CN-122006570-A - Mixer monitoring control method and system based on multi-source data fusion

CN122006570ACN 122006570 ACN122006570 ACN 122006570ACN-122006570-A

Abstract

The application provides a method and a system for monitoring and controlling a stirrer based on multi-source data fusion, and relates to the technical field of stirrer control, wherein the method comprises the steps of dynamically monitoring and obtaining multi-source operation data of the stirrer, including vibration spectrum data of a stirring shaft, acceleration response data of a supporting structure and video motion data, and carrying out collaborative fusion analysis; analyzing the frequency information to obtain frequency proximity, judging whether the frequency proximity is in a preset safety threshold, and if the frequency proximity is not in the preset safety threshold, introducing a working control plan to carry out working intervention control on the stirrer. The method solves the technical problems that in the prior art, resonance danger cannot be identified on line and is automatically avoided in the running process of the stirrer, control response is delayed, and the running stability of the stirrer is affected.

Inventors

Zhou Maoguo
HAN GUANGTAI
ZHAO GUOXING
WANG CHAO
HUANG XIULI
GAO BAODONG
WANG MINGXUE

Assignees

昌信（青岛）工程机械有限公司

Dates

Publication Date: 20260512
Application Date: 20260408

Claims (10)

1. The stirrer monitoring control method based on multi-source data fusion is characterized by comprising the following steps: dynamically monitoring to obtain multi-source operation data of the stirrer, wherein the multi-source operation data comprise stirring shaft vibration spectrum data, supporting structure acceleration response data and video motion data; Performing collaborative fusion analysis on the stirring shaft vibration spectrum data, the support structure acceleration response data and the video motion data to obtain frequency information; analyzing the frequency information to obtain frequency proximity, and judging whether the frequency proximity is in a preset safety threshold; And if the frequency proximity is not in the preset safety threshold, introducing a working control plan to carry out working intervention control on the stirrer.
2. The method for monitoring and controlling a stirrer based on multi-source data fusion as set forth in claim 1, comprising: Extracting the actual operation frequency of the stirrer in the vibration spectrum data of the stirring shaft; carrying out structural dynamics inversion by cooperating with the acceleration response data of the support structure and the video motion data to obtain a natural operation frequency; The actual operation frequency and the natural operation frequency form the frequency information; The video motion data refer to structural displacement data of any reference point on the stirrer, which is dynamically monitored through a non-contact camera.
3. The method of claim 2, wherein the structural dynamics inversion is performed in conjunction with the support structure acceleration response data and the video motion data to obtain a natural operating frequency, and further comprising: when the machine is stopped, the stirring machine is subjected to knocking test, and knocking shaking frequency is recorded; And checking the natural operation frequency according to the knocking and shaking frequency.
4. The method of monitoring and controlling a mixer based on multi-source data fusion according to claim 2, wherein analyzing the frequency information to obtain the frequency proximity comprises: performing spectrum plotting treatment on the actual operating frequency and the natural operating frequency in sequence to obtain an actual frequency curve and a natural frequency curve respectively; Sequentially carrying out parameterization treatment on the actual frequency curve and the natural frequency curve to respectively obtain an actual sampling point set and a natural sampling point set; obtaining a target French distance value based on point comparison between the actual sampling point set and the inherent sampling point set; The frequency proximity is characterized by the target frieze distance value.
5. The method for monitoring and controlling a mixer based on multi-source data fusion according to claim 1, wherein analyzing the frequency information to obtain a frequency proximity and determining whether the frequency proximity is within a preset safety threshold comprises: acquiring an initial safety threshold; Introducing a fluid-solid coupling factor to correct the initial safety threshold to obtain the preset safety threshold; The fluid-solid coupling factor is a coefficient obtained by carrying out normalized variation coefficient weighting calculation on the slurry liquid level height, the slurry density and the fluid disturbance strength of the stirrer.
6. The method of claim 2, wherein the operation control scheme includes a rotation speed adjustment, and if the frequency proximity is not within the preset safety threshold, introducing the operation control scheme to perform operation intervention control on the mixer includes: If the frequency proximity is not in the preset safety threshold, acquiring a preset rotating speed according to the rotating speed adjustment in the operation control plan; Operating and intervening the stirrer at the preset rotating speed; the preset rotation speed refers to a rotation speed preset based on limitation of non-minimum phase system characteristics on control performance.
7. The method of claim 6, wherein the operation control scheme includes mechanical structure parameter adjustment, and wherein the operation intervention is performed on the mixer at the preset rotation speed, and then the method comprises: Acquiring rotation speed intervention information, and analyzing the rotation speed intervention information to obtain intervention proximity; If the intervention proximity is not in the preset safety threshold, adjusting according to the mechanical structure parameters in the operation control plan, and performing operation intervention on the stirrer; the mechanical structure parameter adjustment is to manufacture a replacement shaft sleeve with the inner diameter larger than the original shaft sleeve of the mixer by using a material with wear resistance and self-lubricating property, and change the contact impact frequency of the shaft and the shaft sleeve by increasing the radial clearance between the mixing shaft and the shaft sleeve, so that the equivalent natural operation frequency deviates from the forced vibration frequency range during the operation of the mixer.
8. The method of claim 2, wherein the step of performing structural dynamics inversion in conjunction with the support structure acceleration response data and the video motion data to obtain a natural operating frequency further comprises: acquiring an environment reference point; dynamically monitoring by a non-contact camera to obtain environmental displacement data corresponding to the environmental reference point; and adjusting and correcting the video motion data based on the environment displacement data.
9. The method of claim 8, wherein the environmental reference points comprise at least two stationary reference points in the environment of the mixer.
10. A multi-source data fusion-based blender monitoring control system, characterized by the steps for implementing the multi-source data fusion-based blender monitoring control method of any one of claims 1 to 9, comprising: The dynamic monitoring module is used for dynamically monitoring and obtaining multi-source operation data of the stirrer, wherein the multi-source operation data comprise stirring shaft vibration spectrum data, supporting structure acceleration response data and video motion data; The collaborative fusion analysis module is used for performing collaborative fusion analysis on the stirring shaft vibration spectrum data, the support structure acceleration response data and the video motion data to obtain frequency information; The proximity judging module is used for analyzing the frequency information to obtain frequency proximity and judging whether the frequency proximity is in a preset safety threshold value or not; And the operation intervention control module is used for introducing an operation control plan to perform operation intervention control on the stirrer if the frequency proximity is not in the preset safety threshold.

Description

Mixer monitoring control method and system based on multi-source data fusion Technical Field The application relates to the technical field of stirrer control, in particular to a stirrer monitoring control method and system based on multi-source data fusion. Background Most of the existing methods are based on vibration amplitude overrun alarming or run depending on fixed rotating speed to avoid resonance frequency points obtained by theoretical calculation, and are mainly limited to post-response to dominant faults such as vibration amplitude and the like, and natural frequency drift or excitation frequency change of a structure cannot be perceived in real time in the running process of equipment. Therefore, when the actual operation frequency gradually approaches the current actual natural frequency, on-line identification and automatic avoidance cannot be performed before the actual occurrence of resonance danger, so that control response is necessarily delayed, passive intervention can be performed after severe vibration or part damage occurs, and the operation stability and safety of the stirrer are seriously affected. In summary, in the prior art, the technical problems that the control response is delayed and the running stability of the stirrer is further affected because the resonance danger cannot be identified on line and automatically avoided in the running process of the stirrer exist. Disclosure of Invention The application aims to provide a stirrer monitoring control method and system based on multi-source data fusion, which are used for solving the technical problems that in the prior art, control response is delayed and the running stability of a stirrer is further influenced because resonance danger cannot be identified on line and is automatically avoided in the running process of the stirrer. In order to achieve the above purpose, the application provides a stirrer monitoring control method and system based on multi-source data fusion. The application provides a multi-source data fusion-based stirrer monitoring control method, which is realized by a multi-source data fusion-based stirrer monitoring control system, and comprises the steps of dynamically monitoring multi-source operation data of a stirrer, wherein the multi-source operation data comprise stirring shaft vibration spectrum data, supporting structure acceleration response data and video motion data, carrying out collaborative fusion analysis on the stirring shaft vibration spectrum data, the supporting structure acceleration response data and the video motion data to obtain frequency information, analyzing the frequency information to obtain frequency proximity, judging whether the frequency proximity is in a preset safety threshold, and introducing an operation control scheme to carry out operation intervention control on the stirrer if the frequency proximity is not in the preset safety threshold. The method comprises the steps of obtaining vibration spectrum data of a stirring shaft, extracting actual operation frequency of the stirring machine in the vibration spectrum data of the stirring shaft, carrying out structural dynamics inversion by cooperation with acceleration response data of the supporting structure and video motion data to obtain natural operation frequency, wherein the actual operation frequency and the natural operation frequency form frequency information, and the video motion data refer to structural displacement data of any reference point on the stirring machine, which is dynamically monitored through a non-contact camera. Optionally, during shutdown, performing a knocking test on the stirrer, recording knocking shaking frequency, and checking the inherent operation frequency according to the knocking shaking frequency. Optionally, acquiring an environmental reference point, dynamically monitoring by a non-contact camera to obtain environmental displacement data corresponding to the environmental reference point, and adjusting and correcting the video motion data based on the environmental displacement data. Optionally, the environmental reference points include at least two stationary reference points in the environment in which the blender is located. Optionally, performing spectral mapping on the actual operating frequency and the natural operating frequency in sequence to obtain an actual frequency curve and a natural frequency curve respectively, performing parameterization on the actual frequency curve and the natural frequency curve to obtain an actual sampling point set and a natural sampling point set respectively, performing point comparison on the basis of the actual sampling point set and the natural sampling point set to obtain a target French distance value, and representing the frequency proximity by the target French distance value. Optionally, acquiring an initial safety threshold, and introducing a fluid-solid coupling factor to correct the initial safety threshold to obtain the prese