Intelligent detection method and system for operation of pulse valve of dust remover

Abstract

The invention discloses a dust collector pulse valve operation intelligent detection method and system, and belongs to the technical field of dust collector pulse valve operation state monitoring, and the method comprises the steps: firstly obtaining pulse valve injection noise data, pulse valve air bag pressure data and dust collector outlet particulate matter concentration data of a dust collector pulse valve; a pulse valve injection noise characteristic curve, a pulse valve air bag pressure change curve and a dust remover outlet particulate matter concentration change curve are generated; then respectively generating a noise comparison result, a pressure comparison result and a particulate matter concentration comparison result; and finally, according to the noise comparison result, the pressure comparison result and the particulate matter concentration comparison result, a fault detection result is generated, and a fault warning signal is sent out. Through the detection method, multiple data can be combined for processing and analysis, so that operation detection of the pulse valve of the dust remover is efficiently completed, and the specific fault position of the pulse valve of the dust remover is judged according to a noise comparison result, a pressure comparison result and a particulate matter concentration comparison result.

Description

Technical Field

[0001] The patent of this invention relates to the technical field of dust collector pulse valve operation status monitoring, and specifically to a dust collector pulse valve operation intelligent detection method and system. Background Art

[0002] In the current industrial dust removal sector, dust collectors are key equipment. Their efficient and stable operation is crucial for maintaining a healthy production environment, protecting employee health, and complying with environmental emission standards. However, an often overlooked yet crucial aspect of daily dust collector operation and maintenance is monitoring the operation of the pulse valve. As a core component of the dust collector's pulse cleaning system, the pulse valve's performance directly impacts the dust collector's cleaning performance and overall dust removal efficiency.

[0003] Despite the crucial role pulse valves play in dust collectors, significant technical gaps remain in the pulse valve operation monitoring systems currently available for most dust collectors. This situation stems primarily from the extremely short start-up and shutdown times of pulse valves, typically only around 0.1 seconds. This high-speed response makes it difficult for traditional monitoring methods to effectively capture their operating status. Traditional monitoring methods, such as manual inspections and simple mechanical switch testing, are not only inefficient but also unable to accurately determine the specific fault location.

[0004] Therefore, there is an urgent need to provide an intelligent detection method for the operation of a dust collector pulse valve that can efficiently complete the operation detection of the dust collector pulse valve and determine the specific fault location. Summary of the Invention

[0005] To address the issues raised in the aforementioned background technology, the present invention provides a method and system for intelligently detecting the operation of a dust collector pulse valve. This method addresses the current technical issues of dust collector pulse valve operation status monitoring, which are low efficiency and inability to accurately determine the specific fault location.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides an intelligent detection method for the operation of a pulse valve of a dust collector, comprising:

[0008] Obtain pulse valve blowing noise data, pulse valve air bag pressure data and dust collector outlet particulate matter concentration data when the dust collector pulse valve is in operation;

[0009] Based on the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data, a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve and a dust collector outlet particulate matter concentration change curve are generated;

[0010] Compare the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, compare the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, and compare the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result;

[0011] A fault detection result is generated according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, and a corresponding fault warning signal is issued based on the fault detection result.

[0012] In one possible design, the pulse valve blowing noise data, pulse valve air bag pressure data, and dust collector outlet particulate matter concentration data are obtained during the operation of the dust collector pulse valve, including:

[0013] In response to the pulse valve blowing action trigger signal, the pulse valve blowing noise signal, the pulse valve air bag pressure signal and the dust collector outlet particulate matter concentration signal are collected, and the pulse valve blowing noise signal, the pulse valve air bag pressure signal and the dust collector outlet particulate matter concentration signal are time-aligned using the linear interpolation method;

[0014] The collected pulse valve jet noise signal is band-pass filtered, the noise energy of each noise sampling point is marked, the noise start time, noise peak value and noise duration are recorded, and the noise energy, noise energy peak value, noise start time and noise duration of each noise sampling point are used as the pulse valve jet noise data;

[0015] Perform low-pass filtering on the collected pulse valve air bag pressure signal, mark the pressure value of each pressure sampling point, and use the pressure value of each pressure sampling point as the pulse valve air bag pressure data, wherein each pressure sampling point is bound to a pressure change stage label, and the pressure change stage label includes a pressure drop stage label and a pressure recovery stage label;

[0016] The collected dust collector outlet particle concentration signal is baseline calibrated, the particle concentration at each particle concentration sampling point is marked, and the particle concentration at each particle concentration sampling point is used as the dust collector outlet particle concentration data.

[0017] In one possible design, based on the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data, a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve, and a dust collector outlet particulate matter concentration change curve are generated, including:

[0018] Normalizing the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data respectively;

[0019] With time as the horizontal axis and noise energy as the vertical axis, the noise energy of each noise sampling point is plotted as a pulse valve jet noise characteristic curve;

[0020] With time as the horizontal axis and pressure value as the vertical axis, the pressure values of each pressure sampling point are plotted as a pulse valve air bag pressure change curve;

[0021] With time as the horizontal axis and particle concentration as the vertical axis, the particle concentration at each particle concentration sampling point is plotted as a particle concentration change curve at the dust collector outlet.

[0022] In one possible design, the generated pulse valve jet noise characteristic curve is compared with a noise calibration curve to generate a noise comparison result, including:

[0023] Comparing the generated pulse valve blowing noise characteristic curve with the noise calibration curve to determine whether the pulse valve blowing noise characteristic curve is abnormal;

[0024] If yes, then the noise comparison result is output as abnormal noise characteristics, if not, then the noise comparison result is generated as normal noise characteristics;

[0025] Accordingly, the generated pulse valve air bag pressure change curve is compared with the pressure calibration curve to generate a pressure comparison result, which includes:

[0026] Comparing the generated pulse valve air bag pressure change curve with the pressure calibration curve to determine whether the pulse valve air bag pressure change curve is abnormal;

[0027] If yes, then the pressure comparison result is output as abnormal pressure characteristics, if no, then the pressure comparison result is generated as normal pressure characteristics;

[0028] Accordingly, the generated particle concentration change curve at the dust collector outlet is compared with the particle concentration calibration curve to generate a particle concentration comparison result, which includes:

[0029] Comparing the generated particle concentration change curve at the dust collector outlet with the particle concentration calibration curve to determine whether the particle concentration change curve at the dust collector outlet is abnormal;

[0030] If so, the particle concentration comparison result is output as abnormal particle concentration characteristics; if not, the particle concentration comparison result is generated as normal particle concentration characteristics.

[0031] In one possible design, the generated pulse valve blowing noise characteristic curve is compared with a noise calibration curve to determine whether the pulse valve blowing noise characteristic curve is abnormal, including:

[0032] Based on the pulse valve blowing noise characteristic curve, the noise frequency domain characteristics of the pulse valve blowing noise and the noise energy distribution of the pulse valve blowing noise are obtained, and based on the noise calibration curve, the standard noise frequency domain characteristics and the standard noise energy distribution are obtained;

[0033] Based on the noise frequency domain characteristics of the pulse valve jet noise and the frequency domain characteristics of the standard noise, the frequency domain characteristic similarity is calculated; based on the noise energy distribution of the pulse valve jet noise and the energy distribution of the standard noise, the energy distribution similarity is calculated;

[0034] Obtaining a preset noise similarity threshold, determining whether the frequency domain feature similarity reaches the preset noise similarity threshold, and determining whether the energy distribution similarity reaches the preset noise similarity threshold; if both the frequency domain feature similarity and the energy distribution similarity reach the preset noise similarity threshold, then the pulse valve jet noise characteristic curve is considered normal; otherwise, then the pulse valve jet noise characteristic curve is considered abnormal;

[0035] Accordingly, the generated pulse valve air bag pressure change curve is compared with the pressure calibration curve to determine whether the pulse valve air bag pressure change curve is abnormal, which includes:

[0036] Based on the pulse valve air bag pressure change curve, the pulse valve air bag pressure drop phase characteristics and the pulse valve air bag pressure rise phase characteristics are obtained, and based on the pressure calibration curve, the standard pressure drop phase characteristics and the standard pressure rise phase characteristics are obtained;

[0037] Based on the characteristics of the pulse valve air bag pressure drop stage and the standard pressure drop stage characteristics, the pressure drop stage characteristics similarity is calculated; based on the characteristics of the pulse valve air bag pressure rise stage and the standard pressure rise stage characteristics, the pressure rise stage characteristics similarity is calculated;

[0038] Obtaining a preset pressure similarity threshold, determining whether the characteristic similarity of the pressure drop phase reaches the preset pressure similarity threshold, and determining whether the characteristic similarity of the pressure recovery phase reaches the preset pressure similarity threshold; if both the characteristic similarity of the pressure drop phase and the characteristic similarity of the pressure recovery phase reach the preset pressure similarity threshold, then it is considered that the pulse valve air bag pressure change curve is normal; otherwise, it is considered that the pulse valve air bag pressure change curve is abnormal;

[0039] Accordingly, the generated particle concentration change curve at the dust collector outlet is compared with the particle concentration calibration curve to determine whether the particle concentration change curve at the dust collector outlet is abnormal, which includes:

[0040] Based on the dust collector outlet particle concentration change curve, obtain the dust collector outlet particle concentration peak value and the dust collector outlet particle concentration drop rate, and based on the particle concentration calibration curve, obtain the standard particle concentration peak value and the standard particle concentration drop rate;

[0041] The similarity of the peak concentration of the particle matter at the dust collector outlet and the peak concentration of the standard particle matter is calculated. The similarity of the particle concentration decline rate is calculated based on the decline rate of the particle matter at the dust collector outlet and the decline rate of the standard particle concentration.

[0042] Obtain a preset particle matter concentration similarity threshold, determine whether the particle matter concentration peak similarity reaches the preset particle matter concentration similarity threshold, and determine whether the particle matter concentration decline rate similarity reaches the preset particle matter concentration similarity threshold; if both the particle matter concentration peak similarity and the particle matter concentration decline rate similarity reach the preset particle matter concentration similarity threshold, then it is considered that the particle matter concentration change curve at the dust collector outlet is normal; otherwise, it is considered that the particle matter concentration change curve at the dust collector outlet is abnormal.

[0043] In a possible design, before comparing the generated pulse valve jet noise characteristic curve with the noise calibration curve, the method further includes:

[0044] Acquire historical pulse valve blowing noise data, and establish a historical pulse valve blowing noise data set based on the historical pulse valve blowing noise data;

[0045] Based on the historical pulse valve jet noise data set, a noise calibration curve is obtained;

[0046] Accordingly, before comparing the generated pulse valve air bag pressure change curve with the pressure calibration curve, the method further includes:

[0047] Acquire historical pulse valve air bag pressure data, and establish a historical pulse valve air bag pressure data set based on the historical pulse valve air bag pressure data;

[0048] Based on the historical pulse valve air bag pressure data set, a pressure calibration curve is obtained;

[0049] Accordingly, before comparing the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve, the method further includes:

[0050] Obtain historical dust collector outlet particulate matter concentration data, and establish a historical dust collector outlet particulate matter concentration data set based on the historical dust collector outlet particulate matter concentration data;

[0051] Based on the historical dust collector outlet particulate matter concentration dataset, a particulate matter concentration calibration curve was obtained.

[0052] In one possible design, generating a fault detection result based on the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result includes:

[0053] Get the preset comparison result table;

[0054] According to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, a preset comparison result table is traversed to obtain a fault detection result.

[0055] In a second aspect, the present invention provides an intelligent detection system for the operation of a pulse valve of a dust collector, comprising:

[0056] A data acquisition unit is used to acquire the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data when the dust collector pulse valve is in operation;

[0057] a data processing unit for generating a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve, and a dust collector outlet particulate matter concentration change curve based on the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data;

[0058] a result comparison unit, configured to compare the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, compare the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, and compare the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result;

[0059] The central control unit is configured to generate a fault detection result according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, and to issue a corresponding fault warning signal based on the fault detection result.

[0060] In a third aspect, the present invention provides an electronic device comprising: a memory, a processor and a transceiver communicatively connected in sequence, wherein the memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute an intelligent detection method for the operation of a dust collector pulse valve as in the first aspect or any possible design in the first aspect.

[0061] In a fourth aspect, the present invention provides a computer program product comprising instructions, wherein when the instructions are executed on a computer, the computer is caused to execute an intelligent detection method for the operation of a dust collector pulse valve as in the first aspect or any possible design of the first aspect.

[0062] Beneficial effects:

[0063] The intelligent detection method and system for the operation of the dust collector pulse valve provided by the present invention first obtains the pulse valve blowing noise data, pulse valve air bag pressure data and dust collector outlet particle concentration data when the dust collector pulse valve is in operation; and based on the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particle concentration data, generates a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve and a dust collector outlet particle concentration change curve; then compares the generated pulse valve blowing noise characteristic curve with the noise calibration curve to generate a noise comparison result, compares the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, compares the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result; finally, generates a fault detection result according to the noise comparison result, the pressure comparison result and the particle concentration comparison result, and issues a corresponding fault warning signal based on the fault detection result. Through this intelligent detection method and system, multiple data can be combined for processing and analysis to efficiently complete the operation detection of the dust collector pulse valve. Based on the noise comparison results, pressure comparison results and particle concentration comparison results, the specific fault location of the dust collector pulse valve can be determined, and an alarm message can be issued to prompt the fault information in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A flow chart of an intelligent detection method for pulse valve operation of a dust collector provided by an embodiment of the present invention;

[0065] Figure 2 A preset comparison result table provided in an embodiment of the present invention;

[0066] Figure 3 This is a functional block diagram of the intelligent detection system for pulse valve operation of a dust collector provided by an embodiment of the present invention;

[0067] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0068] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly introduced below in conjunction with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structure of the drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0069] It should be understood that although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element can be referred to as a second element, and similarly, a second element can be referred to as a first element without departing from the scope of the exemplary embodiments of the present invention.

[0070] It should be understood that the term "and / or" that may appear in this document is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B may indicate three situations: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" that may appear in this document describes another type of association object relationship, indicating that two relationships may exist. For example, A / and B may indicate two situations: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0071] Example:

[0072] like Figure 1 As shown, the first aspect of this embodiment provides an intelligent detection method for the operation of a dust collector pulse valve, which includes:

[0073] Obtain pulse valve blowing noise data, pulse valve air bag pressure data and dust collector outlet particulate matter concentration data when the dust collector pulse valve is in operation;

[0074] Based on the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data, a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve and a dust collector outlet particulate matter concentration change curve are generated;

[0075] Compare the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, compare the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, and compare the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result;

[0076] A fault detection result is generated according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, and a corresponding fault warning signal is issued based on the fault detection result.

[0077] It should be noted that this intelligent detection method for the operation of the dust collector pulse valve is combined with multiple data for processing and analysis to efficiently complete the operation detection of the dust collector pulse valve, and based on the noise comparison results, pressure comparison results and particle concentration comparison results, the specific fault location of the dust collector pulse valve is determined, and an alarm message is issued to prompt the fault information in time.

[0078] In one possible implementation, obtaining pulse valve blowing noise data, pulse valve air bag pressure data, and dust collector outlet particulate matter concentration data during the operation of the dust collector pulse valve includes:

[0079] In response to the pulse valve blowing action trigger signal, the pulse valve blowing noise signal, the pulse valve air bag pressure signal and the dust collector outlet particulate matter concentration signal are collected, and the pulse valve blowing noise signal, the pulse valve air bag pressure signal and the dust collector outlet particulate matter concentration signal are time-aligned using the linear interpolation method;

[0080] The collected pulse valve jet noise signal is band-pass filtered, the noise energy of each noise sampling point is marked, the noise start time, noise peak value and noise duration are recorded, and the noise energy, noise energy peak value, noise start time and noise duration of each noise sampling point are used as the pulse valve jet noise data;

[0081] Perform low-pass filtering on the collected pulse valve air bag pressure signal, mark the pressure value of each pressure sampling point, and use the pressure value of each pressure sampling point as the pulse valve air bag pressure data, wherein each pressure sampling point is bound to a pressure change stage label, and the pressure change stage label includes a pressure drop stage label and a pressure recovery stage label;

[0082] The collected dust collector outlet particle concentration signal is baseline calibrated, the particle concentration at each particle concentration sampling point is marked, and the particle concentration at each particle concentration sampling point is used as the dust collector outlet particle concentration data.

[0083] In one possible implementation, based on the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data, a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve, and a dust collector outlet particulate matter concentration change curve are generated, including:

[0084] Normalizing the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data respectively;

[0085] With time as the horizontal axis and noise energy as the vertical axis, the noise energy of each noise sampling point is plotted as a pulse valve jet noise characteristic curve;

[0086] With time as the horizontal axis and pressure value as the vertical axis, the pressure values of each pressure sampling point are plotted as a pulse valve air bag pressure change curve;

[0087] With time as the horizontal axis and particle concentration as the vertical axis, the particle concentration at each particle concentration sampling point is plotted as a particle concentration change curve at the dust collector outlet.

[0088] In a possible implementation, comparing the generated pulse valve jet noise characteristic curve with a noise calibration curve to generate a noise comparison result includes:

[0089] Comparing the generated pulse valve blowing noise characteristic curve with the noise calibration curve to determine whether the pulse valve blowing noise characteristic curve is abnormal;

[0090] If yes, then the noise comparison result is output as abnormal noise characteristics, if not, then the noise comparison result is generated as normal noise characteristics;

[0091] Accordingly, the generated pulse valve air bag pressure change curve is compared with the pressure calibration curve to generate a pressure comparison result, which includes:

[0092] Comparing the generated pulse valve air bag pressure change curve with the pressure calibration curve to determine whether the pulse valve air bag pressure change curve is abnormal;

[0093] If yes, then the pressure comparison result is output as abnormal pressure characteristics, if no, then the pressure comparison result is generated as normal pressure characteristics;

[0094] Accordingly, the generated particle concentration change curve at the dust collector outlet is compared with the particle concentration calibration curve to generate a particle concentration comparison result, which includes:

[0095] Comparing the generated particle concentration change curve at the dust collector outlet with the particle concentration calibration curve to determine whether the particle concentration change curve at the dust collector outlet is abnormal;

[0096] If so, the particle concentration comparison result is output as abnormal particle concentration characteristics; if not, the particle concentration comparison result is generated as normal particle concentration characteristics.

[0097] In a possible implementation, comparing the generated pulse valve blowing noise characteristic curve with a noise calibration curve to determine whether the pulse valve blowing noise characteristic curve is abnormal includes:

[0098] Based on the pulse valve blowing noise characteristic curve, the noise frequency domain characteristics of the pulse valve blowing noise and the noise energy distribution of the pulse valve blowing noise are obtained, and based on the noise calibration curve, the standard noise frequency domain characteristics and the standard noise energy distribution are obtained;

[0099] Based on the noise frequency domain characteristics of the pulse valve jet noise and the frequency domain characteristics of the standard noise, the frequency domain characteristic similarity is calculated; based on the noise energy distribution of the pulse valve jet noise and the energy distribution of the standard noise, the energy distribution similarity is calculated;

[0100] Obtaining a preset noise similarity threshold, determining whether the frequency domain feature similarity reaches the preset noise similarity threshold, and determining whether the energy distribution similarity reaches the preset noise similarity threshold; if both the frequency domain feature similarity and the energy distribution similarity reach the preset noise similarity threshold, then the pulse valve jet noise characteristic curve is considered normal; otherwise, then the pulse valve jet noise characteristic curve is considered abnormal;

[0101] Accordingly, the generated pulse valve air bag pressure change curve is compared with the pressure calibration curve to determine whether the pulse valve air bag pressure change curve is abnormal, which includes:

[0102] Based on the pulse valve air bag pressure change curve, the pulse valve air bag pressure drop phase characteristics and the pulse valve air bag pressure rise phase characteristics are obtained, and based on the pressure calibration curve, the standard pressure drop phase characteristics and the standard pressure rise phase characteristics are obtained;

[0103] Based on the characteristics of the pulse valve air bag pressure drop stage and the standard pressure drop stage characteristics, the pressure drop stage characteristics similarity is calculated; based on the characteristics of the pulse valve air bag pressure rise stage and the standard pressure rise stage characteristics, the pressure rise stage characteristics similarity is calculated;

[0104] Obtaining a preset pressure similarity threshold, determining whether the characteristic similarity of the pressure drop phase reaches the preset pressure similarity threshold, and determining whether the characteristic similarity of the pressure recovery phase reaches the preset pressure similarity threshold; if both the characteristic similarity of the pressure drop phase and the characteristic similarity of the pressure recovery phase reach the preset pressure similarity threshold, then it is considered that the pulse valve air bag pressure change curve is normal; otherwise, it is considered that the pulse valve air bag pressure change curve is abnormal;

[0105] Accordingly, the generated particle concentration change curve at the dust collector outlet is compared with the particle concentration calibration curve to determine whether the particle concentration change curve at the dust collector outlet is abnormal, which includes:

[0106] Based on the dust collector outlet particle concentration change curve, obtain the dust collector outlet particle concentration peak value and the dust collector outlet particle concentration drop rate, and based on the particle concentration calibration curve, obtain the standard particle concentration peak value and the standard particle concentration drop rate;

[0107] The similarity of the peak concentration of the particle matter at the dust collector outlet and the peak concentration of the standard particle matter is calculated. The similarity of the particle concentration decline rate is calculated based on the decline rate of the particle matter at the dust collector outlet and the decline rate of the standard particle concentration.

[0108] Obtain a preset particle matter concentration similarity threshold, determine whether the particle matter concentration peak similarity reaches the preset particle matter concentration similarity threshold, and determine whether the particle matter concentration decline rate similarity reaches the preset particle matter concentration similarity threshold; if both the particle matter concentration peak similarity and the particle matter concentration decline rate similarity reach the preset particle matter concentration similarity threshold, then it is considered that the particle matter concentration change curve at the dust collector outlet is normal; otherwise, it is considered that the particle matter concentration change curve at the dust collector outlet is abnormal.

[0109] In a possible implementation manner, before comparing the generated pulse valve jet noise characteristic curve with the noise calibration curve, the method further includes:

[0110] Acquire historical pulse valve blowing noise data, and establish a historical pulse valve blowing noise data set based on the historical pulse valve blowing noise data;

[0111] Based on the historical pulse valve jet noise data set, a noise calibration curve is obtained;

[0112] Accordingly, before comparing the generated pulse valve air bag pressure change curve with the pressure calibration curve, the method further includes:

[0113] Acquire historical pulse valve air bag pressure data, and establish a historical pulse valve air bag pressure data set based on the historical pulse valve air bag pressure data;

[0114] Based on the historical pulse valve air bag pressure data set, a pressure calibration curve is obtained;

[0115] Accordingly, before comparing the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve, the method further includes:

[0116] Obtain historical dust collector outlet particulate matter concentration data, and establish a historical dust collector outlet particulate matter concentration data set based on the historical dust collector outlet particulate matter concentration data;

[0117] Based on the historical dust collector outlet particulate matter concentration dataset, a particulate matter concentration calibration curve was obtained.

[0118] In a possible implementation, generating a fault detection result according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result includes:

[0119] Get the preset comparison result table;

[0120] According to the noise comparison result, the pressure comparison result and the particle concentration comparison result, the preset comparison result table is traversed to obtain the fault detection result. Figure 2 The figure is a schematic diagram of a preset comparison result table provided in an embodiment of the present application.

[0121] like Figure 3 As shown, the first aspect of this embodiment provides a dust collector pulse valve operation intelligent detection system, which includes:

[0122] A data acquisition unit is used to acquire the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data when the dust collector pulse valve is in operation;

[0123] a data processing unit for generating a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve, and a dust collector outlet particulate matter concentration change curve based on the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data;

[0124] a result comparison unit, configured to compare the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, compare the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, and compare the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result;

[0125] The central control unit is configured to generate a fault detection result according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, and to issue a corresponding fault warning signal based on the fault detection result.

[0126] It should be noted that, preferably, the data acquisition unit can use noise sensors, pressure sensors and particle concentration sensors to collect data; among them, the noise sensor is installed near the pulse valve to collect low-frequency noise signals during injection; the pressure sensor is installed at the pulse valve air bag to collect air bag pressure data in real time; the particle concentration sensor is installed at the dust collector outlet to monitor the instantaneous changes in particle concentration after injection; and the signal output ports of the three sensors are communicated with the data processing unit, and the data sampling frequency is preferentially preset to more than 100 times per second to ensure that the instantaneous action of the pulse valve is captured.

[0127] like Figure 4 As shown, the third aspect of this embodiment provides an electronic device, comprising: a memory, a processor and a transceiver that are communicatively connected in sequence, wherein the memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the intelligent detection method for the operation of the dust collector pulse valve as described in the first aspect of the embodiment.

[0128] For example, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in first-out memory (FIFO), and / or first-in last-out memory (FILO); specifically, the processor may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. The processor may be implemented in at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Furthermore, the processor may include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit); and the coprocessor is a low-power processor for processing data in a standby state.

[0129] In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. For example, the processor may be, but is not limited to, a microprocessor of the STM32F105 series, a reduced instruction set computer (RISC) microprocessor, an X86 architecture processor, or a processor with an integrated embedded neural network processing unit (NPU); the transceiver may be, but is not limited to, a wireless fidelity (WIFI) wireless transceiver, a Bluetooth wireless transceiver, a general packet radio service technology (GPRS) wireless transceiver, a ZigBee protocol (a low-power local area network protocol based on the IEEE802.15.4 standard, ZigBee) wireless transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. In addition, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0130] The fourth aspect of this embodiment provides a computer program product containing instructions, which, when executed on a computer, causes the computer to execute the intelligent detection method for the operation of a dust collector pulse valve as described in the first aspect of the embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0131] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. An intelligent detection method for the operation of a dust collector pulse valve, characterized in that: include: Obtain pulse valve blowing noise data, pulse valve air bag pressure data and dust collector outlet particulate matter concentration data when the dust collector pulse valve is in operation; Based on the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data, a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve and a dust collector outlet particulate matter concentration change curve are generated; Compare the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, compare the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, and compare the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result; A fault detection result is generated according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, and a corresponding fault warning signal is issued based on the fault detection result.

2. The intelligent detection method for the pulse valve operation of the dust collector according to claim 1 is characterized in that: Obtain pulse valve blowing noise data, pulse valve air bag pressure data, and dust collector outlet particulate matter concentration data during dust collector pulse valve operation, including: In response to the pulse valve blowing action trigger signal, the pulse valve blowing noise signal, the pulse valve air bag pressure signal and the dust collector outlet particulate matter concentration signal are collected, and the pulse valve blowing noise signal, the pulse valve air bag pressure signal and the dust collector outlet particulate matter concentration signal are time-aligned using the linear interpolation method; The collected pulse valve jet noise signal is band-pass filtered, the noise energy of each noise sampling point is marked, the noise start time, noise peak value and noise duration are recorded, and the noise energy, noise energy peak value, noise start time and noise duration of each noise sampling point are used as the pulse valve jet noise data; Perform low-pass filtering on the collected pulse valve air bag pressure signal, mark the pressure value of each pressure sampling point, and use the pressure value of each pressure sampling point as the pulse valve air bag pressure data, wherein each pressure sampling point is bound to a pressure change stage label, and the pressure change stage label includes a pressure drop stage label and a pressure recovery stage label; The collected dust collector outlet particle concentration signal is baseline calibrated, the particle concentration at each particle concentration sampling point is marked, and the particle concentration at each particle concentration sampling point is used as the dust collector outlet particle concentration data.

3. The intelligent detection method for the operation of the pulse valve of the dust collector according to claim 2 is characterized in that: Based on the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data, a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve and a dust collector outlet particulate matter concentration change curve are generated, including: Normalizing the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data respectively; With time as the horizontal axis and noise energy as the vertical axis, the noise energy of each noise sampling point is plotted as a pulse valve jet noise characteristic curve; With time as the horizontal axis and pressure value as the vertical axis, the pressure values of each pressure sampling point are plotted as a pulse valve air bag pressure change curve; With time as the horizontal axis and particle concentration as the vertical axis, the particle concentration at each particle concentration sampling point is plotted as a particle concentration change curve at the dust collector outlet.

4. The intelligent detection method for the operation of the pulse valve of the dust collector according to claim 1 is characterized in that: Comparing the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, including: Comparing the generated pulse valve blowing noise characteristic curve with the noise calibration curve to determine whether the pulse valve blowing noise characteristic curve is abnormal; If yes, then the noise comparison result is output as abnormal noise characteristics, if not, then the noise comparison result is generated as normal noise characteristics; Accordingly, the generated pulse valve air bag pressure change curve is compared with the pressure calibration curve to generate a pressure comparison result, which includes: Comparing the generated pulse valve air bag pressure change curve with the pressure calibration curve to determine whether the pulse valve air bag pressure change curve is abnormal; If yes, then the pressure comparison result is output as abnormal pressure characteristics, if no, then the pressure comparison result is generated as normal pressure characteristics; Accordingly, the generated particle concentration change curve at the dust collector outlet is compared with the particle concentration calibration curve to generate a particle concentration comparison result, which includes: Comparing the generated particle concentration change curve at the dust collector outlet with the particle concentration calibration curve to determine whether the particle concentration change curve at the dust collector outlet is abnormal; If so, the particle concentration comparison result is output as abnormal particle concentration characteristics; if not, the particle concentration comparison result is generated as normal particle concentration characteristics.

5. The intelligent detection method for the operation of the pulse valve of the dust collector according to claim 4 is characterized in that: Comparing the generated pulse valve blowing noise characteristic curve with the noise calibration curve to determine whether the pulse valve blowing noise characteristic curve is abnormal includes: Based on the pulse valve blowing noise characteristic curve, the noise frequency domain characteristics of the pulse valve blowing noise and the noise energy distribution of the pulse valve blowing noise are obtained, and based on the noise calibration curve, the standard noise frequency domain characteristics and the standard noise energy distribution are obtained; Based on the noise frequency domain characteristics of the pulse valve jet noise and the frequency domain characteristics of the standard noise, the frequency domain characteristic similarity is calculated; based on the noise energy distribution of the pulse valve jet noise and the energy distribution of the standard noise, the energy distribution similarity is calculated; Obtaining a preset noise similarity threshold, determining whether the frequency domain feature similarity reaches the preset noise similarity threshold, and determining whether the energy distribution similarity reaches the preset noise similarity threshold; if both the frequency domain feature similarity and the energy distribution similarity reach the preset noise similarity threshold, then the pulse valve jet noise characteristic curve is considered normal; otherwise, then the pulse valve jet noise characteristic curve is considered abnormal; Accordingly, the generated pulse valve air bag pressure change curve is compared with the pressure calibration curve to determine whether the pulse valve air bag pressure change curve is abnormal, which includes: Based on the pulse valve air bag pressure change curve, the pulse valve air bag pressure drop phase characteristics and the pulse valve air bag pressure rise phase characteristics are obtained, and based on the pressure calibration curve, the standard pressure drop phase characteristics and the standard pressure rise phase characteristics are obtained; Based on the characteristics of the pulse valve air bag pressure drop stage and the standard pressure drop stage characteristics, the pressure drop stage characteristics similarity is calculated; based on the characteristics of the pulse valve air bag pressure rise stage and the standard pressure rise stage characteristics, the pressure rise stage characteristics similarity is calculated; Obtaining a preset pressure similarity threshold, determining whether the characteristic similarity of the pressure drop phase reaches the preset pressure similarity threshold, and determining whether the characteristic similarity of the pressure recovery phase reaches the preset pressure similarity threshold; if both the characteristic similarity of the pressure drop phase and the characteristic similarity of the pressure recovery phase reach the preset pressure similarity threshold, then it is considered that the pulse valve air bag pressure change curve is normal; otherwise, it is considered that the pulse valve air bag pressure change curve is abnormal; Accordingly, the generated particle concentration change curve at the dust collector outlet is compared with the particle concentration calibration curve to determine whether the particle concentration change curve at the dust collector outlet is abnormal, which includes: Based on the dust collector outlet particle concentration change curve, obtain the dust collector outlet particle concentration peak value and the dust collector outlet particle concentration drop rate, and based on the particle concentration calibration curve, obtain the standard particle concentration peak value and the standard particle concentration drop rate; The similarity of the peak concentration of the particle matter at the dust collector outlet and the peak concentration of the standard particle matter is calculated. The similarity of the particle concentration decline rate is calculated based on the decline rate of the particle matter at the dust collector outlet and the decline rate of the standard particle concentration. Obtain a preset particle matter concentration similarity threshold, determine whether the particle matter concentration peak similarity reaches the preset particle matter concentration similarity threshold, and determine whether the particle matter concentration decline rate similarity reaches the preset particle matter concentration similarity threshold; if both the particle matter concentration peak similarity and the particle matter concentration decline rate similarity reach the preset particle matter concentration similarity threshold, then it is considered that the particle matter concentration change curve at the dust collector outlet is normal; otherwise, it is considered that the particle matter concentration change curve at the dust collector outlet is abnormal.

6. The intelligent detection method for the operation of the pulse valve of the dust collector according to claim 1 is characterized in that: Before comparing the generated pulse valve jet noise characteristic curve with the noise calibration curve, the method further includes: Acquire historical pulse valve blowing noise data, and establish a historical pulse valve blowing noise data set based on the historical pulse valve blowing noise data; Based on the historical pulse valve jet noise data set, a noise calibration curve is obtained; Accordingly, before comparing the generated pulse valve air bag pressure change curve with the pressure calibration curve, the method further includes: Acquire historical pulse valve air bag pressure data, and establish a historical pulse valve air bag pressure data set based on the historical pulse valve air bag pressure data; Based on the historical pulse valve air bag pressure data set, a pressure calibration curve is obtained; Accordingly, before comparing the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve, the method further includes: Obtain historical dust collector outlet particulate matter concentration data, and establish a historical dust collector outlet particulate matter concentration data set based on the historical dust collector outlet particulate matter concentration data; Based on the historical dust collector outlet particulate matter concentration dataset, a particulate matter concentration calibration curve was obtained.

7. The intelligent detection method for the operation of the pulse valve of the dust collector according to claim 1 is characterized in that: Generating a fault detection result according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result includes: Get the preset comparison result table; According to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, a preset comparison result table is traversed to obtain a fault detection result.

8. An intelligent detection system for the operation of a dust collector pulse valve, characterized in that: include: A data acquisition unit is used to acquire the pulse valve blowing noise data, the pulse valve air bag pressure data and the dust collector outlet particulate matter concentration data when the dust collector pulse valve is in operation; a data processing unit for generating a pulse valve blowing noise characteristic curve, a pulse valve air bag pressure change curve, and a dust collector outlet particulate matter concentration change curve based on the pulse valve blowing noise data, the pulse valve air bag pressure data, and the dust collector outlet particulate matter concentration data; a result comparison unit, configured to compare the generated pulse valve jet noise characteristic curve with the noise calibration curve to generate a noise comparison result, compare the generated pulse valve air bag pressure change curve with the pressure calibration curve to generate a pressure comparison result, and compare the generated dust collector outlet particle concentration change curve with the particle concentration calibration curve to generate a particle concentration comparison result; The central control unit is configured to generate a fault detection result according to the noise comparison result, the pressure comparison result, and the particulate matter concentration comparison result, and to issue a corresponding fault warning signal based on the fault detection result.

9. An electronic device, characterized in that: include: A memory, a processor and a transceiver that are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the intelligent detection method for the operation of a dust collector pulse valve as described in any one of claims 1 to 7.

10. A computer program product comprising instructions, characterized in that When the instruction is executed on a computer, the computer is caused to execute the intelligent detection method for the operation of a pulse valve of a dust collector as claimed in any one of claims 1 to 7.

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