is between a preset stall judging threshold value and the surge judging threshold value and outputting a corresponding stall indicating signal, wherein the stall judging threshold value is smaller than the surge judging threshold value.
Preferably, when the target compressor is a multi-stage compressor, the different pressure measurement devices are disposed on different stages of the target compressor.
For example, when the target compressor includes a front stage, an intermediate stage and a rear stage, since the multistage compressor has different positions of the first stall stage at different rotational speeds, the rear stage is firstly flushed at a high rotational speed, and the front stage is flushed at a low rotational speed, the pressure measuring devices are respectively provided on the different stages of the target compressor, so that the first stall stage can be accurately positioned and alarmed at a diffusion early stage, thereby improving the accuracy and reliability of the settling.
Example 3
The embodiment provides an online detection system for instability of a gas compressor, which specifically comprises: the compressor instability online detection apparatus according to embodiment 2 and a plurality of pressure measurement devices, wherein each pressure measurement device is electrically connected to the compressor instability online detection apparatus.
Specifically, a plurality of pressure measurement devices (such as a dynamic pressure probe or a dynamic pressure sensor) of the present embodiment are provided on the outer casing of the target compressor. Wherein the number of pressure measuring devices is typically more than 2 times the number threshold required for a subsequent triggering of the de-asthmatic operation, e.g. if the number threshold is 3, the number of pressure measuring devices exceeds 6.
Preferably, the position of the pressure measuring device generally corresponds to the axial gap between the rotor and the stator of the target compressor, and the final outlet of the compressor exceeding the allowable temperature at high rotation speed is generally not arranged, so that the failure of the measuring point caused by the overhigh temperature of the outlet at high rotation speed in the process of asthma is avoided.
According to the embodiment, the plurality of pressure measuring devices are arranged at different positions of the target compressor, and surge judgment is carried out according to the pulsation pressure signals acquired by all the pressure measuring devices, so that the problems of instability and missed judgment and misjudgment caused by the fact that the prior art completely depends on a single-point pressure sensor at the outlet of the compressor can be avoided.
Example 4
The present embodiment provides an electronic device, which may be expressed in the form of a computing device (for example, may be a service mechanism device), and includes a storage mechanism, a processing mechanism, and a computer program stored on the storage mechanism and capable of running on the processing mechanism, where the processing mechanism may implement the compressor instability online detection method provided in embodiment 1 when executing the computer program.
Fig. 8 shows a schematic diagram of the hardware structure of the present embodiment, and as shown in fig. 8, the electronic device 9 specifically includes:
at least one processing mechanism 91, at least one storage mechanism 92, and a bus 93 for connecting the different system components (including the processing mechanism 91 and the storage mechanism 92), wherein:
the bus 93 includes a data bus, an address bus, and a control bus.
The storage mechanism 92 includes volatile storage mechanisms such as a random access storage mechanism (RAM) 921 and/or a cache storage mechanism 922, and may further include a read only storage mechanism (ROM) 923.
The storage mechanism 92 further includes a program/utility 925 having a set (at least one) of program modules 924, such program modules 924 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The processing means 91 executes various functional applications and data processing, such as the compressor instability on-line detection method provided in embodiment 1 of the present application, by running a computer program stored in the storage means 92.
The electronic device 9 may further communicate with one or more external devices 94 (e.g., keyboard, pointing device, etc.). Such communication may occur through an input/output (I/O) interface 95. Also, the electronic device 9 may communicate with one or more networks, such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adaptation mechanism 96. The network adaptation mechanism 96 communicates with other modules of the electronic device 9 via the bus 93. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in connection with the electronic device 9, including but not limited to: microcode, device drivers, redundancy processing, external disk drive arrays, RAID (disk array) systems, tape drivers, data backup storage systems, and the like.
It should be noted that although several units/modules or sub-units/modules of an electronic device are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more units/modules described above may be embodied in one unit/module in accordance with embodiments of the present application. Conversely, the features and functions of one unit/module described above may be further divided into ones that are embodied by a plurality of units/modules.
Example 5
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processing mechanism, implements the steps of the compressor instability online detection method provided in embodiment 1.
More specifically, among others, readable storage media may be employed including, but not limited to: portable disks, hard disks, random access memory mechanisms, read-only memory mechanisms, erasable programmable read-only memory mechanisms, optical storage mechanism components, magnetic storage mechanism components, or any suitable combination of the foregoing.
In a possible embodiment, the application may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps of implementing the compressor instability online detection method of embodiment 1, when the program product is run on the terminal device.
Wherein the program code for carrying out the application may be written in any combination of one or more programming languages, the program code may execute entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device, partly on a remote device or entirely on the remote device.
While specific embodiments of the application have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and the scope of the application is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the application, but such changes and modifications fall within the scope of the application.
Claims (10)
1. The online detection method for the instability of the gas compressor is characterized by comprising the following steps of:
receiving a plurality of target pulsating pressure signals from different pressure measurement devices, wherein the different pressure measurement devices are respectively arranged at different positions of a target compressor;
extracting characteristic signals corresponding to each target pulsating pressure signal, wherein the characteristic signals corresponding to each target pulsating pressure signal are obtained by carrying out low-pass filtering on each target pulsating pressure signal by adopting a wavelet decomposition method;
traversing the characteristic signals by adopting a preset sliding window aiming at each characteristic signal to obtain N sections of characteristic signals, and then acquiring the relative variation between the characteristic signals of the x section and the characteristic signals before the x section, wherein the method comprises the following steps:
calculating the average value PK of the peak-to-peak value or amplitude of the characteristic signal before the x-th segment according to the following formula (1) av,x-1 ：
Calculating the relative change R between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment according to the following formula (2) x ：
In formula (1) and formula (2), PK i Representing the peak-to-peak value or amplitude of the i-th segment characteristic signal;
outputting a corresponding surge indication signal when the relative variation is larger than a preset surge judgment threshold, wherein N is larger than or equal to 2, and x is smaller than or equal to N;
triggering a de-asthmatic operation when the number of the surge indication signals simultaneously output is greater than a predetermined number threshold.
2. The compressor instability online detection method according to claim 1, wherein when the target compressor is a multi-stage compressor, the different pressure measurement devices are disposed on different stages of the target compressor.
3. The compressor instability online detection method of claim 1, further comprising:
and outputting a corresponding stall indication signal when the relative variation is between a preset stall judgment threshold and the surge judgment threshold, wherein the stall judgment threshold is smaller than the surge judgment threshold.
4. An on-line detection device for compressor instability, comprising:
the signal receiving module is used for receiving a plurality of target pulsating pressure signals from different pressure measuring devices, and the different pressure measuring devices are respectively arranged at different positions of the target air compressor;
the characteristic extraction module is used for extracting characteristic signals corresponding to each target pulsating pressure signal, and carrying out low-pass filtering on each target pulsating pressure signal by adopting a wavelet decomposition method to obtain the characteristic signals corresponding to each target pulsating pressure signal;
the surge judging module is used for carrying out sectional processing on the characteristic signals by adopting a preset sliding window aiming at each characteristic signal to obtain N sections of characteristic signals, and then obtaining the relative variation between the characteristic signals of the x section and the characteristic signals before the x section:
calculating the average value PK of the peak-to-peak value or amplitude of the characteristic signal before the x-th segment according to the following formula (1) av,x-1 ：
Calculating the relative change R between the characteristic signal of the x-th segment and the characteristic signal before the x-th segment according to the following formula (2) x ：
In formula (1) and formula (2), PK i Representing the peak-to-peak value or amplitude of the i-th segment characteristic signal,
outputting a corresponding surge indication signal when the relative variation is larger than a preset surge judgment threshold, wherein N is larger than or equal to 2, and x is smaller than or equal to N;
and the surge-relief triggering module is used for triggering surge-relief operation when the number of the surge indication signals which are simultaneously output is larger than a preset number threshold value.
5. The compressor instability online detection apparatus of claim 4, wherein when the target compressor is a multi-stage compressor, the different pressure measurement devices are disposed on different stages of the target compressor.
6. The compressor instability online detection apparatus of claim 4, further comprising:
and the stall judgment module is used for outputting a corresponding stall indication signal when the relative variation is between a preset stall judgment threshold value and the surge judgment threshold value, wherein the stall judgment threshold value is smaller than the surge judgment threshold value.
7. An on-line compressor instability detection system, comprising: the compressor destabilization on-line detection device according to any of the preceding claims 4-6 and the pressure measurement equipment.
8. The compressor instability online detection system of claim 7, wherein the position of the pressure measurement device corresponds to an axial gap between a rotor and a stator of the target compressor.
9. An electronic device comprising a storage means, a processing means and a computer program stored on the storage means and operable on the processing means, characterized in that the processing means implements the steps of the method according to any of claims 1-3 when the computer program is executed by the processing means.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processing means, implements the steps of the method according to any of claims 1-3.
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