130 results about "Structural fatigue" patented technology

The invention relates to the technical field of port cranes and mechanical engineering, in particular to a crane structure fatigue life prediction method and system. The invention provides a crane structure fatigue life prediction method. The crane structure fatigue life prediction method comprises the steps that a finite element model of a crane structure is established, and a stress-load mapping relation matrix of crane structure nodes is generated through dimension reduction processing; collecting actual working data of the crane structure; performing data processing on the actual working data, and constructing an actual working load spectrum; based on the stress-load mapping relation matrix and the actual operation load spectrum, generating a stress-time history used for calculating the fatigue life structure node of the crane; and calculating the fatigue damage of the crane structure and predicting the residual fatigue life by combining a stress-life curve and an accumulative damage theory of a crane structure material. According to the method provided by the invention, online, real-time and accurate prediction and visualization of the fatigue life of all structures of the crane are realized, and a basis is provided for formulating an accurate operation and maintenance plan.

The invention belongs to the technical field of fatigue life acceleration test equipment, and particularly relates to an acceleration test device and method for the fatigue life of a rubber corrugated pipe limiting structure, the acceleration test device comprises a base and a heat insulation test box, the bottom end of the heat insulation test box is fixedly connected with the upper surface of the base, and two fixing through holes are formed in the outer wall of one side of the heat insulation test box. The device has multiple environment simulation functions, constructs a composite test environment close to the actual working condition, reflects the influence of different environments on the fatigue life of the limiting structure, improves the representativeness of the fatigue life test result of the rubber corrugated pipe limiting structure, realizes automatic failure judgment through resistance real-time monitoring, does not need manual intervention, and improves the test efficiency. The test convenience is improved, the accuracy of the fatigue life test result of the rubber corrugated pipe limiting structure is further improved, the double-sample synchronous test is realized, the time consumption of the multi-sample test is greatly shortened, and the detection efficiency of the fatigue test is remarkably improved.

The invention relates to a steel structure fatigue crack detection system based on digital twinning, and the system comprises a sensing module which is used for collecting fatigue crack monitoring data of a steel structure in real time; the digital twinning back-end data fusion and management module is used for analyzing and standardizing the fatigue crack monitoring data and constructing a digital twinning model of the steel structure so as to map the entity state of the steel structure and the spatial distribution condition of the fatigue crack; the analysis module is used for detecting the fatigue crack of the steel structure according to the fatigue crack monitoring data, updating a detection result to the digital twinborn model for state synchronization, and performing crack risk early warning; and the visualization module is used for displaying the fatigue crack monitoring data and the detection and early warning result output by the analysis module. Compared with the prior art, real-time detection, trend prediction and multi-level early warning of the fatigue crack of the steel structure are realized through cooperative operation of sensing, fusion, analysis and visualization, and the safety and decision scientificity of the operation and maintenance stage are remarkably improved.

The invention discloses an anti-swing predictive control method for an offshore crane, and belongs to the technical field of ocean engineering equipment control. The problem that in the prior art, due to control lag and an inaccurate model, the load swing restraining effect of an offshore crane is poor is solved. According to the scheme, the method is characterized in that the state of a crane and prediction information of future waves are obtained in real time through a state sensor set and a multi-source environment sensing system; mixing the prediction model to predict a crane system state sequence under different control instructions in a future time domain in a rolling manner; based on the prediction sequence, solving a reference control track aiming at suppressing swing and reducing structural fatigue in upper-layer optimization, and solving and outputting an instant control instruction meeting the constraint of an execution mechanism in lower-layer rapid optimization; meanwhile, system health management is independently executed, and a control mode is dynamically adjusted according to evaluation. The method is mainly used for precise anti-swing control of the offshore crane under the complex sea condition, load swing can be effectively inhibited in advance, and operation precision and equipment safety are improved.

The invention discloses a derrick rotation supporting mechanism overturning monitoring system with a remote monitoring function, and relates to the technical field of remote monitoring, and the derrick rotation supporting mechanism overturning monitoring system comprises the following steps: acquiring vibration acceleration and bolt pre-tightening force data, and performing spectrum analysis to obtain a resonance coefficient so as to judge a resonance state; and an overturning coefficient is calculated according to the bolt pre-tightening force time sequence change, so that overturning risk prediction and early warning are realized, and safe operation of a mechanism is guaranteed. Resonance risks are monitored in real time through vibration spectrum analysis, bolt pre-tightening force attenuation and structural fatigue are effectively prevented, the active protection capacity of a system is improved, overturning risks are dynamically evaluated based on bolt pre-tightening force time sequence changes, the chain loosening effect is accurately recognized, overturning advanced early warning is achieved, and the safety and reliability of a mechanism under the complex working condition are enhanced.

The invention relates to the technical field of fatigue load reduction, in particular to a wind power plant torque and variable pitch cooperative control method with fatigue load reduction as the target. The method comprises the following steps: acquiring real-time and historical operation data of each fan in a wind power plant, and preprocessing the operation data; based on the preprocessed operation data, load characteristic indexes reflecting structural fatigue are extracted, and a load state vector reflecting the current fatigue accumulation trend of the draught fan is constructed; and based on the load state vector, establishing a coupling model of the influence of the generator torque and the variable pitch angle on the rotating speed response and the fatigue load, wherein the coupling model is used for reflecting the influence mechanism of torque adjustment on the low-frequency load and the inhibition effect of variable pitch adjustment on the high-frequency load. According to the method, the load state vector fusing the low-frequency mechanical load and the high-frequency pneumatic excitation is constructed, and the rain flow counting and equivalent damage theory is combined, so that the load component which has the greatest influence on the fatigue life of key parts such as a main shaft, a transmission chain, a tower and a blade root is accurately identified.

The invention relates to the technical field of equipment performance detection, in particular to a construction equipment performance intelligent detection method based on an AI algorithm. The method comprises the following steps: acquiring operation data of each monitoring point of the tower crane, further respectively acquiring characteristics of each monitoring point in a time period, and forming a sample by the characteristics of each monitoring point in the time period; forming a sample set of a first node of an isolated tree of the isolated forest by a preset number of samples containing the samples at the current moment; obtaining the sparse degree and the unstable degree of one feature of one sample; obtaining the abnormal distinguishing degree of one feature, further obtaining the segmentation possibility of one feature of each sample, then segmenting the sample set to obtain two sub-sample sets, and so on, segmenting the sub-sample sets until the depth of the isolated tree reaches a preset depth; and obtaining the abnormal degree of the structural fatigue at the current moment according to each constructed isolated tree. The performance of the tower crane can be effectively monitored.

The invention relates to the technical field of structure fatigue evaluation, in particular to a pipe truss structure fatigue analysis parameter optimization method and system based on deep learning, and the method comprises the following steps: constructing a deep learning proxy model fusing a multi-scale structure diagram encoder, a working condition parameter encoder and a damage dimension curve decoder; training the model by using a high-fidelity training data set; for the target truss structure and the load working condition, predicting a damage dimension relation curve through the model; determining the optimal dimension of a rain flow counting matrix by analyzing the convergence characteristic of the curve; and predicting a multi-working-condition damage value through a model, and screening out a dominant working condition based on a damage contribution percentage. According to the method, the deep learning agent model is used for replacing traditional iterative simulation, rapid optimization of key parameters in fatigue analysis is achieved, the efficiency and accuracy of fatigue evaluation of the large truss structure are remarkably improved, and the generalization ability of the model is improved by fusing the physical effect of a multi-scale structure chart encoder to capture key hotspots.

The application provides a ship structure fatigue strength analysis method and system, which calculates the main engine vibration load and the wave load received by the ship structure based on the ship data, the characteristic data of the ship structure and the global sea state data, then calculates the stress response process under the combined action of the wave load and the main engine vibration load, the spectral density function of the stress response process, each order spectral moment of the stress response process and the zero-crossing rate of the stress response process, then calculates the stress response and the stress response peak of the ship structure under the action of the sinusoidal vibration load, calculates the stress cycle number of the ship structure based on the stress response and in combination with the fatigue life S-N curve, further calculates the fatigue damage under the action of the main engine vibration load, and finally calculates the total coupling fatigue damage under the long-term sea state, and further calculates the fatigue damage of the ship structure under the combined action of the high and low frequency loads, which effectively improves the accuracy and reliability of the ship structure fatigue strength calculation.

This invention relates to the field of structural fatigue life prediction technology, and discloses a method and system for predicting the fatigue life of a hinged coupling, comprising: Step 1, acquiring torque and input shaft angular position data, mapping time to angular position and dividing it equally to obtain angular domain torque; Step 2, constructing a load vector based on the angular domain torque and mapping matrix, and converting it into bending stress and torsional stress; Step 3, determining the equivalent stress, principal stress surface direction angle, and rotation rate; Step 4, calculating and correcting the average equivalent stress per revolution; Step 5, calculating the load concentration factor based on the assembly misalignment angle and angular position, generating a dual-sector weight core, and combining it with the rotation rate to obtain a follow-up amplification factor; Step 6, integrating the corrected stress, weight core, and amplification factor to obtain the cumulative damage per revolution; Step 7, determining the life by accumulating multi-revolution damage, and estimating the remaining life revolutions and time if no failure occurs. This invention achieves accurate prediction of the fatigue life of hinged couplings under complex working conditions.

This invention belongs to the technical field of wind resistance performance assessment for the entire life cycle of high-rise steel structures, and discloses a wind-induced fatigue analysis method and its strength degradation model for centrally supported steel frame structures. The method proposed in this invention can effectively assess wind-induced structural fatigue damage and describe the strength degradation law of materials and structural components, while considering the influence of crosswind response and random variables. The steel strength degradation model established in this invention after wind-induced fatigue damage can be used to correct the material parameters of steel structures after fatigue damage, which is crucial for accurately conducting full-life-cycle reliability analysis of high-performance structures.

The present application relates to a method for predicting fatigue crack propagation rate of a diffusion bonded dissimilar titanium alloy laminate structure, which is based on the mechanical properties of the constituent materials of the dissimilar titanium alloy laminate structure, i.e., the quasi-static tensile properties of the two titanium alloy plies. The method for predicting fatigue crack propagation rate of the diffusion bonded dissimilar titanium alloy laminate structure first establishes the relationship between the fatigue crack propagation rate of the laminate structure and the mechanical properties of the laminate structure, and then establishes the relationship between the mechanical properties of the laminate structure and the mechanical properties of the dissimilar titanium alloy single ply, thereby describing the relationship of the fatigue crack propagation rate of the laminate structure. Compared with the prior art, the method of the present application has the advantages of simple and convenient test, engineering precision, rapid and practical, etc., and effectively reduces the test cost and test time required for crack propagation test of the dissimilar titanium alloy laminate structure processed from different parameters.

The application discloses an anti-seismic gate for a hydropower station gate, which comprises a gate plate, a guide rail structure and an adjusting box. A monitoring vibration sensor is arranged on the gate plate, and the guide rail structure is fixed to the upper end of the gate plate. The adjusting box is fixed to the guide rail structure and moves back and forth on the gate plate through the guide rail structure, and the adjusting box is internally provided with a filler. When the vibration frequency of the gate plate reaches a preset value, the adjusting box is moved to reduce the vibration of the gate plate. The gate of the application can monitor the frequency of the gate plate in real time through the vibration sensor, trigger the movement of the adjusting box to dynamically adjust the mass distribution, accurately avoid the resonance frequency band, and significantly improve the anti-seismic efficiency and avoid structural fatigue damage through the replaceable design of the filler in combination with damping energy consumption and frequency self-adaptation.

The present application belongs to the technical field of mechanical structure health monitoring and life prediction, in particular to an engineering machinery load-bearing structure fatigue life intelligent monitoring method, comprising the following steps: step one, establishing a high-fidelity geometric model; step two, establishing a finite element model; step three, constructing a finite element simulation dataset; step four, constructing a neural network proxy model; step five, obtaining working parameters and loading history; and step six, integrating a visual operation and maintenance platform. The engineering machinery load-bearing structure fatigue life intelligent monitoring method can intelligently deduce the evolution process of fatigue damage based on the working parameters and loading history of the structure, realize dynamic calculation of the remaining life and real-time early warning of the service risk, save computing resources, improve the efficiency of fatigue life evaluation, and solve the problems of dependence on offline simulation, response lag, and discontinuous evaluation in traditional structure life management, thereby effectively improving the intelligent operation and maintenance level of engineering machinery and providing protection for safe and efficient operation.

The invention discloses a wind power generator stator winding fault diagnosis method, and relates to the technical field of wind power generators. The method comprises the following steps: detecting winding end surface roughness, environment humidity and vibration data features which are combined into a first risk-induced feature set, and detecting surface roughness and vibration data features which are combined into a second risk-induced feature set at the joint of a straight line segment and the end; extracting a first correlation factor between historical risk correlation data and a historical coverage area value in the historical risk detection data, obtaining a second correlation factor to which the connection part of the straight line segment and the end part belongs according to the first correlation factor, and obtaining a first risk induction feature set according to the first correlation factor and the first risk induction feature set; and estimating an insulativity reduction risk index and a structural fatigue aggravation risk index to which the end part of the winding belongs currently, and estimating a risk temperature value of the connection part of the straight line segment and the end part after the temperature rise is generated currently according to the second correlation factor and the second risk-induced feature set. The risk diagnosis efficiency can be improved.

The application provides a metal structure crack feature recognition method based on measured strain data, utilizes the strain data collected on the surface of a structure, adopts a machine learning method to establish a quantitative relationship model of the measured strain data and crack features, and further realizes the purpose of directly predicting the crack position and crack length through the strain data. The application realizes real-time detection of the fatigue cracks of the aircraft metal structure, provides support for ensuring the service safety of the aircraft, and compared with the crack detection methods of other sensors, utilizes the strain field singularity principle near the crack tip, uses the strain data collected on the surface of the structure for real-time detection of the cracks, the strain collection method is mature, the data source is highly reliable, the weight of the aircraft is not significantly increased, the structural functional characteristics are not affected, and the final precision error of the crack feature detection is less than 1mm.

The present invention relates to a structural fatigue assessment method, system and device for a tower of a wind turbine, and a storage medium. The assessment method comprises: S1, acquiring shape functions of a plurality of nodes on a target tower, wherein the plurality of nodes are obtained by means of uniformly dividing the target tower in the direction of height thereof; S2, acquiring operating data of a target wind turbine; S3, inputting the operating data and the shape function of each node into a preset wind turbine model, in order to obtain a bending moment time series corresponding to each node on the target tower; S4, on the basis of the bending moment time series of each node, determining a cumulative damage degree of each node; and S5, on the basis of the cumulative damage degree of at least one node, outputting a structural fatigue assessment result for the target tower. The assessment method enables accurate estimation of the structural fatigue condition of towers without relying on external sensors.

The invention discloses a ship gas collection platform capable of compensating degree of freedom, which is characterized in that a conventional connection mode of direct welding between a gas collection platform and a main deck and between the gas collection platform and a dome deck is changed through a magnetic buffer mechanism, and the situations of structural fatigue and welding corrosion of a welding part between the lower end of the gas collection platform and a ship body in a long-term use process are avoided; the degree of freedom of the gas collection platform in the ship operation process is compensated through the magnetic suction buffer mechanism, the stand column can move in the stand column cylinder, and the stand column can swing through the ball connection mode between the stand column cylinder and the joint base so as to counteract shaking of the gas collection platform due to the fact that stormy waves act on the ship body and the gas collection platform; and adverse effects of stormy waves on use of the gas collection platform are avoided.

The invention discloses a method for evaluating the fatigue performance of a service period composite structure driven by mass FBG monitoring data, and relates to the technical field of structural health monitoring and fatigue life prediction. An evaluation framework of deep fusion of data and a physical model is constructed, and key time-varying parameters of a fatigue damage evolution model are updated in real time to enable the fatigue damage evolution model to continuously approach a real service state of a structure, so that accurate evaluation of fatigue damage accumulation and dynamic and reliable prediction of residual life are realized. According to the method for evaluating the fatigue performance of the service period composite structure driven by the mass FBG monitoring data, the monitoring data accumulated in the long-term service process is directly introduced into fatigue performance evaluation, so that the monitoring data is upgraded to fatigue performance evaluation and life prediction from traditional state recording and threshold value alarming; and real and online inversion of the fatigue performance of the service structure is realized.

This invention relates to the field of intelligent sensor technology, specifically to a laser diameter measuring sensor and system for wire rope flaw detection, including a structural fatigue early warning module, a cross-sectional profile de-biasing module, a surface defect early warning module, a three-dimensional coordinate construction module, and a structural fatigue early warning module. In this invention, multiple sets of photosensitive arrays are arranged around the wire rope to extract one-dimensional coordinates of the shadow boundary. The coordinates are then mapped by translation using the geometric center point of a polygon to obtain the true external profile of the de-biased cross-section, thereby evaluating radial distance differences for early warning of minor surface defects. Furthermore, by using extreme feature points combined with longitudinal running speed and sampling timestamps to construct a three-dimensional coordinate set of peak vertices, and dynamically calculating the twist span deviation, this invention eliminates measurement errors caused by lateral swaying, accurately captures minor surface anomalies, and comprehensively monitors the deep structural untwisting fatigue of the wire rope, improving the accuracy of wire rope flaw detection and the timeliness of safety early warning.

The utility model relates to the technical field of water conservancy devices, in particular to an anti-floating catchment weir device which comprises a bottom plate, a plurality of anti-floating holes are evenly formed in the middle of the bottom plate at intervals, the anti-floating holes are used for reducing the acting force of buoyancy of water on the bottom plate, the two ends of one end face of the bottom plate are fixedly connected with U-shaped weir plates, and the weir plates are arranged on the bottom plate. Baffles are arranged on the two sides of the bottom plate, sliding plates are slidably connected to the two ends of the bottom plate, the ends, away from the bottom plate, of the sliding plates are rotationally connected with the baffles, and one ends of the baffles are rotationally connected with fixing blocks. Compared with the prior art, the problems that in the prior art, when water enters, due to the buoyancy effect, the connecting position of the structure is prone to loosening, falling off or deforming, the length of the structure blocking water flow cannot be adjusted according to the water flow pressure, stress is uneven, structural fatigue damage is accelerated, and even structural damage is caused are solved.

This invention relates to the field of fatigue loss early warning technology for reinforced concrete structures, and discloses a fatigue damage early warning method, device, electronic equipment, storage medium, and program product for reinforced concrete structures. The invention acquires magnetic field data and calculates magnetic field changes and gradients by scanning sampling points of the component under test along a preset path. Combined with preset abrupt change conditions, it accurately locates dangerous areas, solving the problems of traditional methods in characterizing microscopic material damage and inability to target risks. Subsequently, it focuses on collecting magnetic field characteristic data in dangerous areas, judges structural fatigue damage based on its evolution law, and issues early warnings. This effectively avoids the shortcomings of traditional measurement methods, such as limited applicability, insufficient accuracy, and cumbersome operation, forming an efficient closed loop of location, monitoring, and early warning. It compensates for the shortcomings of existing technologies in efficiently and accurately completing assessment and early warning, significantly improving the timeliness and reliability of structural fatigue damage early warning.

A structural fatigue life prediction method considering strength degradation effect, wherein the method includes: obtaining strain-time data of the structure under at least one working condition; converting the strain-time data into a stress spectrum; processing the stress spectrum by using a nonlinear cumulative damage model considering strength degradation effect to obtain the residual damage of the structure; calculating the fatigue life of the structure according to the residual damage. The invention modifies the nonlinear cumulative damage model by introducing stress ratio and strength degradation coefficient. The function is mainly expressed in exponential form, which can better reflect the degradation performance of the material. The model form is simple and it can be well applied to practical engineering. This model can be applied to the prediction of fatigue life under multi-level load, which greatly improves the prediction accuracy of structural fatigue life.

The invention discloses a Bayesian probability fatigue strength evaluation method for a structural member with defects, and relates to the technical field of fatigue strength prediction of aerospace metal structural members. The method comprises the following steps: firstly, drawing a fatigue limit curve based on test data of a defective material sample, embedding a physical rule of an El Hadad curve through a synthetic data set, and establishing physical priori knowledge of a defect size and a fatigue strength behavior; training model parameters by using test data of the structural member, constructing a Bernoulli likelihood function, and matching an actual failure tag of the structural member; and finally, fusing the prior distribution and the likelihood function through the Bayesian theorem to obtain probability distribution after parameter updating, and outputting a predicted failure probability expected value and uncertainty. According to the method, material sample data containing defects are fused as physical prior based on the Bayesian theory, and the probability fatigue strength is evaluated through experimental data of a small amount of structural parts.

The utility model belongs to the technical field of vehicle testing, and particularly relates to a vehicle body structure fatigue testing device which comprises a vehicle body shell, the vehicle body shell is fixedly connected with a fixing plate, the fixing plate is provided with a connecting block, the connecting block is fixedly connected with an internal assembly, the fixing plate is provided with a testing sensing device, and the testing sensing device is connected with the internal assembly. The test sensing device comprises a rotating shaft. According to the vehicle body structure fatigue testing device, the fatigue condition of the vehicle body structure is analyzed and the fatigue life of the vehicle body structure is evaluated through the test sensing device and the control system according to information such as the triggered times and time intervals of the sensor, and tiny deformation of the vehicle body structure in the fatigue testing process can be accurately converted into detectable signals. Through cooperative work of the extrusion plate, the folding plate, the rotating plate and other parts, deformation of the vehicle body is transmitted to the induction block, when the induction block touches the inductor, a signal can be sent out in time, and an accurate basis is provided for evaluating the fatigue condition of the vehicle body structure.

The invention provides a near-fault seismic motion vector type intensity index construction method, and belongs to the technical field of structural toughness anti-seismic analysis, and the method comprises the steps: calculating a value of an ideal speed pulse signal acceleration response spectrum at a structural basic period under a 5% damping ratio, and taking the value as a near-fault seismic motion speed pulse spectrum characteristic representation parameter; calculating the normalized total speed pulse duration, and representing the influence of the multi-speed pulse generation time process on the low-cycle fatigue damage of the structure; the two parameters are combined into a vector, namely the near-fault multi-speed pulse record vector type intensity index. According to the method, the structure dynamic response is directly associated with the velocity pulse frequency spectrum characteristic, meanwhile, the pulse generation time process parameters are introduced for the first time, the structure fatigue damage is associated with the velocity pulse generation process in the seismic oscillation, the near-fault multi-velocity pulse seismic oscillation intensity can be effectively represented, and the accuracy of the seismic oscillation intensity is improved. And the influence on the seismic response of the structure can be measured more accurately.

The utility model relates to the technical field of air conditioner air pipe installation, and discloses a heat insulation support of an air conditioner air pipe, which comprises two pipe bodies, buffer mechanisms are arranged at the tops of the two pipe bodies, supporting mechanisms are arranged at the tops of the pipe bodies, and the buffer mechanisms comprise two supporting plates. The outer portions of the two supporting plates are fixedly connected to the adjacent sides of the outer portions of the two pipe bodies correspondingly, supporting blocks are fixedly connected to the bottoms of the two supporting plates, rotating columns are rotationally connected to the interiors of the supporting blocks, and rotating plates are fixedly connected to the outer portions of the rotating columns. By means of the telescopic reset capacity of the buffer spring, vibration energy is absorbed, fatigue damage of the structure is reduced, the service life of equipment is prolonged, the adaptability and reliability of the support are further enhanced through the design of the connecting plate and the ejector block, the pipe body can be supported, stable operation can be guaranteed, and meanwhile the safety capacity is improved.

The present application relates to the technical field of structural fatigue life prediction, in particular to a multistage variable amplitude loading modulus double drive fatigue life prediction method, which comprises: carrying out multistage variable amplitude loading uniaxial fatigue test of metal structure to obtain sample data; constructing a physical model to extract a physical feature vector, which takes intrinsic damage dissipation as the core and introduces a nonlinear representation term to capture the load sequence effect; constructing a data-driven model containing NGMM data enhancement, semantic and time sequence coding and Mamba-Transformer collaborative architecture to extract data feature vectors; through full connection layer dimension unification, attention mechanism dynamic fusion and double item loss optimization, outputting fusion prediction value to predict the fatigue life of metal structure. The present application takes into account the physical interpretability and data nonlinear description ability, solves the problem of poor prediction accuracy of existing technology in the aspect of structural multistage variable amplitude loading fatigue life prediction, has strong cross material and working condition adaptability, and significantly improves the prediction accuracy and stability.

The application relates to the technical field of material fatigue test, in particular to a structure fatigue testing machine. The structure fatigue testing machine comprises an operation table, the operation table is provided with symmetrically-distributed fixing frames, the fixing frames are slidably connected with symmetrically-distributed guide blocks, the guide blocks are rotatably connected with rotating shafts, the rotating shafts are fixedly connected with connecting plates, the connecting plates symmetrically and close to different fixing frames are fixedly connected with fixing shafts, the fixing shafts are fixedly connected with symmetrically-distributed T-shaped plates, the T-shaped plates are provided with equidistantly-distributed sliding grooves, the symmetrically and close sliding grooves of different fixing frames are jointly slidably connected with connecting pieces, and the connecting pieces are rotatably connected with symmetrically-distributed rollers. The position of the connecting piece on the adjacent sliding groove is adjusted, the bending degree of the two sides of the steel plate is continuously increased in the steel plate bending process, the connecting piece drives the roller to move to support and fix the multiple points of the steel plate, the stress of the two sides of the steel plate is uniform, and the accuracy of the stress change data of the middle part of the steel plate is ensured.

This invention relates to the field of pressure reducing valve testing technology and discloses a pressure testing system for pressure reducing valves. The system's environmental parameter monitoring module collects real-time data on temperature, humidity, and vibration intensity of the environment in which the pressure reducing valve is located and transmits this data to the test execution module. Based on the received environmental data, the test execution module initiates a pressure loading process, applying a dynamically changing pressure load sequence through a hydraulic control device, while simultaneously recording the deformation response data of the pressure reducing valve. After receiving the deformation response data, the result analysis module performs multi-dimensional failure mode identification calculations, generating a test report containing leakage risk assessment parameters and structural fatigue coefficients. This report is fed back to the test execution module for real-time adjustment of the pressure load sequence application strategy. Through the coordinated operation of its modules, this system achieves dynamic monitoring and evaluation of the pressure performance of the pressure reducing valve, improving the accuracy and relevance of the test.