A method and system for detecting the operation safety of amusement equipment based on image signal recognition

Abstract

The present invention discloses a method and system for detecting the operation safety of amusement equipment based on image signal recognition, comprising the following steps: acquiring the image signal data information of the amusement equipment and performing preprocessing of image signal enhancement; performing image segmentation processing on the result of the preprocessing of image signal enhancement for the amusement equipment; performing amusement equipment feature recognition and extraction processing on the result of the local image segmentation processing of the amusement equipment based on the amusement equipment operation state model; generating a corresponding amusement equipment feature map based on the result of the amusement equipment feature recognition and extraction processing and the amusement equipment operation state model, and performing amusement equipment component classification and comparison processing; performing amusement equipment operation state determination processing on the result of the amusement equipment component classification processing based on the amusement equipment operation state model; realizing the enhancement and segmentation processing of the amusement equipment image for the amusement equipment image signal, and performing feature recognition and extraction processing and amusement equipment component classification and comparison processing, so as to accurately judge the operation state of the amusement equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of amusement equipment, and in particular to a method and system for detecting the safe operation of amusement equipment based on image signal recognition. Background Art

[0002] At present, the safety operation state of amusement equipment is mostly judged by collecting voltage signals and current signals of the amusement equipment, collecting image signals of the amusement equipment to identify and extract the characteristics of safety belts to monitor in real time whether tourists have fastened their safety belts, and judging the safety operation state of the amusement equipment according to the collected voltage signals, current signals and image signals of the amusement equipment. This method of judging the safe operation of amusement equipment through voltage signals, current signals and image signals cannot clearly understand the operation conditions of amusement equipment and its components at each time period, and does not perform real-time full-process monitoring of the speed and acceleration of the amusement equipment in different regions, so it cannot accurately judge the safe operation of the amusement equipment. Summary of the Invention

[0003] In order to overcome the deficiencies of the prior art, the present invention provides a method and system for detecting the safe operation of amusement equipment based on image signal recognition, which realizes the enhancement and segmentation processing of the amusement equipment image signal, and performs feature recognition extraction processing and classification and comparison processing of amusement equipment components, so as to accurately judge the operation state of the amusement equipment.

[0004] In order to achieve the above invention purpose, the present invention adopts the following technical solutions:

[0005] The first aspect of the present application provides a method for detecting the safe operation of amusement equipment based on image signal recognition, including the following steps:

[0006] S101. Obtain the image signal data information of the amusement equipment and perform preprocessing of image signal enhancement;

[0007] S102. Perform segmentation processing on the preprocessed result of image signal enhancement for the amusement equipment image to remove the background area and obtain the local segmentation processing result of the amusement equipment image;

[0008] S103. Perform feature recognition and extraction processing on the local segmentation processing result of the amusement equipment image based on the amusement equipment operation state model, and generate the corresponding amusement equipment feature map;

[0009] S104. Perform classification and comparison processing on the amusement equipment components based on the amusement equipment operation state model for the feature recognition and extraction processing result of the amusement equipment and the generated corresponding amusement equipment feature map;

[0010] S105 , performing a process of determining the operating state of the amusement equipment on the amusement equipment component classification process result based on the amusement equipment operating state model.

[0011] Furthermore, the image signal data information of amusement equipment includes carousel type amusement equipment, rotating aircraft type amusement equipment, rail train type amusement equipment, trampoline swing type amusement equipment, bumper car type amusement equipment, overhead tour bus type amusement equipment, and pirate ship type amusement equipment.

[0012] Furthermore, obtaining the image signal data information of the amusement equipment and performing image signal enhancement preprocessing includes the following steps:

[0013] Perform image filtering processing on the image signals of amusement equipment;

[0014] Performing image histogram equalization processing on the amusement equipment image signal processed by image filtering;

[0015] Divide the amusement equipment image signal processed by image histogram equalization into several areas, and calculate the average brightness of the areas;

[0016] The amusement equipment image signal processed by calculating the regional brightness average value is subjected to image normalization processing.

[0017] Furthermore, performing amusement equipment image segmentation processing on the image signal enhancement preprocessing result to remove the background area and obtain a local segmentation processing result of the amusement equipment image includes the following steps:

[0018] Based on the gray value edge detection, the image signal is enhanced and pre-processed to identify the background area and the amusement equipment area;

[0019] Perform image segmentation on the background area and the amusement equipment area to remove the background area;

[0020] Perform local segmentation of amusement equipment images in the amusement equipment area.

[0021] Furthermore, the construction of the amusement equipment operation status model includes the following steps:

[0022] Obtaining historical data information on the normal operation status and abnormal operation status of amusement equipment, and performing image preprocessing of the amusement equipment;

[0023] Performing feature recognition and extraction processing on the amusement equipment image preprocessing results;

[0024] Performing classification and comparison processing of amusement equipment components based on the results of amusement equipment feature recognition and extraction processing;

[0025] Perform model training processing on the initial model of the amusement equipment based on the classification comparison processing results of the amusement equipment components;

[0026] If the model training result is the same as the training sample result, the model training is completed; if the model training result is different from the training sample result, re-perform model training.

[0027] Furthermore, perform amusement equipment feature recognition and extraction processing on the local segmentation processing result of the amusement equipment image based on the amusement equipment operation state model, and generate the corresponding amusement equipment feature map, including the following steps:

[0028] Perform amusement equipment feature recognition processing on the local segmentation processing result of the amusement equipment image;

[0029] Perform amusement equipment component feature marking processing on the amusement equipment feature recognition processing result;

[0030] Perform line segment area speed calculation processing and amplitude calculation processing on the amusement equipment component feature marking processing result;

[0031] Generate a speed map and an acceleration map based on the line segment area speed calculation processing result, and generate an amplitude map based on the amplitude calculation processing result.

[0032] Furthermore, perform amusement equipment component classification comparison processing on the amusement equipment feature recognition and extraction processing result and the generated corresponding amusement equipment feature map based on the amusement equipment operation state model, including the following steps:

[0033] Perform amusement equipment component classification processing based on the amusement equipment feature recognition processing result to obtain the amusement equipment moving component type and the amusement equipment stationary component type;

[0034] Construct the speed and acceleration constraint conditions for the amusement equipment moving component type, and perform comparison processing with the speed map and the acceleration map;

[0035] Construct the vibration amplitude constraint condition for the amusement equipment stationary component type, and perform comparison processing with the amplitude map.

[0036] Furthermore, perform amusement equipment operation state determination processing on the amusement equipment component classification comparison processing result based on the amusement equipment operation state model, including the following steps:

[0037] If there are values greater than or equal to the corresponding set speed threshold and acceleration threshold of the moving component in the speed map and the acceleration map of the amusement equipment moving component type, determine that the operation state of the amusement equipment moving component type is abnormal; otherwise, determine that the operation state of the amusement equipment moving component type is normal.

[0038] If the amplitude spectrum of the fixed components of the amusement equipment shows an amplitude greater than or equal to the corresponding set amplitude threshold for the fixed components, it is determined that the operating state of the fixed components of the amusement equipment is abnormal; otherwise, it is determined that the operating state of the fixed components of the amusement equipment is normal.

[0039] The second aspect of the present application provides a safety system for detecting the operation of amusement equipment based on image signal recognition, including:

[0040] A data acquisition unit for acquiring image signal data information of the amusement equipment;

[0041] A model construction unit for constructing an operating state model of the amusement equipment;

[0042] A first data processing unit for performing preprocessing of image signal enhancement on the image signal data information of the amusement equipment;

[0043] A second data processing unit for performing image segmentation processing on the result of the preprocessing of image signal enhancement to remove the background area and obtain a local segmentation processing result of the amusement equipment image;

[0044] A third data processing unit for performing feature recognition and extraction processing on the local segmentation processing result of the amusement equipment image based on the operating state model of the amusement equipment, and generating a corresponding feature spectrum of the amusement equipment;

[0045] A fourth data processing unit for performing component classification and comparison processing on the result of the feature recognition and extraction processing of the amusement equipment and the generated corresponding feature spectrum of the amusement equipment based on the operating state model of the amusement equipment;

[0046] A fifth data processing unit for performing operating state determination processing on the result of the component classification processing of the amusement equipment based on the operating state model of the amusement equipment.

[0047] Further, the first data processing unit performing preprocessing of image signal enhancement on the image signal data information of the amusement equipment includes:

[0048] Performing image filtering processing on the image signal of the amusement equipment;

[0049] Performing image histogram equalization processing on the image signal of the amusement equipment after image filtering processing;

[0050] Dividing the image signal of the amusement equipment after image histogram equalization processing into several regions, and performing regional brightness average value calculation processing;

[0051] Performing image normalization processing on the image signal of the amusement equipment after regional brightness average value calculation processing.

[0052] Further, the second data processing unit performs amusement device image segmentation processing on the preprocessed result of the image signal enhancement to remove the background area and obtain the local segmentation processing result of the amusement device image, including:

[0053] Based on the edge detection of the gray value, identify and process the background area and the amusement device area in the preprocessed result of the image signal enhancement;

[0054] Perform image segmentation processing on the background area and the amusement device area to remove the background area;

[0055] Perform local segmentation processing on the amusement device area of the amusement device image.

[0056] Further, the model construction unit is used to construct an amusement device operation state model. The construction of the amusement device operation state model includes:

[0057] Obtain the historical data information of the normal operation state of the amusement device and the historical data information of the abnormal operation state of the amusement device, and perform preprocessing on the amusement device image;

[0058] Perform amusement device feature recognition and extraction processing on the preprocessed result of the amusement device image;

[0059] Perform amusement device component classification and comparison processing based on the result of the amusement device feature recognition and extraction processing;

[0060] Perform model training processing on the initial model of the amusement device based on the result of the amusement device component classification and comparison processing;

[0061] If the model training result is the same as the training sample result, the model training is completed; if the model training result is different from the training sample result, the model training is restarted.

[0062] Further, the third data processing unit performs amusement device feature recognition and extraction processing on the local segmentation processing result of the amusement device image based on the amusement device operation state model, and generates the corresponding amusement device feature map, including:

[0063] Perform amusement device feature recognition processing on the local segmentation processing result of the amusement device image;

[0064] Perform amusement device component feature marking processing on the result of the amusement device feature recognition processing;

[0065] Perform line segment area speed calculation processing and amplitude calculation processing on the result of the amusement device component feature marking processing;

[0066] Generate a speed map and an acceleration map based on the result of the line segment area speed calculation processing, and generate an amplitude map based on the result of the amplitude calculation processing.

[0067] Further, the fourth data processing unit performs classification and comparison processing on the amusement device component feature recognition extraction processing result and the generated corresponding amusement device feature map based on the amusement device operation state model, including:

[0068] Performing classification processing on the amusement device components based on the amusement device feature recognition processing result to obtain the types of movable components and fixed components of the amusement device;

[0069] Constructing the speed and acceleration constraint conditions for the types of movable components of the amusement device and comparing them with the speed map and acceleration map;

[0070] Constructing the vibration amplitude constraint conditions for the types of fixed components of the amusement device and comparing them with the amplitude map.

[0071] Further, the fifth data processing unit performs amusement device operation state determination processing on the amusement device component classification processing result based on the amusement device operation state model, including:

[0072] If there are speed maps and acceleration maps of the types of movable components of the amusement device that are greater than or equal to the corresponding set speed threshold and acceleration threshold of the movable components, it is determined that the operation state of the types of movable components of the amusement device is abnormal; otherwise, it is determined that the operation state of the types of movable components of the amusement device is normal.

[0073] If there is an amplitude map of the types of fixed components of the amusement device that is greater than or equal to the corresponding set amplitude threshold of the fixed components, it is determined that the operation state of the types of fixed components of the amusement device is abnormal; otherwise, it is determined that the operation state of the types of fixed components of the amusement device is normal.

[0074] Advantages of this application: Compared with the prior art, which extracts the seat belt features by collecting the image signals of the amusement device to identify whether the tourists have fastened their seat belts and combines the voltage signals and current signals of the amusement device to judge the operation of the amusement device, this application realizes the amusement device image enhancement segmentation processing on the amusement device image signals, obtains the amusement device component feature image signals with clear contours, and performs feature recognition extraction processing to generate the corresponding amusement device feature map and amusement device component classification comparison processing, so as to accurately judge the operation state of the amusement device.

[0075] It realizes the line segment area speed calculation processing and amplitude calculation processing on the amusement device component feature marking processing result, and generates the corresponding amusement device feature map. Based on the amusement device operation state model, the amusement device feature recognition extraction processing result and the generated corresponding amusement device feature map are used to perform amusement device component classification comparison processing, and the operation of the amusement device in each line segment area is monitored in real time, thus greatly improving the accuracy of judging the operation state of the amusement device.

[0076] The image filtering process is implemented on the image signal of the amusement equipment to improve the image quality of the amusement equipment. The image histogram equalization process is performed on the image signal of the amusement equipment to obtain an amusement equipment image signal with uniform gray value distribution, so that the amusement equipment image signal has more data information. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0078] Figure 1 This is a schematic diagram of the steps of a method for detecting the safe operation of an amusement device based on image signal recognition according to the present invention:

[0079] Figure 2 It is a structural diagram of a system for detecting the operation safety of an amusement device based on image signal recognition according to the present invention. DETAILED DESCRIPTION

[0080] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0081] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0082] Embodiment 1:

[0083] A method for detecting the safe operation of an amusement device based on image signal recognition includes the following steps:

[0084] S101, obtaining image signal data information of an amusement device and performing image signal enhancement preprocessing;

[0085] Obtain the image signal data information of amusement equipment based on time series, perform preprocessing of image signal enhancement on the image signal data information of amusement equipment, and obtain the result of preprocessing of image signal enhancement. The image signal data information of amusement equipment includes carousel amusement equipment, rotating airplane amusement equipment, track train amusement equipment, trampoline swing amusement equipment, bumper car amusement equipment, aerial tramway amusement equipment, pirate ship amusement equipment.

[0086] Obtain the image signal data information of amusement equipment and perform preprocessing of image signal enhancement, including the following steps:

[0087] Perform image filtering processing on the image signal of amusement equipment;

[0088] Perform image histogram equalization processing on the image signal of amusement equipment after image filtering processing;

[0089] Divide the image signal of amusement equipment after image histogram equalization processing into several regions, and perform processing of calculating the average brightness of the regions;

[0090] Perform image normalization processing on the image signal of amusement equipment after processing of calculating the average brightness of the regions.

[0091] Perform image filtering processing on the image signal of amusement equipment to improve the image quality of amusement equipment. Perform image histogram equalization processing on the image signal of amusement equipment to obtain an image signal of amusement equipment with a uniform gray value distribution, so that the image signal of amusement equipment has more data information. By dividing the image signal of amusement equipment after image histogram equalization processing into several regions, and performing processing of calculating the average brightness of the regions and image normalization processing, the image is adjusted to a unified image size, which is conducive to subsequent processing of the image signal of amusement equipment.

[0092] S102. Perform amusement equipment image segmentation processing on the result of preprocessing of image signal enhancement to remove the background region and obtain the result of local segmentation processing of the amusement equipment image;

[0093] Through performing preprocessing of image signal enhancement on the image signal data information of amusement equipment, obtain the result of preprocessing of image signal enhancement. Through performing amusement equipment image segmentation processing on the result of preprocessing of image signal enhancement, remove the image background region and obtain the result of local segmentation processing of the amusement equipment image.

[0094] Perform amusement equipment image segmentation processing on the result of preprocessing of image signal enhancement to remove the background region and obtain the result of local segmentation processing of the amusement equipment image, including the following steps:

[0095] Based on gray value edge detection, perform recognition processing of the background region and the amusement equipment region on the result of preprocessing of image signal enhancement;

[0096] Perform image segmentation processing on the background area and the amusement equipment area, and remove the background area;

[0097] Perform local image segmentation processing on the amusement equipment area of the amusement equipment.

[0098] Based on the edge detection of the gray value, perform background area and amusement equipment area recognition processing on the preprocessed result of image signal enhancement, identify the background area and the amusement equipment area, perform image segmentation processing on the background area and the amusement equipment area to obtain the background area and the amusement equipment area, remove the background area to obtain the amusement equipment image signal with only the amusement equipment area, and perform local image segmentation processing on the amusement equipment area to obtain the result of local image segmentation processing of the amusement equipment.

[0099] For example, perform image segmentation processing on the image signal of amusement equipment such as a track train. Based on the edge detection of the gray value, perform recognition processing on the background area of the track train type amusement equipment and the amusement equipment area of the track train type to identify the background area of the track train type and the amusement equipment area of the track train type. Perform image segmentation processing on the background area of the track train type and the amusement equipment area of the track train type to obtain the background area of the track train type and the amusement equipment area of the track train type, remove the background area of the track train type to obtain the image signal of the track train type amusement equipment with only the amusement equipment area of the track train type, and perform local image segmentation processing on the amusement equipment area of the track train type to obtain the result of local image segmentation processing of the track train type amusement equipment.

[0100] S103. Perform amusement equipment feature recognition and extraction processing on the result of local image segmentation processing of the amusement equipment based on the amusement equipment operation state model, and generate corresponding amusement equipment feature maps;

[0101] Through performing amusement equipment image segmentation processing on the preprocessed result of image signal enhancement, removing the background area to obtain the amusement equipment image signal with only the amusement equipment area, and then performing local image segmentation processing on the amusement equipment area to obtain the result of local image segmentation processing of the amusement equipment. Obtain the historical data information of the normal operation state of the amusement equipment and the historical data information of the abnormal operation state of the amusement equipment, and construct an amusement equipment operation state model. Through performing amusement equipment feature recognition and extraction processing on the result of local image segmentation processing of the amusement equipment based on the amusement equipment operation state model, obtain the result of amusement equipment feature recognition and extraction processing, and generate corresponding amusement equipment feature maps. The generated corresponding amusement equipment feature maps include speed maps, acceleration maps, and amplitude maps.

[0102] The construction of the amusement equipment operation state model includes the following steps:

[0103] Obtaining historical data information on the normal operation status and abnormal operation status of amusement equipment, and performing image preprocessing of the amusement equipment;

[0104] Performing feature recognition and extraction processing on the amusement equipment image preprocessing results;

[0105] Performing classification and comparison processing of amusement equipment components based on the results of amusement equipment feature recognition and extraction processing;

[0106] Performing model training on the initial model of the amusement equipment based on the classification and comparison processing results of the amusement equipment components;

[0107] If the model training results are the same as the training sample results, the model training is completed; if the model training results are different from the training sample results, the model training is repeated.

[0108] Performing amusement equipment feature recognition and extraction processing on the amusement equipment image local segmentation processing result based on the amusement equipment operation state model and generating the corresponding amusement equipment feature map includes the following steps:

[0109] Performing amusement equipment feature recognition processing on the local segmentation processing results of the amusement equipment image;

[0110] Performing amusement equipment component feature marking processing on the amusement equipment feature recognition processing result;

[0111] Performing line segment area speed calculation and amplitude calculation on the result of the feature marking of the amusement equipment components;

[0112] A velocity map and an acceleration map are generated based on the speed calculation results of the line segment area, and an amplitude map is generated based on the amplitude calculation results.

[0113] For example, the results of the local segmentation processing of the train-type amusement ride image are processed for amusement ride feature recognition and extraction to obtain the train-type amusement ride feature recognition and extraction processing results. The train-type amusement ride features are processed for amusement ride component feature labeling. The train-type amusement ride features include train-type track features, train-type seat features, train-type speed features, and train-type safety protection fixed component features. The train-type track features include track slope features, track rotation features, track amplitude features, and track route features. The train-type amusement ride component feature labeling processing results are processed for line segment area speed calculation to obtain the train-type amusement ride line segment area speed calculation processing results. Based on the train-type amusement ride line segment area speed calculation processing results, a speed map and a train-type amusement ride acceleration map are generated. The feature labeling processing results are processed for line segment area amplitude calculation to generate an amplitude map based on the amplitude calculation processing results.

[0114] S104. Based on the amusement equipment operation status model, perform amusement equipment component classification and comparison processing on the amusement equipment feature recognition and extraction processing results and generate the corresponding amusement equipment feature atlas;

[0115] Through the amusement equipment feature recognition and extraction processing on the amusement equipment image local segmentation processing results based on the amusement equipment operation status model, generate the corresponding amusement equipment feature atlas, generate the speed atlas and the acceleration atlas, obtain the amusement equipment feature recognition and extraction processing results, and through the amusement equipment feature recognition and extraction processing results and generate the corresponding amusement equipment feature atlas based on the amusement equipment operation status model, perform amusement equipment component classification and comparison processing to obtain the amusement equipment component classification and comparison processing results.

[0116] Based on the amusement equipment operation status model, performing amusement equipment component classification and comparison processing on the amusement equipment feature recognition and extraction processing results and generating the corresponding amusement equipment feature atlas includes the following steps:

[0117] Based on the amusement equipment feature recognition processing results, perform amusement equipment component classification processing to obtain the amusement equipment movable component types and the amusement equipment fixed component types;

[0118] Construct the speed and acceleration constraint conditions for the amusement equipment movable component types, and compare them with the speed atlas and the acceleration atlas;

[0119] Construct the vibration amplitude constraint conditions for the amusement equipment fixed component types, and compare them with the amplitude atlas.

[0120] For example, through the amusement equipment component classification and comparison processing on the train-type amusement equipment line segment area speed calculation processing results, obtain the train-type amusement equipment component classification and comparison processing results. The train-type amusement equipment component classification processing results include the amusement equipment movable component types and the amusement equipment fixed component types. The amusement equipment movable component types include train-type seats and train-type safety protection fixed components. The amusement equipment fixed component types include train-type tracks. By constructing the speed and acceleration constraint conditions for the amusement equipment movable component types and constructing the vibration amplitude constraint conditions for the amusement equipment fixed component types, and comparing them with the speed atlas and the acceleration atlas, and comparing them with the amplitude atlas, obtain the comparison processing results of the speed atlas and the acceleration atlas, and obtain the comparison processing results of the amplitude atlas.

[0121] S105. Based on the amusement equipment operation status model, perform amusement equipment operation status determination processing on the amusement equipment component classification processing results;

[0122] Based on the operating state model of the amusement equipment, the classification processing of the amusement equipment components is carried out on the recognition and extraction processing results of the amusement equipment characteristics, and the classification processing results of the amusement equipment components are obtained, and the comparison processing of the speed spectrum, acceleration spectrum, and amplitude spectrum is carried out. Through the determination processing of the operating state of the amusement equipment based on the operating state model of the amusement equipment for the classification and comparison processing results of the amusement equipment components, the determination processing results of the operating state of the amusement equipment are obtained.

[0123] The determination processing of the operating state of the amusement equipment based on the classification and comparison processing results of the amusement equipment components by the operating state model of the amusement equipment includes the following steps:

[0124] If there are values greater than or equal to the corresponding set speed threshold and acceleration threshold of the moving parts in the speed spectrum and acceleration spectrum of the moving parts type of the amusement equipment, it is determined that the operating state of the moving parts type of the amusement equipment is abnormal; otherwise, it is determined that the operating state of the moving parts type of the amusement equipment is normal.

[0125] If there is a value greater than or equal to the corresponding set amplitude threshold of the stationary parts in the amplitude spectrum of the stationary parts type of the amusement equipment, it is determined that the operating state of the stationary parts type of the amusement equipment is abnormal; otherwise, it is determined that the operating state of the stationary parts type of the amusement equipment is normal.

[0126] For example, if there are values greater than or equal to the corresponding set speed threshold and acceleration threshold of the moving parts in the speed spectrum and acceleration spectrum of the seats of the train type or the fixed parts of the safety protection of the train type, it is determined that the operating state of the seats of the train type or the fixed parts of the safety protection of the train type is abnormal. If there is a value greater than or equal to the corresponding set amplitude threshold of the stationary parts in the amplitude spectrum of the train type track, it is determined that the operating state of the train type track is abnormal.

[0127] The above is a method for detecting the operating safety of amusement equipment based on image signal recognition provided in the embodiments of the present application. The following is a system for detecting the operating safety of amusement equipment based on image signal recognition provided in the embodiments of the present application.

[0128] A system for detecting the operating safety of amusement equipment based on image signal recognition includes:

[0129] A data acquisition unit for acquiring amusement equipment image signal data information;

[0130] A model construction unit for constructing an operating state model of the amusement equipment;

[0131] A first data processing unit for performing image signal enhancement preprocessing on the amusement equipment image signal data information;

[0132] A second data processing unit for performing amusement equipment image segmentation processing on the preprocessed result of image signal enhancement to remove the background area and obtain a local segmentation processing result of the amusement equipment image;

[0133] A third data processing unit for performing amusement equipment feature recognition and extraction processing on the local segmentation processing result of the amusement equipment image based on the amusement equipment operation state model, and generating a corresponding amusement equipment feature map;

[0134] A fourth data processing unit for performing amusement equipment component classification and comparison processing on the result of amusement equipment feature recognition and extraction processing and generating a corresponding amusement equipment feature map based on the amusement equipment operation state model;

[0135] A fifth data processing unit for performing amusement equipment operation state determination processing on the result of amusement equipment component classification processing based on the amusement equipment operation state model.

[0136] A data acquisition unit for acquiring amusement equipment image signal data information, which includes carousel amusement equipment, rotating airplane amusement equipment, track train amusement equipment, trampoline swing amusement equipment, bumper car amusement equipment, aerial sightseeing car amusement equipment, pirate ship amusement equipment.

[0137] A first data processing unit for performing preprocessing of image signal enhancement on the amusement equipment image signal data information, including:

[0138] Performing image filtering processing on the amusement equipment image signal;

[0139] Performing image histogram equalization processing on the amusement equipment image signal after image filtering processing;

[0140] Dividing the amusement equipment image signal after image histogram equalization processing into several regions, and performing regional brightness average value calculation processing;

[0141] Performing image normalization processing on the amusement equipment image signal after regional brightness average value calculation processing.

[0142] A second data processing unit for performing amusement equipment image segmentation processing on the preprocessed result of image signal enhancement to remove the background area and obtain a local segmentation processing result of the amusement equipment image, including:

[0143] Based on gray value edge detection of the preprocessed result of the image signal, performing background area and amusement equipment area recognition processing;

[0144] Performing image segmentation processing on the background area and the amusement equipment area to remove the background area;

[0145] Perform local segmentation of amusement equipment images in the amusement equipment area.

[0146] The model building unit is used to build an amusement equipment operation status model. The amusement equipment operation status model building includes:

[0147] Obtaining historical data information on the normal operation status and abnormal operation status of amusement equipment, and performing image preprocessing of the amusement equipment;

[0148] Performing feature recognition and extraction processing on the amusement equipment image preprocessing results;

[0149] Performing classification and comparison processing of amusement equipment components based on the results of amusement equipment feature recognition and extraction processing;

[0150] Performing model training on the initial model of the amusement equipment based on the classification and comparison processing results of the amusement equipment components;

[0151] If the model training results are the same as the training sample results, the model training is completed; if the model training results are different from the training sample results, the model training is repeated.

[0152] The third data processing unit is configured to perform amusement equipment feature recognition and extraction processing on the amusement equipment image local segmentation processing result based on the amusement equipment operation state model, and generate a corresponding amusement equipment feature map including:

[0153] Performing amusement equipment feature recognition processing on the local segmentation processing results of the amusement equipment image;

[0154] Performing amusement equipment component feature marking processing on the amusement equipment feature recognition processing result;

[0155] Performing line segment area speed calculation and amplitude calculation on the result of the feature marking of the amusement equipment components;

[0156] A velocity map and an acceleration map are generated based on the speed calculation results of the line segment area, and an amplitude map is generated based on the amplitude calculation results.

[0157] The fourth data processing unit is configured to process the amusement equipment feature identification and extraction results based on the amusement equipment operation state model and generate a corresponding amusement equipment feature map, and perform a classification and comparison process on the amusement equipment components, including:

[0158] Based on the result of the feature recognition processing of the amusement equipment, the amusement equipment parts are classified to obtain the types of the movable parts and the fixed parts of the amusement equipment;

[0159] Construct the speed and acceleration constraints of the active parts of the amusement equipment and compare them with the speed and acceleration maps;

[0160] Construct the vibration amplitude constraints of the fixed parts of the amusement equipment and compare them with the amplitude spectrum.

[0161] The fifth data processing unit is configured to perform a process for determining the operating state of the amusement equipment based on the amusement equipment component classification processing result based on the amusement equipment operating state model, and includes:

[0162] If the speed map and acceleration map of the active component type of the amusement equipment contain speed thresholds and acceleration thresholds greater than or equal to the corresponding set speed thresholds of the active component, the operating status of the active component type of the amusement equipment is judged to be abnormal; otherwise, the operating status of the active component type of the amusement equipment is judged to be normal.

[0163] If the amplitude spectrum of the fixed component type of the amusement equipment contains an amplitude greater than or equal to the corresponding set amplitude threshold of the fixed component, the operation status of the fixed component type of the amusement equipment is judged to be abnormal; otherwise, the operation status of the fixed component type of the amusement equipment is judged to be normal.

[0164] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0165] The terms "first", "second" and "third" etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0166] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units described is merely a logical functional division. In actual implementation, other division methods may be used, such as combining or integrating multiple units or components into another system, or ignoring or not implementing certain features.

[0167] The unit described as a separation component may or may not be physically separated. The component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] In addition, each functional unit in various embodiments of the present application may be integrated in a processing unit, may also be physically present separately for each unit, or two or more units may be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0169] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A method for detecting the operation safety of amusement equipment based on image signal recognition, characterized in that It includes the following steps: S101. Obtain the image signal data information of the amusement equipment and perform preprocessing of image signal enhancement; S102. Perform image segmentation processing on the result of the preprocessing of image signal enhancement for the amusement equipment to remove the background area and obtain the local segmentation processing result of the amusement equipment image; S103. Based on the operation state model of the amusement equipment, perform amusement equipment feature recognition and extraction processing on the local segmentation processing result of the amusement equipment image, and generate the corresponding amusement equipment feature spectrum; S104. Based on the operation state model of the amusement equipment, perform amusement equipment component classification and comparison processing on the result of the amusement equipment feature recognition and extraction processing and the generated corresponding amusement equipment feature spectrum; S105. Based on the operation state model of the amusement equipment, perform amusement equipment operation state determination processing on the result of the amusement equipment component classification processing; The performing amusement equipment feature recognition and extraction processing on the local segmentation processing result of the amusement equipment image based on the operation state model of the amusement equipment and generating the corresponding amusement equipment feature spectrum includes the following steps: Perform amusement equipment feature recognition processing on the local segmentation processing result of the amusement equipment image; Perform amusement equipment component feature marking processing on the result of the amusement equipment feature recognition processing; Perform line segment area speed calculation processing and amplitude calculation processing on the result of the amusement equipment component feature marking processing; Generate a speed spectrum and an acceleration spectrum based on the result of the line segment area speed calculation processing, and generate an amplitude spectrum based on the result of the amplitude calculation processing.

2. The method for detecting the operation safety of amusement equipment based on image signal recognition according to claim 1, characterized in that: The obtaining the image signal data information of the amusement equipment and performing preprocessing of image signal enhancement includes the following steps: Perform image filtering processing on the amusement equipment image signal; Perform image histogram equalization processing on the amusement equipment image signal that has undergone image filtering processing; Divide the amusement equipment image signal that has undergone image histogram equalization processing into several regions, and perform regional brightness average value calculation processing; Perform image normalization processing on the amusement equipment image signal that has undergone regional brightness average value calculation processing.

3. The method for detecting the operation safety of amusement equipment based on image signal recognition according to claim 1, characterized in that: The performing image segmentation processing on the result of the preprocessing of image signal enhancement for the amusement equipment to remove the background area and obtain the local segmentation processing result of the amusement equipment image includes the following steps: Based on gray value edge detection, perform background area and amusement equipment area recognition processing on the result of the preprocessing of image signal enhancement; Perform image segmentation processing on the background area and the amusement equipment area to remove the background area; Perform local segmentation processing of the amusement equipment image on the amusement equipment area.

4. The method for detecting the operation safety of amusement equipment based on image signal recognition according to claim 1, characterized in that: The construction of the operation state model of the amusement equipment includes the following steps: Obtain the historical data information of the normal operation state of the amusement equipment and the historical data information of the abnormal operation state of the amusement equipment, and perform preprocessing of the amusement equipment image; Perform amusement equipment feature recognition and extraction processing on the result of the preprocessing of the amusement equipment image; Perform amusement equipment component classification and comparison processing based on the result of the amusement equipment feature recognition and extraction processing; Perform model training processing on the initial model of the amusement equipment based on the result of the amusement equipment component classification and comparison processing; If the model training result is the same as the training sample result, the model training is completed; if the model training result is different from the training sample result, re-perform model training.

5. The method for detecting the operation safety of amusement equipment based on image signal recognition according to claim 1, characterized in that: Based on the operation state model of the amusement equipment, the processing results of identifying and extracting the characteristics of the amusement equipment and generating the corresponding characteristic atlas of the amusement equipment, and the classification and comparison processing of the amusement equipment components include the following steps: Based on the processing results of identifying the characteristics of the amusement equipment, classify the components of the amusement equipment to obtain the types of movable components and the types of immovable components of the amusement equipment; Construct the speed and acceleration constraint conditions for the types of movable components of the amusement equipment, and compare them with the speed atlas and the acceleration atlas; Construct the vibration amplitude constraint conditions for the types of immovable components of the amusement equipment, and compare them with the amplitude atlas.

6. The method for detecting the operation safety of amusement equipment based on image signal recognition according to claim 1, characterized in that: Based on the operation state model of the amusement equipment, the processing of determining the operation state of the amusement equipment based on the processing results of classifying and comparing the amusement equipment components includes the following steps: If there are values greater than or equal to the corresponding set speed threshold and acceleration threshold of the movable components in the speed atlas and the acceleration atlas of the types of movable components of the amusement equipment, it is determined that the operation state of the types of movable components of the amusement equipment is abnormal; otherwise, it is determined that the operation state of the types of movable components of the amusement equipment is normal; If there is a value greater than or equal to the corresponding set amplitude threshold of the immovable components in the amplitude atlas of the types of immovable components of the amusement equipment, it is determined that the operation state of the types of immovable components of the amusement equipment is abnormal; otherwise, it is determined that the operation state of the types of immovable components of the amusement equipment is normal.

7. An operation safety system for amusement equipment based on image signal recognition and detection, characterized in that, Including: A data acquisition unit for acquiring the image signal data information of the amusement equipment; A model construction unit for constructing an operation state model of the amusement equipment; A first data processing unit for performing preprocessing of image signal enhancement on the image signal data information of the amusement equipment; A second data processing unit for performing image segmentation processing on the result of the preprocessing of image signal enhancement to remove the background area and obtain the local segmentation processing result of the amusement equipment image; A third data processing unit for performing amusement equipment feature identification and extraction processing on the local segmentation processing result of the amusement equipment image based on the operation state model of the amusement equipment, and generating the corresponding characteristic atlas of the amusement equipment; A fourth data processing unit for performing classification and comparison processing of the amusement equipment components based on the processing results of identifying and extracting the characteristics of the amusement equipment and generating the corresponding characteristic atlas of the amusement equipment based on the operation state model of the amusement equipment; A fifth data processing unit for performing amusement equipment operation state determination processing based on the processing results of classifying the amusement equipment components based on the operation state model of the amusement equipment; The third data processing unit performs amusement equipment feature identification and extraction processing on the local segmentation processing result of the amusement equipment image based on the operation state model of the amusement equipment, and generates the corresponding characteristic atlas of the amusement equipment, including: Performing amusement equipment feature identification processing on the local segmentation processing result of the amusement equipment image; Performing amusement equipment component feature marking processing on the processing result of the amusement equipment feature identification; Performing line segment area speed calculation processing and amplitude calculation processing on the processing result of the amusement equipment component feature marking; Generating a speed atlas and an acceleration atlas based on the processing result of the line segment area speed calculation, and generating an amplitude atlas based on the processing result of the amplitude calculation.

8. The amusement equipment operation safety system based on image signal recognition and detection according to claim 7 is characterized in that: The fourth data processing unit performs classification and comparison processing of amusement equipment components based on the operation state model of the amusement equipment for the feature recognition and extraction processing results of the amusement equipment and generates corresponding amusement equipment feature maps, including: Performing classification processing of amusement equipment components based on the feature recognition processing results of the amusement equipment to obtain the types of movable components and fixed components of the amusement equipment; Constructing speed and acceleration constraint conditions for the types of movable components of the amusement equipment and performing comparison processing with the speed map and acceleration map; Constructing vibration amplitude constraint conditions for the types of fixed components of the amusement equipment and performing comparison processing with the amplitude map.

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