CN-121591113-B - PHM-based lifting appliance state test and verification method

CN121591113BCN 121591113 BCN121591113 BCN 121591113BCN-121591113-B

Abstract

The invention relates to the technical field of lifting appliance detection, and discloses a lifting appliance state testing and verifying method based on PHM. The method comprises the steps of extracting design parameters from a hoisting instrument technical document, synchronously collecting high-frequency operation characteristics when the hoisting instrument starts operation, and judging whether to start a multidimensional state evaluation flow by fusing two types of data. After starting, firstly calculating an instrument design robustness index, detecting a structural vibration condition, combining the two to complete modularized segmentation and extracting a plurality of groups of evaluation units. The vibration deviation and stress diffusion speed of each unit are continuously monitored, the contribution degree of each unit to the state deviation is evaluated to obtain a contribution factor, and meanwhile, the load continuous interval is tracked. And finishing unit grading based on the load continuous interval and the contribution factor, collecting interface stress and tolerance limit load, deriving grading weight, and finally integrating the unit grading and the weight to generate a health index of the hoisting apparatus under the current working condition, so as to realize comprehensive and accurate assessment of the apparatus state.

Inventors

ZHANG ZEDONG
YU ZHIYUAN
ZHANG JITONG

Assignees

法兰泰克重工股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260128

Claims (9)

1. A lifting appliance state testing and verifying method based on PHM, the method comprising: Extracting design parameters from a lifting appliance technical document, collecting high-frequency operation characteristics when the lifting appliance starts operation, and fusing the design parameters and the high-frequency operation characteristics to determine whether to start a multi-dimensional state evaluation flow; The design parameters comprise a structural material endurance limit, a stress superposition model is constructed by reading material density, elastic modulus and material thickness, and structural surface stress is judged and polymerized with baseline stress to obtain the structural material endurance limit; the method comprises the steps of adopting standard operation test sequences and operation frequency setting to enable a tested hoisting instrument to execute cyclic load operation within a specified period, counting total operation times and generating high-frequency operation characteristics, comparing a structural material endurance limit value and the high-frequency operation characteristics with preset thresholds in sequence to generate a reasonable conclusion of the current hoisting instrument design, directly judging that the health index of the hoisting instrument in the current state is low level if the conclusion shows that the current hoisting instrument design is invalid, otherwise, executing a multidimensional state evaluation flow of the hoisting instrument in the current state; if a multidimensional state evaluation flow is started, calculating a design robustness index of the hoisting instrument, detecting the structural vibration condition of the hoisting instrument, carrying out modularized segmentation on the hoisting instrument by combining the structural vibration condition and the design robustness index, and extracting a plurality of groups of evaluation units; Continuously monitoring vibration deviation and stress diffusion speed of each evaluation unit, evaluating contribution degree of each evaluation unit to state deviation in hoisting equipment, calculating contribution factors, tracking load continuous intervals of each evaluation unit, and screening out low-contribution units as identification evaluation units; And carrying out unit grading on the contribution factors of the load continuous interval correlation corresponding units of the identification evaluation units, collecting the interface stress and the tolerance limit load of the identification evaluation units, deducing the grading weight of the identification evaluation units, and integrating the grading and the weight of the identification evaluation units to obtain the health index of the hoisting instrument under the current working condition.
2. The PHM-based lifting instrument state testing and verifying method according to claim 1, wherein the structural material endurance limit and the high-frequency operation characteristic are normalized, a weighted average algorithm is applied to output a design robustness index, vibration amplitude and frequency variation are measured by means of a micro acceleration sensor arranged on a lifting instrument structure channel, the vibration state of the lifting instrument structure is detected, and an effective vibration evaluation model based on a vibration propagation theory is adopted to output vibration intensity in unit time.
3. The lifting appliance state test and verification method based on PHM is characterized by comprising the steps of carrying out standardized conversion on design robustness indexes and vibration intensity in unit time, inputting the design robustness indexes and the vibration intensity in unit time into a decision tree model to generate unit screening index values, carrying out modularized segmentation on lifting appliances to obtain each unit of the lifting appliances, carrying out comprehensive operation on the basis of unit vibration demand measurement and unit historical failure probability, calculating expected stress load in unit time according to material stress attributes of the unit, calculating required minimum attenuation energy according to a structural damping model to obtain unit vibration demand measurement, extracting fault examples of each structural unit by retrieving lifting appliance historical records, carrying out ratio operation on the accumulated number of faults of the unit in a reference period and the number of operation periods according to the classification summary of each unit, and obtaining unit historical failure probability.
4. The PHM-based lifting appliance state test and verification method according to claim 3, wherein the unit vibration demand measurement and the unit historical failure probability are normalized and fed into the comprehensive risk analysis model operation to determine the unit liveness corresponding to each unit of the lifting appliance, the unit liveness is arranged in ascending order according to the numerical value, the unit screening index value is compared with the multiple groups of classification threshold through the predefined multiple groups of classification threshold, all the evaluation unit groups with the classification threshold not exceeding the current index value are selected, and all the evaluation units with the classification threshold positioned before the current index value in the arrangement are synchronously selected in combination with the liveness arrangement result.
5. The lifting instrument state testing and verifying method based on PHM according to claim 1 is characterized in that an embedded acceleration sensor network and a thermal imager or a strain gauge array are adopted to continuously measure vibration deviation and stress diffusion speed of each evaluation unit, a sampling interval is set to obtain continuous vibration reading through recording vibration change sequences in unit time, vibration deviation is generated according to differential and fluctuation analysis model processing, continuous stress data are obtained through monitoring internal stress change quantity of each evaluation unit in unit time, an observation period is set to obtain continuous stress data, stress at the stress observation end time is subtracted from stress at the stress observation start time and is calculated with corresponding observation time to obtain stress diffusion speed, the vibration deviation and the stress diffusion speed are subjected to standardized processing, and a linear correlation model is input to generate a contribution factor of state deviation.
6. The method according to claim 5, wherein the contribution factor of the state deviation in each evaluation unit is compared with a predefined influence threshold, if the contribution factor reaches or exceeds the influence threshold, the contribution degree of the state deviation is determined to be high, the corresponding evaluation unit is marked as low-level and excluded, otherwise, if the contribution factor is lower than the influence threshold, the contribution degree of the state deviation is determined to be low, the corresponding evaluation unit is reserved and identified, when the lifting appliance starts up, the load duration interval of the identification evaluation unit is monitored, the load start and stop moments of each identification evaluation unit at the moment of triggering the lifting appliance are captured, and the load duration interval is obtained based on a time difference operation.
7. The PHM-based lifting appliance state test and verification method according to claim 6, wherein after normalizing the contribution factors of the load duration interval association corresponding units of each identification evaluation unit, the S-shaped curve fusion model is input, and the ratings of the identification evaluation units are output.
8. The PHM-based lifting instrument state testing and verifying method according to claim 7, wherein the interface stress of each identification evaluation unit is calculated according to an elasticity theory by applying constant low load to each identification evaluation unit and measuring deformation of each identification evaluation unit, the maximum allowable deformation is set by combining structural material characteristics and establishing a fatigue response model, the tolerance limit load of each identification evaluation unit is calculated, the interface stress and the tolerance limit load of each identification evaluation unit are subjected to standardized processing, and an entropy weight distribution model is input to obtain the rating weight of each identification evaluation unit.
9. The PHM-based lifting appliance state testing and verifying method according to claim 8, wherein the ranking and ranking weight of each identification evaluation unit are integrated to output the health index of the lifting appliance under the current working condition through linear combination operation.

Description

PHM-based lifting appliance state test and verification method Technical Field The invention relates to the technical field of lifting appliance detection, in particular to a lifting appliance state testing and verifying method based on PHM. Background The hoisting apparatus is used as key equipment in the fields of industrial production, logistics transportation, building construction and the like, and the stability of the running state of the hoisting apparatus is directly related to the production efficiency and the operation safety. Along with the promotion of industrial automation level, the structure of hoisting apparatus is becoming complicated day by day, and the operating condition also presents diversified, high strength's characteristics, and this has put forward higher demands to its state monitoring and trouble early warning. Currently, the state testing method of the hoisting apparatus mostly relies on single sensor data acquisition, only focuses on local parameter changes in the running process of the apparatus, and fails to fully combine the original design and inherent properties of the apparatus, so that the state evaluation is not comprehensive. In practical application, the existing method often ignores potential influence of design parameters on the running state of equipment, and judges the equipment only according to real-time running data, so that evaluation deviation is easy to occur. For example, some methods only collect data through vibration sensors to determine whether an abnormality exists in a structure, but do not consider the robustness index of the device design stage, so that hidden faults caused by design defects are difficult to effectively identify. Meanwhile, the traditional evaluation mode lacks a scientific modularized segmentation strategy, the lifting appliance is used as a whole for state judgment, a specific unit where a fault source is located cannot be accurately positioned, and when slight state deviation occurs to equipment, the influence degree of each component is difficult to distinguish, so that the fault checking efficiency is low. The current health assessment system mostly adopts a single-dimension rating standard, and a weight distribution mechanism matched with load characteristics and stress states is not established, so that the final health state assessment result lacks pertinence and scientificity. Under the high-intensity operation scene, the extensive assessment method is difficult to accurately reflect the real operation state of the equipment, and can cause the problems of excessive maintenance or untimely maintenance, thereby not only increasing the operation cost, but also burying potential safety hazards. Therefore, a crane instrument state testing and verifying method capable of integrating design parameters and operation characteristics and realizing fine evaluation is needed to solve the defects existing in the prior art. Disclosure of Invention The invention aims to provide a lifting appliance state testing and verifying method based on PHM, so as to solve the problems in the background technology. To achieve the above object, the present invention provides a lifting appliance status testing and verifying method based on PHM, the method comprising: The method comprises the steps of collecting high-frequency operation characteristics from a lifting appliance technical document, collecting the high-frequency operation characteristics when the lifting appliance starts operation, fusing the design parameters and the high-frequency operation characteristics to determine whether to start a multi-dimensional state evaluation flow, calculating design robustness indexes of the lifting appliance if the multi-dimensional state evaluation flow is started, detecting the structural vibration condition of the lifting appliance, carrying out modularized segmentation on the lifting appliance by combining the structural vibration condition and the design robustness indexes, extracting a plurality of groups of evaluation units, continuously monitoring vibration deviation and stress diffusion speed of each evaluation unit, evaluating contribution degree of each evaluation unit to the state deviation and calculating contribution factors of each evaluation unit, tracking load continuous intervals of each evaluation unit, screening out low contribution units as identification evaluation units, carrying out unit rating on the contribution factors of corresponding units related to the load continuous intervals of each identification evaluation unit, collecting interface stress and tolerance limit load of each identification evaluation unit, deducing the rating of each identification evaluation unit, and integrating the rating and weight of each identification evaluation unit to obtain the health index of the lifting appliance under the current working condition. Preferably, the design parameters comprise a structural material endurance limit, a stress superpo