Method and system for automatically identifying and removing temperature and vibration interference signals of sintering main exhaust fan
Through dynamic threshold analysis and sliding filtering technology, the temperature and vibration interference signals of the sintering main exhaust fan are intelligently identified and removed, solving the problem of false shutdown, achieving high-accuracy fault identification and stable operation, and reducing the false shutdown rate and maintenance costs.
Patent Information
- Application Number
- CN202510980278.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-16
- Publication Date
- 2025-10-17
AI Technical Summary
The existing technology in the temperature and vibration monitoring system of the sintering main exhaust fan cannot effectively distinguish between transient interference and real faults, resulting in frequent false shutdown accidents. Especially in high electromagnetic interference environments, traditional fixed thresholds and filtering methods cannot cope with rapid interference such as power grid fluctuations, resulting in a high false shutdown rate.
It adopts dynamic threshold analysis, hierarchical judgment mechanism and sliding filtering technology to intelligently identify and remove interference signals, generate and obtain temperature and vibration signal data, judge channel integrity, eliminate abnormal data, and identify instantaneous interference by dynamically comparing current and historical data, perform arithmetic averaging processing, and output alarms or shutdown instructions.
The stable operation of the sintering main exhaust fan was achieved in a high electromagnetic interference environment, the false shutdown rate was reduced to 0 times, the fault identification accuracy was increased to 99.5%, and the system response time was shortened to less than 100ms, significantly reducing maintenance costs and improving production efficiency.
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Figure CN120800002A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of industrial automation control processing, and particularly relates to a sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting method and system. BACKGROUND
[0002] At present, the sinter main exhaust fan is the main equipment in the raw material preparation process in steel production, and its reliable and stable operation is crucial to the sinter output and quality. The functions of the monitoring system include: data acquisition and monitoring of the motor stator temperature, motor front and rear bearing temperatures, and fan front and rear bearing temperatures; data acquisition and monitoring of the horizontal and vertical vibrations of the main exhaust fan front and rear bearings, and the horizontal and vertical vibrations of the fan front and rear bearings; analysis and judgment of the real-time data collected into the control system, specifically: according to the equipment protection requirements, the motor stator temperature is greater than or equal to 135 DEG C to send an alarm instruction, greater than or equal to 145 DEG C to send a stop instruction, the motor bearing temperature is greater than or equal to 85 DEG C to send an alarm instruction, greater than or equal to 90 DEG C to send a stop instruction, the fan bearing temperature is greater than or equal to 75 DEG C to send an alarm instruction, greater than or equal to 85 DEG C to send a stop instruction, the motor bearing vibration horizontal and vertical vibration is greater than or equal to 4.0 mm / s to send an alarm instruction, greater than or equal to 4.0 mm / s, and the delay is 2 seconds to send a stop instruction, the fan bearing vibration horizontal and vertical vibration is greater than or equal to 4.0 mm / s to send an alarm instruction, greater than or equal to 7.1 mm / s, and the delay is 2 seconds to send a stop instruction.
[0003] In the actual production process, due to external factor disturbance, the monitoring system is prone to collect abnormal data, and misoperation accidents occur. Therefore, it is hoped to find a sinter main exhaust control system temperature and vibration interference automatic cutting method.
[0004] That is, the traditional method only judges the fault by a fixed threshold (such as temperature greater than or equal to 145 DEG C stop), and cannot distinguish between transient interference and real fault; and mean filtering or hardware isolation is adopted, but cannot cope with power grid fluctuations and other rapid interferences; for example, a steel plant caused the vibration signal to be temporarily over-standard due to electric welding operation, and the annual average misoperation was 3 times.
[0005] In other words, the sinter main exhaust temperature and vibration monitoring system generally adopts shielding grounding, signal isolation and other measures for interference elimination. In the actual operation process, due to external factors such as 10KV power grid voltage fluctuation, high-power equipment starting, temporary maintenance electric welding operation, long-time running detection probe terminal loosening, point inspection operator misoperation, etc., the temperature and vibration are abnormally increased, and misoperation accidents occur; occasionally, the temperature and vibration sensing elements are broken and open, resulting in abnormal data collection and misoperation failure.
[0006] Therefore, in view of the technical problems of the above static threshold criterion, single filtering means and high misoperation rate, it is urgent to design and develop a sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting method and system. SUMMARY
[0007] In order to overcome the deficiencies and difficulties existing in the prior art, the purpose of the present application is to provide a sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting method and system to protect the equipment from fire in a high electromagnetic interference environment. By intelligently identifying and cutting interference signals, false shutdown accidents are avoided.
[0008] The first purpose of the present application is to provide a sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting method. The second purpose of the present application is to provide a sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting system.
[0009] The first purpose of the present application is achieved by the method comprising the following steps: generating and acquiring first data corresponding to the sinter main exhaust fan, and A / D converting the first data to generate corresponding second data; wherein the first data is temperature data and vibration signal data; the second data is converted data; judging the channel integrity of the second data processing, and discarding abnormal data processing beyond the conversion accuracy range, while generating first alarm data; interference fluctuation analysis processing corresponding to the second data and channel integrity judgment data, and identifying and cutting transient interference signal data by dynamically comparing current data with historical data; performing arithmetic average processing on the filtered data, converting to actual engineering quantity, and generating and outputting second alarm or third data according to the preset alarm threshold; wherein the third data is shutdown instruction data.
[0010] The second purpose of the present application is achieved by the system applied to the sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting method, and the system comprises: a first data generation unit for generating and acquiring first data corresponding to the sinter main exhaust fan, and A / D converting the first data to generate corresponding second data; wherein the first data is temperature data and vibration signal data; the second data is converted data; a first data judgment unit for judging the channel integrity of the second data processing, and discarding abnormal data processing beyond the conversion accuracy range, while generating first alarm data; a first data processing unit for interference fluctuation analysis processing corresponding to the second data and channel integrity judgment data, and identifying and cutting transient interference signal data by dynamically comparing current data with historical data; A second data processing unit is configured to perform arithmetic average processing on the filtered data, convert the filtered data into actual engineering quantities, and generate and output a second alarm or a third data according to a preset alarm threshold, wherein the third data is a shutdown instruction data.
[0011] The method of the present application generates and acquires first data corresponding to the sintering main exhaust fan, performs A / D conversion processing on the first data to generate corresponding second data, wherein the first data is temperature data and vibration signal data, and the second data is the converted data; judges the channel integrity of the second data, discards abnormal data that exceeds the conversion accuracy range, and generates first alarm data; analyzes and processes the second data and the channel integrity judgment data corresponding to the second data through dynamic comparison of current data and historical data, identifies and cuts off transient interference signal data; performs arithmetic average processing on the filtered data, converts the filtered data into actual engineering quantities, and generates and outputs a second alarm or a third data according to a preset alarm threshold, wherein the third data is a shutdown instruction data, and the system corresponding to the method can intelligently identify and cut off interference signals to avoid false shutdown accidents. That is, automatic judgment and abnormal alarm cutting are realized; abnormal alarms are issued for temperature, vibration sensors, and line breakage or short circuit; and false shutdown accidents of the main exhaust fan are avoided.
[0012] That is, the present application provides a method for effectively cutting off analog input interference data by discretely storing temperature and vibration AI acquisition data of the sintering main exhaust control system, segmenting the data to determine whether it is normal or abnormal, taking effective values, discarding abnormal interference values, and solving the problem of false shutdown accidents caused by temperature and vibration abnormalities caused by power grid voltage fluctuations, high-power equipment starting, temporary maintenance welding operations, long-time running detection probe terminal loosening, and misoperation of point inspection operators. At the same time, the external detection probe and line fault are also judged. In the case of ensuring the integrity of temperature and vibration acquisition data, the main exhaust system can be effectively protected to run stably, and false shutdown caused by interference data can be prevented.
[0013] In other words, the application realizes intelligent identification and accurate cutting of the sintering main exhaust fan temperature and vibration interference signals through dynamic threshold analysis, hierarchical judgment mechanism and sliding filter technology, reduces the false shutdown rate from 3 times per year to 0 times, improves the fault identification accuracy to more than 99.5%, and shortens the system response time to less than 100 ms. For different industrial scenes (steel, cement, chemical industry), through dynamic deviation rate algorithm, self-recovery design and explosion-proof optimization, the problems of power grid fluctuation, dust interference and signal drift are effectively solved, while ensuring the safety of the equipment, significantly reducing the maintenance cost (such as reducing the sensor cleaning frequency by 75%), and improving the production efficiency (such as increasing the annual production of a cement plant by 12,000 tons). The technology has been successfully applied to key equipment in multiple industries, and a single device can save false shutdown costs of 1.5-3 million yuan per year, with significant economic benefits and industrial applicability. BRIEF DESCRIPTION OF DRAWINGS
[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating laborious work.
[0015] Figure 1 The figure is a step flowchart of the automatic identification and cutting method of the sintering main exhaust fan temperature and vibration interference signals. Figure 2 The figure is a temperature and vibration collection data processing schematic diagram of an embodiment of the automatic identification and cutting method of the sintering main exhaust fan temperature and vibration interference signals. Figure 3 The figure is an abnormal fluctuation schematic diagram of vibration collection data of an embodiment of the automatic identification and cutting method of the sintering main exhaust fan temperature and vibration interference signals. Figure 4 The figure is a system architecture schematic diagram of the automatic identification and cutting system of the sintering main exhaust fan temperature and vibration interference signals. DETAILED DESCRIPTION
[0016] In order to better understand the purpose, technical solutions and advantages of the present application, the present application will be further described below in combination with the drawings and specific embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in the present description.
[0017] The present application can also be implemented or applied through other different specific examples, and each detail in the present description can be modified and changed in various ways without departing from the spirit of the present application.
[0018] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, motion condition, etc. between components in a certain posture (as shown in the drawings), and if the certain posture changes, the directional indications will also change accordingly.
[0019] In addition, if the embodiments of the present application involve descriptions such as "first", "second", etc., the descriptions of "first", "second", etc. are only for description purposes and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first" and "second" can explicitly or implicitly include at least one of the features. Secondly, the technical solutions of various embodiments can be combined with each other, but must be based on the fact that a person skilled in the art can realize it, and when the combination of technical solutions contradicts each other or cannot be realized, it should be considered that the combination of technical solutions does not exist and is not within the protection scope required by the present application.
[0020] The present application will be described in further detail below with reference to the accompanying drawings, in which Figures 1-3 As shown in the drawings, the present application provides a method for automatically identifying and cutting off temperature and vibration interference signals of a sintering main exhaust fan, which comprises the following steps: S01, generating and acquiring first data corresponding to the sintering main exhaust fan, and A / D converting and processing the first data to generate corresponding second data; wherein the first data is temperature data and vibration signal data; and the second data is converted and processed data; S02, judging the channel integrity of processing the second data, and discarding abnormal data that exceeds the conversion accuracy range, while generating first alarm data; S03, analyzing and processing the second data corresponding to the channel integrity judgment data, and identifying and cutting off the instantaneous interference signal data by dynamically comparing the current data with the historical data; S04, performing arithmetic average processing on the filtered data, converting it into actual engineering quantity, and generating and outputting second alarm or third data according to the preset alarm threshold; wherein the third data is shutdown instruction data.
[0021] The judgment processing of the channel integrity of the second data, and the discarding of the abnormal data that exceeds the conversion accuracy range, while generating the first alarm data, further comprises: S021, comparing the collected AI data with the maximum and minimum values of the module conversion accuracy, respectively; S022, if the data exceeds the range, it is determined to be abnormal, and the abnormal data is discarded and an alarm is triggered; otherwise, the next step is entered.
[0022] The judgment processing channel integrity of the second data, and discarding processing abnormal data beyond the conversion accuracy range, while generating first alarm data, further comprises: S023, if the data exceeds the maximum or minimum value of the module conversion accuracy, it is determined that the sensor is disconnected or short-circuited, the data is discarded and the first level alarm is triggered.
[0023] The interference fluctuation analysis processing corresponds to the second data and the channel integrity judgment data, and identifies and cuts off the transient interference signal data by dynamically comparing the current data with the historical data, and further comprises: S031, store the sampling data for 10 seconds, and calculate the dynamic deviation of the current data and the data for 10 seconds; S032, if the deviation exceeds 3 times the historical fluctuation range but is not sustained, it is determined that it is a transient interference, and the current data is discarded and replaced with the average of the previous 10 seconds, and the second level alarm is triggered; S033, if the deviation continues for 10 seconds and exceeds 5 times the historical fluctuation range, it is determined that it is a real fault, and a stop command data is triggered.
[0024] The arithmetic average processing is performed on the filtered data, and is converted into actual engineering quantity, and second alarm or third data is generated and output according to the preset alarm threshold, and further comprises: S041, discard the maximum and minimum values in 10 continuous sampling data, and take the arithmetic average of the remaining 8 data; S042, if the maximum or minimum value needs to be discarded for 3 consecutive samplings, it is determined that it is a sensor drift fault, and the third level alarm is triggered.
[0025] The engineering quantity conversion formula is: Among them, the upper and lower limits of the engineering quantity are set according to the motor stator, bearing temperature or vibration protection threshold.
[0026] Specifically, in the embodiment of the present application, the present application provides an automatic cutting method for temperature and vibration interference signals of a sinter main exhaust fan, comprising the following steps: collecting temperature and vibration signals in real time through a PLC analog quantity module and performing A / D conversion; judging the channel integrity of the converted data: if the data exceeds the maximum or minimum value of the module conversion precision, it is determined that the sensor is disconnected or short-circuited, the data is discarded, and a first-level alarm is triggered; performing interference fluctuation analysis on the data that passes the channel integrity judgment: storing 10 seconds of continuous sampling data, calculating the dynamic deviation of the current data from the previous 10 seconds of data; if the deviation exceeds 3 times the historical fluctuation range but is not sustained, it is determined to be transient interference, the current data is discarded and replaced with the average of the previous 10 seconds, and a second-level alarm is triggered; if the deviation continues for 10 seconds and exceeds 5 times the historical fluctuation range, it is determined to be a real fault, and a stop command is triggered; performing sliding filter processing on the valid data: discarding the maximum and minimum values of 10 continuous sampling data, and taking the arithmetic mean of the remaining 8 data; converting the filtered data into actual engineering quantities, and outputting an alarm or a stop command according to a preset threshold.
[0027] In the channel integrity judgment, the maximum and minimum values of the module conversion precision are determined by the technical specification of the PLC analog quantity module, specifically: the minimum value corresponding to the 4~20mA signal is 0, and the maximum value is 27648 (16-bit resolution); exceeding this range is determined as a hardware failure. In the interference fluctuation analysis, the calculation formula of the dynamic deviation is: When the deviation rate is >3, a second-level alarm is triggered, and when it is >5, a stop determination is triggered.
[0028] In the sliding filter processing, if the maximum or minimum value needs to be discarded for 3 consecutive samplings, it is determined to be a sensor drift fault, and a third-level alarm is triggered. The engineering quantity conversion formula is: Among them, the upper and lower limits of the engineering quantity are set according to the motor stator, bearing temperature or vibration protection threshold.
[0029] The method further includes a fault self-recovery mechanism: if the data returns to normal within 30 seconds after the transient interference alarm, the alarm record is automatically cleared; if the stop command is triggered, it can be reset after manual confirmation.
[0030] That is, the temperature and vibration interference automatic cutting method of the sinter main exhaust control system converts the temperature and vibration data collected by the PLC analog quantity module through digital-to-analog (A / D) conversion into real numbers according to the instructions provided by different types of PLCs, improves the data processing precision, and processes the collected data step by step.
[0031] The first step is channel integrity judgment. The collected AI data is compared with the maximum value and the minimum value of the module conversion accuracy by using a comparison instruction. If the AI data is greater than the maximum value or less than the minimum value, it is judged that the data input is abnormal, the input value is discarded, and an abnormal alarm is issued. If the AI data is within the module conversion accuracy range, it enters the next step of data processing. The second step is data interference fluctuation judgment. The input data is sampled and stored for 10 seconds according to a 1-second pulse. The current collected data is compared with the data 10 seconds ago. If it is greater than 3 times, it is considered that the current data is abnormal, the data is discarded, the data 10 seconds ago is taken as the current data, and an abnormal alarm is output. If the current collected data is greater than 5 times, it is considered that the current data is abnormal, the data is discarded, the data 10 seconds ago is taken as the current data, and an abnormal alarm is output. If the data is greater than 5 times for 10 seconds, it is judged that the detected data is real, and a stop signal is output. If the data is within the normal range, it enters the next step. The third step is filter data calculation and processing. The collected 10 AI data is judged to remove the maximum value and the minimum value, and the 8 effective values are taken for arithmetic average. The fourth step is to calculate the arithmetic average value according to the formula: output engineering quantity=average value / (A / D conversion upper limit-A / D conversion lower limit)×(engineering quantity upper limit-engineering quantity lower limit). According to the alarm setting requirement, the upper limit stop alarm, the upper limit alarm, the lower limit stop alarm and the lower limit alarm are judged. The fifth step is to output the processing result.
[0032] To achieve the above purpose, the application also provides a sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting system, as shown in Figure 4 The system is applied to the sinter main exhaust fan temperature and vibration interference signal automatic identification and cutting method. The system comprises: A first data generation unit is used for generating and acquiring first data corresponding to the sinter main exhaust fan, and A / D conversion processing the first data to generate corresponding second data. The first data is temperature data and vibration signal data. The second data is the data after conversion processing. A first data judgment unit is used for judging the channel integrity of the second data, discarding abnormal data exceeding the conversion accuracy range, and generating first alarm data. A first data processing unit is used for interference fluctuation analysis and processing of the second data corresponding to the channel integrity judgment data, and identifying and cutting the transient interference signal data by dynamically comparing the current data with the historical data. The second data processing unit is used for performing arithmetic average processing on the filtered data, converting the filtered data into actual engineering quantities, and generating and outputting a second alarm or third data according to a preset alarm threshold.
[0033] The first data determination unit further comprises: The first processing module is used for comparing the collected AI data with the maximum value and the minimum value of the module conversion precision respectively. The first determination module is used for determining that the data is abnormal if the data is out of range, discarding the data and triggering an alarm. The first data processing unit further comprises: The second processing module is used for storing sampling data for 10 seconds, and calculating and processing the dynamic deviation of the current data and the data for 10 seconds. The third processing module is used for determining that the deviation is a transient disturbance if the deviation exceeds 3 times the historical fluctuation range but is not sustained, discarding the current data and replacing it with the average value of the previous 10 seconds, and triggering a second-level alarm. The fourth processing module is used for determining that the deviation is a real fault if the deviation is sustained for 10 seconds and exceeds 5 times the historical fluctuation range, and triggering a shutdown instruction data. The second data processing unit further comprises: The fifth processing module is used for discarding the maximum value and the minimum value of 10 consecutive sampling data, and performing arithmetic average processing on the remaining 8 data. The second determination module is used for determining that the sensor drift fault is triggered if the maximum value or the minimum value needs to be discarded for three consecutive samplings.
[0034] The first data determination unit further comprises: The third determination module is used for determining that the sensor is disconnected or short-circuited if the data exceeds the maximum value or the minimum value of the module conversion precision, discarding the data and triggering a first-level alarm. In the second data processing unit, the engineering quantity conversion formula is: The upper and lower limits of the engineering quantity are set according to the motor stator, bearing bush temperature or vibration protection threshold.
[0035] In the system scheme embodiment of the present application, the method steps involved in the automatic identification and cutting of the sintering main exhaust fan temperature and vibration interference signal are described in detail above, that is, the function modules in the system are used to realize the steps or sub-steps in the above method embodiment, which will not be described here.
[0036] The present invention generates and acquires first data corresponding to a sintering main exhaust fan, and A / D converts the first data to generate corresponding second data. The first data comprises temperature data and vibration signal data, and the second data is the converted data. The second data is then processed to determine channel integrity, discarding abnormal data that exceeds the conversion accuracy range and simultaneously generating first alarm data. Interference fluctuation analysis is then performed on the channel integrity determination data corresponding to the second data, and transient interference signal data is identified and removed by dynamically comparing current data with historical data. The filtered data is then arithmetic averaged and converted into actual engineering quantities. A second alarm or third data is generated and output based on a preset alarm threshold. The third data is shutdown command data. A system corresponding to the method can intelligently identify and remove interference signals, avoiding accidental shutdowns. This system automatically determines and removes abnormal alarms, issues abnormal alarms for temperature and vibration sensors, and issues disconnections or short circuits in the circuit, and prevents accidental shutdowns of the main exhaust fan.
[0037] Specifically, this invention utilizes dynamic threshold analysis, a hierarchical judgment mechanism, and sliding filtering technology to intelligently identify and precisely eliminate temperature and vibration interference signals from sintering main exhaust fans. This reduces the annual false shutdown rate from an average of three to zero, improves fault identification accuracy to over 99.5%, and shortens system response time to less than 100ms. Targeted at various industrial scenarios (steel, cement, and chemical industries), this technology effectively addresses issues such as power grid fluctuations, dust interference, and signal drift through a dynamic deviation rate algorithm, self-recovery design, and explosion-proof optimization. While ensuring equipment safety, it significantly reduces maintenance costs (e.g., sensor cleaning frequency is reduced by 75%) and improves production efficiency (e.g., annual output of cement plants is increased by 12,000 tons). This technology has been successfully applied to key equipment across multiple industries, saving an average of 1.5 to 3 million yuan in false shutdown costs per unit annually, demonstrating significant economic benefits and industrial applicability.
[0038] In other words, the present invention discretely stores the temperature and vibration AI data collected by the sintering main exhaust control system, determines whether the data is normal or abnormal in segments, takes the effective value, discards the abnormal interference value, and provides an effective method for cutting out the interference data of the analog input. It solves the problem of the sintering main exhaust fan causing abnormal shutdowns due to voltage fluctuations in the power grid, startup of high-power equipment, temporary maintenance welding operations, loose terminals of the detection probe during long-term operation, and erroneous operations of the inspection operator. At the same time, it also makes judgments on external detection probe and line faults. While ensuring that the temperature and vibration collection data are not distorted, it can not only effectively protect the stable operation of the main exhaust system, but also prevent the occurrence of false shutdowns caused by interference data.
[0039] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the patent scope of the present application. It should be noted that for ordinary skilled persons in the art, without departing from the concept of the present application, several modifications and improvements can be made, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.
Claims
1. A method for automatically identifying and removing temperature and vibration interference signals of a sintering main exhaust fan, characterized in that: The method comprises the steps of: Generate and obtain first data corresponding to the sintering main exhaust fan, and A / D convert and process the first data to generate corresponding second data; wherein the first data is temperature data and vibration signal data; the second data is the converted data; determining the integrity of a channel for processing the second data, discarding abnormal data that exceeds a conversion accuracy range, and generating first alarm data; Interference fluctuation analysis and processing corresponding to the second data and channel integrity judgment data, and identifying and removing instantaneous interference signal data by dynamically comparing current data with historical data; The filtered data is subjected to arithmetic averaging and converted into actual engineering quantities, and a second alarm or third data is generated and output according to a preset alarm threshold; wherein the third data is shutdown instruction data.
2. The method for automatically identifying and removing temperature and vibration interference signals of a sintering main exhaust fan according to claim 1, characterized in that: The determining and processing the channel integrity of the second data, discarding and processing abnormal data that exceeds the conversion accuracy range, and generating the first alarm data at the same time also includes: Compare the collected AI data with the maximum and minimum values of the module conversion accuracy; If the data exceeds the range, it is judged as abnormal, discarded and an alarm is triggered; otherwise, the next step is processed.
3. The method for automatically identifying and removing temperature and vibration interference signals of a sintering main exhaust fan according to claim 1 or 2, characterized in that: The determining and processing the channel integrity of the second data, discarding and processing abnormal data that exceeds the conversion accuracy range, and generating the first alarm data at the same time also includes: If the data exceeds the maximum or minimum value of the module conversion accuracy, it is determined that the sensor is disconnected or short-circuited, the data is discarded and the first level alarm is triggered.
4. The method for automatically identifying and removing temperature and vibration interference signals of a sintering main exhaust fan according to claim 1, characterized in that: The interference fluctuation analysis and processing corresponds to the second data and the channel integrity judgment data, and identifies and removes the instantaneous interference signal data by dynamically comparing the current data with the historical data, further comprising: Store 10 seconds of continuous sampling data and calculate the dynamic deviation between the current data and the previous 10 seconds of data; If the deviation exceeds 3 times the historical fluctuation range but does not persist, it is determined to be a transient interference, and the current data is discarded and replaced with the average of the previous 10 seconds, triggering a second-level alarm; If the deviation exceeds 5 times the historical fluctuation range for 10 seconds, it is determined to be a real fault and the shutdown command data is triggered.
5. The method for automatically identifying and removing temperature and vibration interference signals of a sintering main exhaust fan according to claim 1, characterized in that: The arithmetic mean processing is performed on the filtered data, and the data is converted into actual engineering quantities, and a second alarm or third data is generated and output according to a preset alarm threshold, and further includes: Eliminate the maximum and minimum values in 10 consecutive sampling data, and take the arithmetic mean of the remaining 8 data; If the maximum or minimum value is eliminated for three consecutive samples, it is determined to be a sensor drift failure and the third level alarm is triggered.
6. The method for automatically identifying and removing temperature and vibration interference signals of a sintering main exhaust fan according to claim 1 or 5, characterized in that: The engineering quantity conversion formula is: Among them, the upper and lower limits of the engineering quantity are set according to the motor stator, bearing temperature or vibration protection threshold.
7. An automatic identification and removal system for temperature and vibration interference signals of a sintering main exhaust fan, characterized in that: The system is applied to the method for automatically identifying and removing the temperature and vibration interference signals of the sintering main exhaust fan as claimed in any one of claims 1 to 6, and the system comprises: A first data generating unit is configured to generate and obtain first data corresponding to the sintering main exhaust fan, and perform A / D conversion processing on the first data to generate corresponding second data; wherein the first data is temperature data and vibration signal data; and the second data is the converted data; a first data determination unit, configured to determine integrity of a channel for processing the second data, discard abnormal data that exceeds a conversion accuracy range, and generate first alarm data; a first data processing unit, configured to analyze and process interference fluctuations corresponding to the second data and channel integrity judgment data, and to identify and remove instantaneous interference signal data by dynamically comparing current data with historical data; The second data processing unit is used to perform arithmetic averaging on the filtered data, convert it into actual engineering quantity, and generate and output a second alarm or third data according to a preset alarm threshold; wherein the third data is shutdown instruction data.
8. The automatic identification and removal system for temperature and vibration interference signals of a sintering main exhaust fan according to claim 7 is characterized in that: The first data determination unit further includes: The first processing module is used to compare the collected AI data with the maximum and minimum values of the module conversion accuracy respectively; The first determination module is used to determine that the data is abnormal if it exceeds the range, discard it and trigger an alarm; The first data processing unit further includes: The second processing module is used to store 10 seconds of continuous sampling data and calculate and process the dynamic deviation between the current data and the data of the previous 10 seconds; The third processing module is used to determine that if the deviation exceeds 3 times the historical fluctuation range but does not persist, it is considered as a transient interference, and the current data is discarded and replaced with the average value of the previous 10 seconds, triggering a second-level alarm; The fourth processing module is used to determine that it is a real fault and trigger the shutdown instruction data if the deviation exceeds 5 times the historical fluctuation range for 10 seconds; The second data processing unit further includes: The fifth processing module is used to remove the maximum and minimum values in 10 consecutive sampling data and calculate the arithmetic mean of the remaining 8 data; The second judgment module is used to determine that it is a sensor drift fault if the maximum value or the minimum value needs to be eliminated in three consecutive samplings, and trigger the third level alarm.
9. The automatic identification and removal system for temperature and vibration interference signals of a sintering main exhaust fan according to claim 7 or 8, characterized in that: The first data determination unit further includes: The third judgment module is used to determine that the sensor is disconnected or short-circuited if the data exceeds the maximum or minimum value of the module conversion accuracy, discard the data and trigger the first level alarm; In the second data processing unit, the engineering quantity conversion formula is: Among them, the upper and lower limits of the engineering quantity are set according to the motor stator, bearing temperature or vibration protection threshold.