CN-121979063-A - Intelligent management system and method for detection data applied to reaction kettle stirrer

CN121979063ACN 121979063 ACN121979063 ACN 121979063ACN-121979063-A

Abstract

The invention discloses an intelligent management system and an intelligent management method for detection data applied to a reaction kettle stirrer, and relates to the technical field of data analysis.A ring-shaped tool is arranged in the reaction kettle stirrer, an infrared sensor is deployed on the ring-shaped tool, and an initial distance sequence is processed to obtain a reference distance sequence, a reference center coordinate and a reference circle radius; setting a monitoring period and a constant-speed inspection mode, acquiring real-time distance values by an infrared sensor according to the monitoring period, calculating instantaneous runout deviation by using the real-time distance values and the radius of the annular tool, judging instantaneous runout deviation by using a runout deviation threshold value to obtain a potential abnormal region, calculating the regional severity index of the potential abnormal region, setting the monitoring priority of all the potential abnormal regions by using the regional severity index, interrupting the constant-speed inspection mode for the potential abnormal region with high priority, executing intensive scanning of key regions, setting a fault judging rule according to faults of a historical stirrer, and analyzing and judging the real-time fault type of the approximate axis track.

Inventors

XU DONGHUA
LEI HUAJIE
ZHANG YONG
SUN ZHEN
DONG PAN
WU DI

Assignees

南京三叶流体科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260203

Claims (10)

1. The intelligent management method for the detection data applied to the reaction kettle stirrer is characterized by comprising the following steps of: S100, arranging an annular tool in a reaction kettle stirrer, deploying an infrared sensor on the annular tool, acquiring an initial distance sequence of the stirrer during working by using the infrared sensor, and processing the initial distance sequence to obtain a reference distance sequence, a reference center coordinate and a reference circle radius; S200, setting a monitoring period and a constant-speed inspection mode when the stirrer works, acquiring a real-time distance value by an infrared sensor according to the monitoring period, and calculating instantaneous runout deviation by using the real-time distance value and the radius of the annular tool; s300, presetting a jumping deviation threshold, judging instantaneous jumping deviation by using the jumping deviation threshold to obtain a potential abnormal region, calculating a region severity index of the potential abnormal region, and setting monitoring priorities of all the potential abnormal regions by using the region severity index; s400, when high monitoring priority is identified, interrupting a constant-speed inspection mode, and executing dense scanning of key areas; s500, reconstructing an approximate axis track of the stirring shaft relative to a reference center coordinate by using an interpolation method, and calculating a comprehensive jump index in a key scanning period; s600, presetting a dynamic threshold library, carrying out grading early warning after judging the comprehensive jump index by using the dynamic threshold library, setting a fault judging rule according to the faults of the historical stirrer, and analyzing and judging the real-time fault type of the approximate axle center track.
2. The intelligent management method for detecting data applied to a reaction kettle stirrer according to claim 1, wherein the step of performing intensive scanning of a key region in S400 is specifically: The method comprises the steps of presetting a priority threshold P threshold , judging as high priority when the monitoring priority of a potential abnormal area is more than or equal to the priority threshold, interrupting a constant-speed inspection mode, and executing dense scanning of a key area, wherein the dense scanning of the key area specifically comprises the steps of setting a dense angle alpha and a key scanning period T important , and restricting a condition alpha < S θ ,T important > T; And when the potential abnormal region diffuses and moves in the continuous monitoring period, the diffusion and movement region of the potential abnormal region in the next monitoring period is predicted in advance by utilizing the infrared sensor according to the diffusion and movement direction of the potential abnormal region in the continuous monitoring period, and the diffusion and movement region of the potential abnormal region in the next monitoring period is tracked and monitored in advance.
3. The intelligent management method for detection data applied to a reaction kettle stirrer according to claim 1, wherein the comprehensive jump index in S500 comprises maximum jump amount, average jump amount, main jump direction and track ovality, wherein the maximum jump amount represents the maximum value of instantaneous jump deviation of all sampling points in a key scanning period, and the average jump amount represents the average value of the instantaneous jump deviation of all sampling points in the key scanning period; The main jump direction is specifically that absolute values of instantaneous jump deviations of all sampling points are removed in an important scanning period to be used as offset vectors, the offset vectors comprise offset and directions, and the directions represent the directions of unbalance centers in reference centers during jumping; the track ellipticity is obtained by calculating the length-to-length axis ratio of the approximate axis track.
4. The intelligent management method for detecting data applied to a reaction kettle stirrer according to claim 1, wherein the fault judgment rule in S600 is specifically as follows: presetting an elliptical threshold value, and setting a fault judgment rule according to a historical stirrer fault, wherein the fault judgment rule specifically comprises the following steps: when the track ovality of the approximate axis track is smaller than an ellipse threshold value and the main jumping direction is smaller than +/-10 degrees in the continuous key scanning period, judging that the fault is 'static mass unbalance'; when the track ovality of the approximate axis track is more than or equal to an ellipse threshold value and the jumping main direction shows periodic variation in a continuous key scanning period, judging that the fault is 'axial bending or dynamic misalignment'; When the approximate axis track is irregular, the fault is judged to be 'loose bearing or overlarge gap'.
5. The intelligent management method for detecting data applied to a reaction kettle stirrer according to claim 1, wherein the step S100 of processing the initial distance sequence to obtain a reference distance sequence, a reference center coordinate and a reference circle radius is specifically as follows: After the stirrer of the reaction kettle is started and reaches the rated rotation speed, the infrared sensor is utilized to rotate at a constant speed along the annular tool for one circle, the infrared sensor is used for collecting the infrared sensor at intervals of a fixed angle theta, an initial distance sequence D 0 ={d 1 、d 2 、...、d n },d 1 、d 2 、...、d n of n positions is collected and represents the 1 st, 2 nd, the first and the n positions of initial distances collected by the infrared sensor, the initial distances represent the distances between the infrared sensor and a stirring shaft of the stirrer, the initial distance sequence is processed by a mean filtering algorithm to obtain a reference distance sequence D base , and the theta is less than or equal to 1 degree; Converting the distance value measured by the infrared sensor into polar coordinates of the stirring shaft surface point by utilizing the inner radius R ring of the annular tool, wherein the formula is ρ i =R ring -d i , ρ i represents the radial distance from the center of the annular tool corresponding to the ith position to the stirring shaft surface point, and d i represents the reference distance of the ith position in the reference distance sequence; Collecting angles of each position and combining the corresponding radial distances, and calculating to obtain Cartesian coordinates (x i ,y i ) of the corresponding stirring shaft surface points of each position; And (3) setting a round equation to be fitted, substituting all the Cartesian coordinates of the stirring shaft surface points converted by the reference distance sequence into (x, y) of the round equation, and calculating to obtain a reference center coordinate (x 0 ,y 0 ) and a reference circle radius R by using least square solution.
6. The intelligent management method of detection data applied to a reaction kettle stirrer according to claim 1, wherein the uniform-speed inspection mode in S400 is characterized in that an infrared sensor is collected at intervals of a fixed angle S θ , a uniform-speed VP rotates to conduct inspection, the distance of each position is collected, and each position is used as a sampling point.
7. The intelligent management method of detection data applied to a reaction kettle stirrer according to claim 1, wherein the step of setting the monitoring priority of all potential abnormal areas by using the area severity index in the step S400 is specifically as follows: Presetting a jitter deviation threshold E threshold , and marking a continuous angle area as a potential abnormal area when the instantaneous jitter deviation E > jitter deviation threshold E threshold of continuous sampling points in a sampling period, wherein the number of the continuous sampling points is more than 1; And (3) calculating a region severity index for each potential abnormal region according to the marks, sorting all the potential abnormal regions from large to small according to the region severity index, and setting monitoring priority for sorting, wherein the monitoring priority of the first sorting is highest, and the monitoring priority is sequentially reduced according to the sorting.
8. The intelligent management system for the detection data applied to the reaction kettle stirrer is characterized by comprising a reference calculation module, a real-time jumping module, a fault area identification module, a patrol mode adjustment module, a comprehensive analysis module and a fault early warning module; The reference calculation module is used for setting an annular tool in the reaction kettle stirrer, deploying an infrared sensor on the annular tool, acquiring an initial distance sequence of the stirrer during working by using the infrared sensor, and processing the initial distance sequence to obtain a reference distance sequence, a reference center coordinate and a reference circle radius; The real-time jump module is used for setting a monitoring period and a constant-speed inspection mode when the stirrer works, the infrared sensor collects real-time distance values according to the monitoring period, and the real-time distance values and the radius of the annular tool are used for calculating instantaneous jump deviation; The fault region identification module is used for presetting a jump deviation threshold, judging instantaneous jump deviation by using the jump deviation threshold to obtain a potential abnormal region, calculating the region severity index of the potential abnormal region, and setting the monitoring priority of all the potential abnormal regions by using the region severity index; The inspection mode adjustment module is used for interrupting the uniform speed inspection mode and executing dense scanning of key areas when the high monitoring priority is identified; The comprehensive analysis module is used for integrating all sampling points acquired by the infrared sensor in a monitoring period, reconstructing an approximate axis track of a stirring shaft of the stirrer relative to a reference center coordinate by using an interpolation method, and calculating a comprehensive jump index in the monitoring period; The fault early warning module is used for presetting a dynamic threshold value library, carrying out grading early warning after the comprehensive jump index is judged by utilizing the dynamic threshold value library, setting a fault judgment rule according to the faults of the historical stirrer, and analyzing and judging the real-time fault type of the approximate axle center track.
9. The intelligent management system for detecting data applied to a reaction kettle stirrer according to claim 8, wherein the comprehensive analysis module comprises an axis track unit and a comprehensive jump index unit; the axis track unit is used for reconstructing an approximate axis track of the stirring shaft relative to the reference center in the key scanning period based on all discrete sampling points by utilizing an interpolation algorithm; the comprehensive jump index unit is used for calculating the maximum jump quantity, the average jump quantity, the main jump direction and the track ovality.
10. The intelligent management system for detection data applied to the reaction kettle stirrer according to claim 8, wherein the fault early-warning module comprises an early-warning unit and a fault type unit; The early warning unit is used for presetting a dynamic threshold library, comprising an early warning threshold, an alarm threshold and a shutdown threshold, and carrying out hierarchical early warning after the comprehensive jump index is judged by using the dynamic threshold library; The fault type unit is used for presetting an ellipse threshold value and setting a fault judgment rule according to the historical stirrer faults.

Description

Intelligent management system and method for detection data applied to reaction kettle stirrer Technical Field The invention relates to the technical field of data analysis, in particular to an intelligent management system and method for detection data applied to a reaction kettle stirrer. Background The reaction kettle is a process industry core reaction device, the stirrer is used as a key moving part of the reaction kettle, and the operation state of the reaction kettle directly determines the production safety, the product quality and the energy consumption level under the severe working conditions of high temperature, high pressure, corrosion, inflammability, explosiveness and the like; When the reaction kettle stirrer has larger radial runout, the stirring blades are unstable in contact with the kettle wall or materials in the rotating process, so that the materials are unevenly flowed and mixed, meanwhile, the radial runout also can enable parts such as a stirring shaft, a bearing and a sealing element to bear additional stress and friction, so that abrasion of the parts is aggravated, the load of a motor is increased, the motor is overheated, finally, the radial runout can cause vibration and noise of equipment to be increased, the operating environment is influenced, other parts of the equipment are possibly loosened or damaged, the traditional multi-sensor fixed layout sampling point is fixed and inflexible, and the area with the most serious runout is possibly missed. Disclosure of Invention The invention aims to provide an intelligent management system and method for detection data applied to a reaction kettle stirrer, so as to solve the problems in the prior art. In order to achieve the above purpose, the present invention provides the following technical solutions: the intelligent management method of the detection data applied to the reaction kettle stirrer comprises the following steps: S100, arranging an annular tool in a reaction kettle stirrer, deploying an infrared sensor on the annular tool, acquiring an initial distance sequence of the stirrer during working by using the infrared sensor, and processing the initial distance sequence to obtain a reference distance sequence, a reference center coordinate and a reference circle radius; further, the specific steps of processing the initial distance sequence to obtain the reference distance sequence, the reference center coordinate and the reference circle radius are as follows: S101, after a reaction kettle stirrer is started and reaches a rated rotation speed, the reaction kettle stirrer rotates at a constant speed along an annular tool for one circle, the reaction kettle stirrer is collected at intervals of a fixed angle theta, an initial distance sequence D 0={d1、d2、...、dn},d1、d2、...、dn of n positions collected by the infrared sensor is used for representing initial distances of 1 st, 2 nd, third and n positions collected by the infrared sensor, the initial distances are represented by distances between the infrared sensor and a stirring shaft of the stirrer, a mean value filtering algorithm is used for processing the initial distance sequence to obtain a reference distance sequence D base, theta is less than or equal to 1 DEG, the infrared sensor rotates at a constant speed to collect the initial distance sequence, the mean value filtering algorithm is used for processing the initial distance sequence to obtain the reference distance sequence, random noise in initial collected data is effectively filtered, and stability of the reference data is ensured. The acquisition interval angle theta of the infrared sensor is limited to be less than or equal to 1 degree, the acquired initial distance sequence is ensured to cover the whole circumference of the stirring shaft, and the sampling density is enough, so that the fitted reference parameters can truly reflect the axis position and the radius size of the stirring shaft in the normal working state. S102, converting a distance value measured by an infrared sensor into a polar coordinate of a stirring shaft surface point by utilizing an inner radius R ring of the annular tool, wherein the formula is ρ i=Rring-di, ρ i represents a radial distance from the center of the annular tool corresponding to the ith position to the stirring shaft surface point, and d i represents a reference distance of the ith position in a reference distance sequence; Collecting angles of each position and combining the corresponding radial distances, and calculating to obtain Cartesian coordinates (x i,yi) of the corresponding stirring shaft surface points of each position; Let A=2x 0,B=2y0,C=R2-x02-y02, then deform the round equation into linear equation x 2+y2 =ax+by+C, substituting all the Cartesian coordinates of the stirring shaft surface points converted By the reference distance sequence into (x, y) of the linear equation, and calculating By using least square solution to obtain A, B, C; The reference center c