CN-122020476-A - Cableway safety-oriented rope clip operation risk analysis system and method

CN122020476ACN 122020476 ACN122020476 ACN 122020476ACN-122020476-A

Abstract

The invention relates to the technical field of cableway safety, and discloses a cableway safety-oriented rope clip operation risk analysis system and a cableway safety-oriented rope clip operation risk analysis method, wherein the cableway safety-oriented rope clip operation risk analysis system comprises the steps of performing abnormality judgment based on first abrasion data and second abrasion data corresponding to texture characteristics and dynamic track characteristics; the intelligent monitoring system and the intelligent monitoring method for the safety of the rope clip are characterized in that a multi-mode data fusion technology is adopted for comprehensively capturing external deformation and internal stress change of equipment, collaborative analysis of image features and physical signals can effectively identify potential risks and avoid limitation of a single data source, in addition, a self-adaptive standardized parameter mechanism is introduced, a standard value is dynamically adjusted, robustness is enhanced, false alarm is reduced, interpretable risk score and rule are built based on physical rules and statistical features, transparency and traceability of diagnosis logic are ensured, quick response and long-term early warning under emergency conditions are considered through setting of different risk grades, and safety and operation and maintenance efficiency of a cableway are improved.

Inventors

LIU XIAOCHENG
Chu Jianyue
FENG XIAOYAN

Assignees

北京中索国游索道工程技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. A cableway safety oriented rope clip operation risk analysis method, characterized in that the method comprises: s101, acquiring an original image sequence and structural parameters of a rope clip, respectively carrying out optimization processing on the original image sequence and the structural parameters to generate a segmented image and a characteristic data set, and aligning the segmented image with the characteristic data set; s102, analyzing the aligned segmented image, extracting texture features and dynamic track features from the aligned segmented image, and performing abnormality judgment based on first abrasion data and second abrasion data corresponding to the texture features and the dynamic track features; s103, extracting vibration signal characteristics, acoustic emission signal characteristics and temperature sequences from the aligned characteristic data sets, respectively calculating vibration kurtosis, acoustic emission frequency and temperature difference, and carrying out abnormality judgment based on the vibration kurtosis, the acoustic emission frequency and the temperature difference; And S104, normalizing the texture variance, the closure delay frame number, the acoustic emission frequency and the temperature sequence, weighting the normalized three types of data, calculating the comprehensive risk score, judging the risk level, and continuously adjusting the normalization parameters.
2. The cableway safety-oriented rope clip operation risk analysis method according to claim 1, wherein the performing anomaly determination based on the first wear data and the second wear data corresponding to the texture feature and the dynamic track feature comprises: Converting the clamping block area of the rope clip in the aligned segmented image into texture features, calculating texture variance of the texture features, extracting a gray level co-occurrence matrix from the texture features, and obtaining contrast and correlation values; the abnormality judgment rule is that if texture variance is greater than texture variance threshold, abrasion risk marking is carried out; If the contrast is less than n and the correlation value fluctuates, judging that the surface fatigue is abnormal; Wherein the variance threshold is the historical mean plus twice the standard deviation.
3. The cableway safety-oriented rope clip operation risk analysis method according to claim 2, wherein the abnormality determination is performed based on the first wear data and the second wear data corresponding to the texture feature and the dynamic track feature, and further comprising: For two continuous frame segmentation images, optical flow jitter detection is carried out, and the angular velocity standard deviation of the clamping block area is calculated; Identifying a starting frame and a closing frame of the closing of the clamping blocks, counting a closing delay frame number, introducing mass center coordinates of the left clamping block and the right clamping block, and calculating corresponding Euclidean distance and phase difference; The abnormality judgment rule is that if the angular speed standard deviation is more than m, the machine is regarded as machine clamping; if the closed delay frame number is greater than the average value of the closed delay frame numbers plus twice the standard deviation of the closed delay frame numbers, triggering closed delay early warning; If the Euclidean distance > a or the phase difference > b, the synchronization failure of the left and right clamping blocks is judged.
4. The cableway safety-oriented rope clip operation risk analysis method according to claim 1, wherein the abnormality determination based on the vibration kurtosis, the acoustic emission frequency, and the temperature difference comprises: Extracting triaxial vibration acceleration signals from the aligned characteristic data set, performing Fourier transform to obtain a frequency spectrum, and calculating the frequency domain energy ratio of a main frequency band; Meanwhile, the vibration kurtosis and the waveform distortion rate are calculated, and the formulas are respectively as follows: wherein: for the nth vibration acceleration sample value, As the mean value of the vibration acceleration, Is the standard deviation of the vibration acceleration; Wherein A k is FFT amplitude of the kth harmonic, and A 1 is amplitude of the main frequency; Acquiring health mode data of the rope clip, and performing cross-correlation analysis on the health mode data and the current vibration mode to obtain a cross-correlation coefficient; The abnormality judgment rule is that if the frequency domain energy ratio of the main frequency band is less than-10% of the historical average value, the rigidity is regarded as degradation; if the vibration kurtosis or the waveform distortion rate is larger than the corresponding threshold value, indicating that impact vibration occurs; if the cross-correlation coefficient is less than the cross-correlation threshold, and judging that the structure is abnormal.
5. The cableway-safety-oriented rope clip operational risk analysis method according to claim 1, characterized in that the logic for normalizing texture variance, closing delay frame number, acoustic emission frequency and temperature sequence is as follows: Respectively adopting corresponding standardization parameters for standardization of the texture variance and the closed delay frame number; for the acoustic emission frequency and the temperature sequence, the historical maximum acoustic emission frequency and the temperature safety threshold are respectively adopted as standardized parameters.
6. The cableway security-oriented rope clip operation risk analysis method according to claim 1, wherein the calculation formula for calculating the comprehensive risk score is as follows: wherein: , , the sum of texture variance and number of closed delay frames, the acoustic emission frequency and the weight of the temperature sequence, For sub-weights between texture variance and number of closed latency frames, For normalized texture variance and closure delay frame number, For the acoustic emission frequency, For a historic maximum acoustic emission frequency, As the current temperature difference is the one, Is a temperature safety threshold.
7. The cableway security oriented rope clip operational risk analysis method according to claim 6, characterized in that said continuously adjusting standardized parameters comprises: Calculating the historical mean and standard deviation of the texture variance and the closed delay frame number at each interval of time T, and updating the standardized parameters corresponding to the texture variance and the closed delay frame number; The updating formulas of the historical mean value and the standard deviation are respectively as follows: wherein: Is the nth history sample value.
8. A cableway security oriented rope clip operational risk analysis system, characterized in that it is implemented based on the cableway security oriented rope clip operational risk analysis method according to any of claims 1 to 7, the system comprising: The data acquisition module acquires an original image sequence and structural parameters of the rope clip, optimizes the original image sequence and the structural parameters respectively, generates a segmented image and a characteristic data set, and aligns the segmented image and the characteristic data set; The image feature module is used for analyzing the aligned segmented image, extracting texture features and dynamic track features from the aligned segmented image, and performing abnormality judgment based on first abrasion data and second abrasion data corresponding to the texture features and the dynamic track features; The data characteristic module extracts vibration signal characteristics, acoustic emission signal characteristics and temperature sequences from the aligned characteristic data set, calculates vibration kurtosis, acoustic emission frequency and temperature difference respectively, and carries out abnormality judgment based on the vibration kurtosis, the acoustic emission frequency and the temperature difference; The risk analysis module is used for standardizing the texture variance, the closing delay frame number, the acoustic emission frequency and the temperature sequence, weighting the standardized three types of data, calculating the comprehensive risk score, judging the risk level and continuously adjusting the standardized parameters.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the cableway security-oriented grip running risk analysis method according to claims 1-7 when executing the computer program.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed, implements the cableway security oriented rope clip operation risk analysis method according to claims 1-7.

Description

Cableway safety-oriented rope clip operation risk analysis system and method Technical Field The invention relates to the technical field of cableway safety, in particular to a cableway safety-oriented rope clip operation risk analysis system and a cableway safety-oriented rope clip operation risk analysis method. Background The rope clip for cableway safety is an important safety device for a cableway system, and has the main functions of ensuring the safety and stability in the transportation process of the cableway, and preventing the cableway from loosening or slipping in the operation process by fastening and supporting a cableway cable, so that the normal operation of the cableway and the safety of passengers are ensured. However, the traditional rope clip operation risk analysis method has four main core defects that firstly, a perception blind area is caused by multi-source data fracture, if the perception blind area is only dependent on images or vibration signals, the external deformation and internal stress related characteristics cannot be synchronously captured, hidden risks such as internal fatigue or abnormal clamping blocks are easy to miss, secondly, fixed threshold judgment is easy to lose effectiveness, a static threshold cannot adapt to the slow change of equipment states along with time, false alarm or false alarm is easy to occur, thirdly, a deep learning model depends on a large amount of marked data and has poor interpretation, the black box characteristics are difficult to meet the requirements of industrial scenes on diagnostic logic transparency, fourthly, single risk assessment and response are lagged, and binary judgment or single threshold lacks a dynamic grading mechanism. The problems described above result in incomplete risk coverage, high false positive rate and opaque decisions in conventional methods, and it is difficult to meet the requirements of cableway safety for high reliability, interpretability and hierarchical response. Disclosure of Invention In order to overcome the defects in the prior art, the embodiment of the invention provides a cableway safety-oriented rope clip operation risk analysis system and a cableway safety-oriented rope clip operation risk analysis method. In order to achieve the above purpose, the present invention provides the following technical solutions: In a first aspect, a cableway safety-oriented rope clip operation risk analysis method is provided, the method comprising: s101, acquiring an original image sequence and structural parameters of a rope clip, respectively carrying out optimization processing on the original image sequence and the structural parameters to generate a segmented image and a characteristic data set, and aligning the segmented image with the characteristic data set; s102, analyzing the aligned segmented image, extracting texture features and dynamic track features from the aligned segmented image, and performing abnormality judgment based on first abrasion data and second abrasion data corresponding to the texture features and the dynamic track features; s103, extracting vibration signal characteristics, acoustic emission signal characteristics and temperature sequences from the aligned characteristic data sets, respectively calculating vibration kurtosis, acoustic emission frequency and temperature difference, and carrying out abnormality judgment based on the vibration kurtosis, the acoustic emission frequency and the temperature difference; And S104, normalizing the texture variance, the closure delay frame number, the acoustic emission frequency and the temperature sequence, weighting the normalized three types of data, calculating the comprehensive risk score, judging the risk level, and continuously adjusting the normalization parameters. Further, the performing anomaly determination based on the first wear data and the second wear data corresponding to the texture feature and the dynamic track feature includes: Converting the clamping block area of the rope clip in the aligned segmented image into texture features, calculating texture variance of the texture features, extracting a gray level co-occurrence matrix from the texture features, and obtaining contrast and correlation values; the abnormality judgment rule is that if texture variance is greater than texture variance threshold, abrasion risk marking is carried out; If the contrast is less than n and the correlation value fluctuates, judging that the surface fatigue is abnormal; Wherein the variance threshold is the historical mean plus twice the standard deviation. Further, the anomaly determination is performed based on the first wear data and the second wear data corresponding to the texture feature and the dynamic track feature, and the anomaly determination method further includes: For two continuous frame segmentation images, optical flow jitter detection is carried out, and the angular velocity standard deviation of the clamping block area is cal