A state self-checking method and system of an immersive live interactive device

Abstract

This invention relates to a self-checking method and system for the status of immersive interactive devices, belonging to the field of interactive device technology. The method includes: performing a status self-check on each motion seat in response to a power-on signal and collecting no-load self-check parameters; determining the no-load self-check result; collecting the current time point and determining the current operating segment; determining the loading self-check location point based on the no-load self-check result, and determining the loading self-check scheme and loading self-check benchmark parameters; performing a loading self-check based on the loading self-check scheme and collecting loading self-check parameters; determining the loading self-check result; combining the no-load self-check result and the loading self-check result to determine the comprehensive self-check result; and determining operation recommendation information and operation and maintenance information based on the comprehensive self-check result and outputting them to the administrator's terminal. This invention improves the accuracy of motion seat self-checks and enhances the overall experience for all visitors.

Description

Technical Field

[0001] This invention relates to the field of field interactive device technology, and in particular to a self-checking method and system for the status of an immersive field interactive device. Background Technology

[0002] Interactive devices typically refer to electronic devices or apparatuses deployed in a specific physical location that can interact with users in real time and in two directions, thereby transmitting information, providing services, or creating experiences.

[0003] In a large-scale immersive flying theater in a theme park, the interactive equipment in a single hall includes six-degrees-of-freedom motion seats, projectors, environmental effects equipment (wind, fog, water, scent, vibration), a central control system, and a safety interlock system. Based on the actual theater requirements, the central control system synchronizes the operation of the six-degrees-of-freedom motion seats, projectors, and environmental effects equipment, providing visitors with an immersive experience. To ensure a truly immersive experience, before the interactive equipment in a single hall is put into operation, a self-test is performed, including full-stroke motion tests for each motion seat, calibration and color consistency checks for the projector's blending band, timing trigger tests for the environmental effects equipment, and circuit continuity verification for the safety interlock system. This ensures that all interactive equipment functions correctly during the visitor experience.

[0004] Currently, the full-stroke motion tests of each motion seat are generally conducted before tourists experience them. Therefore, the self-checks of the motion seats are all performed under no-load conditions. This can easily lead to situations where the seats are normal when empty but lack power when fully occupied. This can cause some motion seats to experience motion lag and poor positioning accuracy, thereby reducing the experience for some tourists. Summary of the Invention

[0005] To improve the accuracy of self-checking of motion seats and enhance the experience for all visitors, this invention provides a method and system for self-checking the status of immersive on-site interactive devices.

[0006] In a first aspect, the present invention provides a self-checking method for the status of an immersive on-site interactive device, employing the following technical solution: A self-checking method for the status of an immersive on-site interactive device includes: In response to the power-on signal, the system performs a status self-check on each motion seat based on the preset no-load seat self-check scheme and collects no-load self-check parameters. The no-load self-test result is determined by comparing the no-load self-test parameters with the preset seat self-test benchmark parameters. Collect the current time point, and determine the current running segment based on the current time point's occurrence with the preset device running segment; The loading self-test location point is determined by combining the current running segment and the no-load self-test results, and the loading self-test scheme and loading self-test benchmark parameters are determined based on the loading self-test location point; Perform load self-test based on the load self-test scheme and collect load self-test parameters; The loading self-test result is determined based on the comparison between the loading self-test parameters and the loading self-test baseline parameters; The overall self-inspection result is determined by combining the no-load self-inspection results and the loaded self-inspection results. Based on the comprehensive self-inspection results, the recommended operation information and operation and maintenance information are determined and output to the terminal held by the administrator.

[0007] By adopting the above technical solution, the system performs an unloaded self-test in response to the power-on signal and collects unloaded self-test parameters. These parameters are then compared with unloaded self-test baseline parameters to obtain the unloaded self-test results. The system then divides the equipment's operating time into segments based on the current time point, thereby determining the targeted loading self-test location. A corresponding loading self-test scheme and loading self-test baseline parameters are matched to perform the loading self-test. The system then synthesizes the unloaded and loading self-test results to obtain a comprehensive self-test result. Finally, it determines and outputs recommended operating information and maintenance information adapted to the current scenario. This approach simultaneously considers both unloaded basic verification and real load condition verification, resolving the disconnect between the unloaded self-test and full-load operation of the motion seats. It achieves precise self-testing at different time periods and levels, ensuring the operational safety and targeted maintenance of immersive interactive equipment, improving the accuracy of motion seat self-testing, and ultimately enhancing the experience for all visitors.

[0008] Optionally, methods for determining the load self-test location point include: Based on the current runtime segment, retrieve the historical operating parameters of each motion seat, and determine the remaining self-test time value according to the current runtime segment; The historical selection location point is selected by combining the remaining self-test time value and historical operating parameters. Determine whether all no-load self-test results are preset successful self-test results; If so, the historical selected location point will be used as the loading self-check location point; If not, retrieve the location of the no-load self-test failure based on the no-load self-test result; Based on the location point of the no-load self-test failure, the historical selection location points are adjusted to determine the failed selection location points, and the failed selection location points are used as the loading self-test location points.

[0009] By adopting the above technical solution, historical operating parameters are retrieved and historical selection location points are selected in combination with the remaining self-test time value. Then, it is judged whether all no-load self-test results are preset successful self-test results. When all are preset successful self-test results, the historical selection location points are used as loading self-test location points. When not all are preset successful self-test results, the no-load self-test failure location points are retrieved and adjusted to obtain the failed selection location points, which are then used as loading self-test location points. This prioritizes the verification of no-load abnormal related points, avoids blind selection of loading self-test points, and improves the rationality of loading self-test point selection.

[0010] Optionally, methods for determining historical selection locations include: Historical operating loads are retrieved based on historical operating parameters, and the estimated weight value for operators is determined based on the historical operating loads. Determine the operating baseline parameters based on the weight values ​​estimated by the operators; Based on the comparison results between historical operating parameters and operating baseline parameters, the operating deviation parameters are determined; Determine the baseline parameters for operational deviation based on historical operating loads; Based on the comparison between the operating deviation parameters and the operating deviation benchmark parameters, the location points of the operating anomalies are determined. Determine the number of self-test values ​​based on the remaining self-test time; Based on the self-check values, the abnormal operation location points are selected and adjusted to obtain the abnormal selection location points, and the abnormal selection location points are used as historical selection location points.

[0011] By adopting the above technical solution, historical operating loads are retrieved through historical operating parameters to determine the estimated weight value of operators. Then, the operating benchmark parameters are determined through the estimated weight value of operators. Combined with historical operating parameters, operating deviation parameters are obtained. Then, by determining the operating deviation benchmark parameters through historical operating loads, abnormal operating locations are identified. Finally, the number of self-check values ​​is determined through the remaining self-check time value to filter and adjust the abnormal operating locations to obtain historically selected locations. This ensures that the historically selected locations conform to the operating deviation patterns under the actual load of tourists, and prioritizes the self-checking of seat locations that are prone to load performance degradation.

[0012] Optionally, methods for determining the location of runtime anomalies include: By comparing the operating deviation parameters with the operating deviation benchmark parameters, the benchmark deviation value and the corresponding benchmark deviation type are determined. Determine the category benchmark coefficient based on the category of benchmark deviation; Calculate the product between the baseline deviation value and the category baseline coefficient, and use it as a single category reference value; Calculate the sum of all individual reference values ​​corresponding to the same operating deviation parameter and use it as the reference value for position selection; Based on the comparison between the selected location reference value and the preset selection benchmark reference value, a reference selection location point is determined, and the selected location point is used as the abnormal operation location point.

[0013] By adopting the above technical solution, the reference deviation value and reference deviation type are obtained by comparing the operating deviation parameter with the operating deviation benchmark parameter. The reference coefficient of the type is determined and the reference value for position selection is calculated. In this way, the abnormal operation position points are screened and determined. Differentiated weight judgment can be made for different types of seat operating deviations, and the seat points corresponding to different abnormal types such as motor attenuation and transmission abnormality can be accurately identified, thereby improving the comprehensiveness and accuracy of abnormal operation position point identification.

[0014] Optionally, methods for determining abnormal selection locations include: Retrieve values ​​at the abnormal locations based on the abnormal location points; Calculate the difference between the number of abnormal locations and the number of self-checks, and use this difference as the additional number of self-checks. Determine if any of the additional self-check values ​​are negative; If so, then combine the additional self-check values ​​and positions to select reference values ​​to determine additional supplementary location points; The additional supplementary location points are combined with the abnormal operation location points and used as historical selection location points; If not, the abnormal location point will be used as the historical selection location point, and the remaining self-check time value will be adjusted and updated based on the additional self-check values.

[0015] By adopting the above technical solution, additional self-check values ​​are obtained by comparing the number of abnormal locations with the number of self-check values. When the additional self-check values ​​are negative, additional supplementary location points are added to improve the historically selected location points. When the values ​​are positive, the abnormal location points are directly used and the remaining self-check time value is adjusted. This achieves dynamic adaptation between the number of self-check points and the self-check duration, and makes full use of the remaining self-check time value to supplement the points, thereby improving the time utilization rate of the self-check process.

[0016] Optionally, methods for determining failed selection locations include: Determine whether the historical selected location points include locations where no-load self-test failed; If so, the historical selected location point that is consistent with the location point of the no-load self-test failure will be taken as the failure consistent location point, and the historical selected location point other than the failure consistent location point will be taken as the historical success location point. The remaining historical location points are determined by comparing them with the preset overall seat location points. Based on the failed consistent location point, select the adjacent historical remaining location points and use them as the failed adjacent location points; The failed adjacent positions are combined with historical successful positions and used as the failed selection positions. If not, then the historical selected position point will be considered a failed selection position point.

[0017] By adopting the above technical solution, the system determines whether the historical selected location points include location points that failed during unloaded self-test. If and only if they do, it defines a consistent failure location point and a historical successful location point. It then filters the adjacent failure location points among the remaining historical location points and combines them with the historical successful location points to obtain the failure selection location point. This allows for priority detection of seats around the failure location point, thereby improving the accuracy of the failure selection location point.

[0018] Optionally, after selecting the adjacent points of the failed selection, the following steps are also included: Retrieve historical loading self-check time points based on adjacent locations of failures; Calculate the time interval between the historical loading self-test time point and the current time point, and use it as the historical self-test interval value; Determine the baseline interval value for runtime self-test based on the current runtime segment; Determine whether the historical self-test interval value is greater than the operational self-test baseline interval value; If yes, continue outputting the adjacent positions of the failure; If not, then based on the failed consistent location point, a new adjacent historical remaining location point is selected and the failed adjacent location point is updated and replaced.

[0019] By adopting the above technical solution, the historical self-test interval value is calculated by retrieving the historical loading self-test time point and compared with the running self-test benchmark interval value. Then, the adjacent position points of the recently completed loading self-test are updated and replaced. This can avoid repeatedly verifying points that have no recent anomalies, prioritize the selection of related points that have not been self-tested for a long time, reduce invalid self-test operations, and improve the overall self-test efficiency.

[0020] Optionally, after determining the remaining historical location points, the following may also be included: Determine the distribution area of ​​successful locations based on historical successful locations; The remaining location distribution area is determined by comparing the successful location distribution area with the preset overall seat location points; Based on the historical remaining location points and the distribution area of ​​remaining locations, the distribution and placement locations are determined; Calculate the distance between the distribution landing point and the adjacent failure consistent point and use it as the distribution landing distance value; Retrieve the number of failed consistent values ​​based on the failed consistent location points; The location point for distribution selection is determined by combining the number of consistent failures with the distance value from the distribution's fall point. The selected location points are combined with historical successful location points and used as failed selection location points.

[0021] By adopting the above technical solution, the distribution area of ​​successful locations and the distribution area of ​​remaining locations are divided to determine the location points where the distribution falls and to calculate the distance value of the distribution falling. Then, the consistent values ​​of failures are retrieved to combine with the selection of distribution location points. Finally, the distribution selection location points are combined with historical successful location points as failure selection location points. This takes into account the distance correlation and regional distribution pattern of failure points, and further improves the scientific nature of the selection of failure selection location points.

[0022] Optionally, the methods for determining the loading self-test scheme and loading self-test baseline parameters include: Calculate the average of the estimated weight values ​​by the operators and use it as the average estimated weight; Retrieve values ​​for each self-test position based on the loaded self-test position points; Determine the self-inspection number adjustment coefficient based on the number of self-inspection locations; Calculate the product between the self-inspection number adjustment factor and the estimated average weight, and use it as the estimated weight adjustment value. Determine the average weight baseline parameters and weight relative to load value based on the estimated weight adjustment value; A loading self-test scheme is formed based on the weight relative to the load value, and the average weight benchmark parameter is used as the loading self-test benchmark parameter.

[0023] By adopting the above technical solution, the average estimated weight of the operators is calculated and the estimated weight adjustment value is calculated in combination with the self-inspection number adjustment coefficient. In this way, the average weight benchmark parameter and the weight relative load value are determined, and a loading self-inspection scheme and loading self-inspection benchmark parameter that are adapted to the actual weight distribution of tourists are generated. This accurately matches the actual load conditions during normal operation, thereby improving the authenticity and reference value of loading self-inspection.

[0024] Secondly, the present invention provides a status self-checking system for an immersive on-site interactive device, which adopts the following technical solution: A self-checking system for the status of an immersive on-site interactive device includes: The data acquisition module is used to collect idle self-test parameters, the current time point, and loading self-test parameters. The memory stores a program for implementing a state self-checking method for an immersive field interactive device as described in any one of the first aspects; The processor loads and executes programs stored in memory.

[0025] In summary, the present invention has at least one of the following beneficial technical effects: 1. By responding to the power-on signal, the system performs an unloaded self-test and collects unloaded self-test parameters. These parameters are compared with the unloaded self-test baseline parameters to obtain the unloaded self-test results. The system then divides the equipment's operating time into segments based on the current time point, thereby determining the loading self-test location points and matching the corresponding loading self-test scheme and loading self-test baseline parameters to perform loading self-tests. The system combines the unloaded self-test results with the loading self-test results to obtain a comprehensive self-test result. Finally, it determines and outputs recommended operation information and operation and maintenance information adapted to the current scenario. This approach simultaneously considers both unloaded basic verification and real load condition verification, solving the problem of the disconnect between the unloaded self-test of the motion seats and the operation under full load. It achieves precise self-testing by time period and level, ensuring the operational safety and targeted maintenance of immersive on-site interactive equipment, improving the accuracy of motion seat self-testing, and ultimately enhancing the experience for all visitors. 2. Retrieve historical operating parameters and combine them with the remaining self-test time value to select historical selection location points. Then, determine whether all no-load self-test results are preset successful self-test results. If all are preset successful self-test results, use the historical selection location points as loading self-test location points. If not all are preset successful self-test results, retrieve the no-load self-test failure location points, adjust them to obtain the failed selection location points, and use them as loading self-test location points. This prioritizes the verification of no-load abnormal related points, avoids blind selection of loading self-test points, and improves the rationality of loading self-test point selection. 3. Calculate the average estimated weight of operators and combine it with the self-inspection number adjustment coefficient to calculate the estimated weight adjustment value. In this way, determine the average weight benchmark parameter and the weight relative load value, generate a loading self-inspection scheme and loading self-inspection benchmark parameter that are adapted to the actual weight distribution of tourists, accurately match the actual load conditions during normal operation, and thus improve the authenticity and reference value of loading self-inspection. Attached Figure Description

[0026] Figure 1 This is a flowchart of the self-checking method for the status of immersive on-site interactive devices; Figure 2 This is a flowchart illustrating the method for determining the self-test location point. Figure 3 This is a flowchart illustrating the loading self-test scheme and the method for determining the loading self-test baseline parameters. Detailed Implementation

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0028] A self-checking method for immersive interactive devices is proposed. This method collects no-load self-check parameters in response to the power-on signal and compares them with no-load self-check baseline parameters to obtain the no-load self-check result. Based on the current time, the device's operating period is determined, and the loading self-check location is determined by combining the operating period and the no-load self-check result. By analyzing historical operating parameters and combining the operator's estimated weight value, operating deviation parameters, and remaining self-check time, the method optimizes the location. Simultaneously, it dynamically corrects the loading self-check location based on the no-load self-check failure location and the spatial distribution characteristics of the seats. Furthermore, it generates a relative load value based on the estimated average weight and matches the corresponding loading self-check scheme with the loading self-check baseline parameters to complete the loading self-check. Combining the no-load and loading self-check results with the remaining self-check time, the method outputs recommended operating information and maintenance information. This approach simultaneously addresses both no-load baseline verification and actual load condition verification, resolving the disconnect between no-load self-checks and full-load operation of the dynamic seats. It achieves precise self-checks at different time periods and levels, ensuring the operational safety and targeted maintenance of the immersive interactive devices, improving the accuracy of dynamic seat self-checks, and ultimately enhancing the experience for all visitors.

[0029] Reference Figure 1 This invention discloses a self-checking method for the status of an immersive on-site interactive device, comprising: S100: In response to the power-on signal, it performs a status self-check on each motion seat based on the preset no-load seat self-check scheme and collects no-load self-check parameters.

[0030] Among them, the power-on signal refers to the electrical signal or software instruction generated when the power of the immersive on-site interactive device is turned on, the system is started, or it is manually triggered by the administrator.

[0031] An unloaded seat self-check program is an automated script or program used to check the basic functions of a motion seat, such as its mechanical movement, drive response, and sensor feedback, when the seat is not occupied (i.e., in an unloaded state). The unloaded seat self-check program is obtained after pre-input by the operator.

[0032] No-load self-test parameters refer to parameters such as drive current, response speed, and travel accuracy collected by each motion seat during self-testing when no one is sitting on it. These parameters are obtained through sensors pre-installed in the drive motors, servo actuators, or joint bearings of each motion seat.

[0033] Upon receiving the power-on signal, the system executes the unloaded seat self-test protocol to perform a status self-test on each motion seat and collects the unloaded self-test parameters for subsequent use.

[0034] S101: Determine the no-load self-test result based on the comparison between the no-load self-test parameters and the preset seat self-test benchmark parameters.

[0035] The no-load self-test result refers to the success of the self-test performed on each motion seat when no one is seated. The seat self-test baseline parameters are pre-stored reference parameter ranges used to determine whether the motion seat's no-load operation is normal. These baseline parameters are obtained after being pre-input by the operator.

[0036] By comparing the no-load self-test parameters with the preset seat self-test benchmark parameters, when the no-load self-test parameters meet the preset seat self-test benchmark parameters, the preset self-test success result is output as the no-load self-test result; when the no-load self-test parameters do not meet the preset seat self-test benchmark parameters, the preset self-test failure result is output as the no-load self-test result.

[0037] A successful self-test result indicates that the motion seat has successfully completed its self-test when no one is seated. A failed self-test result indicates that the motion seat has failed its self-test when no one is seated. Successful and failed self-test results are obtained after pre-entry by the operator.

[0038] S102: Collect the current time point and determine the current running segment based on the current time point's occurrence with the preset device running segment.

[0039] The current time point refers to the current point in time. The current time point is obtained by querying the built-in real-time clock module.

[0040] The equipment runtime segment refers to the set of time periods corresponding to the normal operation time and interval time of the motion seat. The equipment runtime segment is obtained through pre-input by the operator. The current runtime segment refers to the current operating stage of the motion seat.

[0041] By collecting data at the current time point and analyzing whether the current time point falls within the preset device runtime segment, if the current time point does not fall within the device runtime segment at all, it means that the current time is the device just turned on and the preset power-on runtime segment is output and used as the current runtime segment. If the current time point falls within the device runtime segment, the interval time corresponding to the current runtime segment or the most recent interval time is used as the current runtime segment for convenient use later.

[0042] The startup runtime period refers to the time period immediately following startup.

[0043] For example, the device's runtime segments are as follows: 8:00-8:20 is the running time, 8:20-8:30 is the interval time, 8:30-8:50 is the running time, 8:50-9:00 is the interval time, and so on until 18:00. If the current time is 7:50, the startup runtime segment will be used as the current runtime segment; if the current time is 8:50, the second interval time segment will be used as the current runtime segment.

[0044] S103: Determine the loading self-test location point by combining the current running segment and the no-load self-test results, and determine the loading self-test scheme and loading self-test benchmark parameters based on the loading self-test location point.

[0045] Here, "load self-test location point" refers to the specific seat number or physical location among all motion seats in the venue that requires further testing under simulated load conditions. "Load self-test scheme" refers to the automated script or program used to load the motion seats to simulate human seating and perform self-tests. "Load self-test benchmark parameters" refers to the standard values ​​used to judge whether the load self-test parameters are qualified.

[0046] By combining and analyzing the current runtime segment and the no-load self-test results, the loading self-test location point is determined. Then, by analyzing the loading self-test location point, the loading self-test scheme and loading self-test benchmark parameters are determined for convenient subsequent use.

[0047] S104: Perform load self-test based on the load self-test scheme and collect load self-test parameters.

[0048] Among them, the loading self-test parameters refer to the parameters such as drive current, response speed, and travel accuracy collected by each motion seat during the self-test when simulating a person sitting. The loading self-test parameters are obtained by sensors preset in the drive motor, servo actuator, or joint bearing of each motion seat.

[0049] By controlling the electromagnetic loading device pre-installed on the motion seat to apply a simulated load through a self-test scheme, and performing a self-test, the loading self-test parameters are collected for subsequent use.

[0050] S105: Determine the loading self-test result based on the comparison between the loading self-test parameters and the loading self-test baseline parameters.

[0051] Among them, the loading self-test result refers to the result of whether the self-test of each motion seat is successful in the simulated passenger riding state.

[0052] By comparing the loading self-test parameters with the loading self-test benchmark parameters, when the loading self-test parameters meet the loading self-test benchmark parameters, a preset self-test success result is output as the loading self-test result; when the loading self-test parameters do not meet the loading self-test benchmark parameters, a preset self-test failure result is output as the loading self-test result.

[0053] S106: Determine the comprehensive self-inspection result by combining the no-load self-inspection result and the loaded self-inspection result.

[0054] The self-inspection comprehensive result refers to the final status assessment of the overall dynamic seat based on the self-inspection results under both loaded and unloaded conditions.

[0055] By combining the unloaded self-test results with the loaded self-test results, the dynamic seats with successful and failed self-test results are classified and merged to obtain a comprehensive self-test result, which is convenient for subsequent use.

[0056] S107: Determine recommended operation information and operation and maintenance information based on the comprehensive self-inspection results, and output the recommended operation information and operation and maintenance information to the terminal held by the administrator.

[0057] The "Operation Recommendation Information" refers to recommended locations indicating that the motion seat can operate normally. The "Operation and Maintenance Information" refers to location information indicating that the motion seat requires maintenance. The "Administrator Terminal" refers to the communication terminal held by personnel managing and maintaining the motion seat's operation. This terminal can be a mobile phone.

[0058] By retrieving the location numbers of the motion seats corresponding to successful self-test results from the comprehensive self-test results and using them as operational recommendation information, and then retrieving the location numbers of the motion seats corresponding to failed self-test results from the comprehensive self-test results and using them as operational maintenance information, and then outputting the operational recommendation information and operational maintenance information to the administrator's terminal, the system simultaneously considers both no-load basic verification and actual load condition verification. This solves the problem of the disconnect between no-load self-testing and full-load operation of motion seats, enabling precise self-testing at different times and levels. This ensures the operational safety and targeted maintenance of immersive on-site interactive equipment, improves the accuracy of motion seat self-testing, and ultimately enhances the experience for all visitors.

[0059] To further ensure the rationality of the loading self-test position point, it is necessary to perform a further separate analysis and calculation on the loading self-test position point, which will be explained in detail through the following steps.

[0060] Reference Figure 2 The method for determining the self-test location point includes the following steps: S200: Retrieves historical operating parameters of each motion seat based on the current operating segment, and determines the remaining self-test time value based on the current operating segment.

[0061] Historical operating parameters refer to a set of time-series data continuously recorded and stored by the system during the actual operation of each motion seat, reflecting the operating status of each operation. Historical operating parameters include quantifiable indicators such as the real-time current value of the drive motor, the thrust feedback value of the servo actuator, the response time of moving parts, the displacement stroke curve, and the load detection value. The remaining self-test time value refers to the time available for self-testing between the current operating segment and the boundary moment of the next segment transition.

[0062] The system retrieves the operating parameters corresponding to the most recent running time from the device's running time segment based on the current running time segment and uses them as historical operating parameters. Then, it retrieves the most recent running time from the device's running time segment based on the current running time segment and calculates the time interval between the current time point and uses it as the remaining self-test time value for convenient use later.

[0063] S201: Select historical location points by combining the remaining self-test time value and historical operating parameters.

[0064] Among them, the historical selection location points refer to a set of candidate locations selected from all the dynamic seats in the venue for loading self-testing.

[0065] By combining and analyzing the remaining self-test time value with historical operating parameters, a historical selection point can be determined for convenient subsequent use.

[0066] S202: Determine whether all no-load self-test results are preset successful self-test results. If yes, proceed to S203; if no, proceed to S204.

[0067] In this process, the system determines whether historically selected location points can be used directly by checking whether all the no-load self-test results are preset successful self-test results.

[0068] S203: Use the historical selected location point as the loading self-test location point.

[0069] When all no-load self-test results are preset successful self-test results, it means that the no-load self-test is qualified and the historically selected location points can be used directly. Therefore, the historically selected location points are used as the loading self-test location points.

[0070] S204: Retrieve the location of the no-load self-test failure based on the no-load self-test results.

[0071] Among them, the no-load self-test failure location point refers to the location corresponding to the motion seat that failed the no-load self-test.

[0072] When the no-load self-test results are not all the preset successful self-test results, it means that the no-load self-test is not qualified at this time, and the historical selected location points cannot be used directly. Therefore, the no-load self-test failure location points are retrieved through the no-load self-test results for convenient use later.

[0073] S205: Adjust the historical selected position points based on the no-load self-test failure position points, determine the failed selected position points, and use the failed selected position points as the load self-test position points.

[0074] Among them, the failed selection location points refer to the final set of detection locations formed after correcting and adjusting the historical selection location points.

[0075] By adjusting and analyzing the historical selected locations based on the locations of failed no-load self-tests, the failed selected locations are determined and used as the loading self-test locations, thereby improving the accuracy of the obtained loading self-test locations.

[0076] To further ensure the rationality of the historically selected location points, it is necessary to perform further separate analysis and calculation on the historically selected location points, which will be explained in detail through the steps shown below.

[0077] The method for determining historical location points includes the following steps: S300: Retrieves historical operating loads based on historical operating parameters and determines the estimated weight value for operators based on the historical operating loads.

[0078] Historical operating load refers to the physical quantity record characterizing the actual load borne by the motion seats during each operation. Estimated weight value by operators refers to the calculated estimate representing the actual weight of the audience during the current operating period.

[0079] By retrieving historical operating parameters, the historical operating load is obtained, and then the product between the historical operating load and the preset load weight coefficient is calculated and used as the estimated weight value for operators, which is convenient for subsequent use.

[0080] The load weight factor is a factor used to convert historical operating load into the estimated weight value of operators. The load weight factor is calculated by having people of different weights sit in the motion seat and collecting the actual load borne by the motion seat.

[0081] S301: Determine the operating baseline parameters based on the weight value estimated by the operators.

[0082] Among them, the operating reference parameters refer to the set of parameters corresponding to the normal tolerance range that the key indicators such as the current, response time, and stroke accuracy of the motion seat drive motor should fall into under simulated specific load conditions.

[0083] By inputting the estimated weight value of the operators into a preset weight reference table, the operating reference parameters are matched to facilitate subsequent use.

[0084] The weight reference table is pre-stored with different estimated weight ranges for operators and their corresponding operating reference parameters. The weight reference table can be obtained by querying the factory specifications of the motion seat, or by applying different levels of weight using standard weights or simulated dummies. Standard operating data of the health seat under various weight conditions can be collected one by one and established in advance after statistical analysis.

[0085] S302: Determine the operating deviation parameters based on the comparison results between historical operating parameters and operating baseline parameters.

[0086] Among them, the operating deviation parameter refers to the set of deviation values ​​corresponding to the existence of deviations in various operating parameters.

[0087] By comparing historical operating parameters with operating baseline parameters in sequence according to indicator type, and calculating the deviation value corresponding to each indicator, the results are combined as operating deviation parameters for convenient subsequent use.

[0088] S303: Determine the operating deviation baseline parameters based on historical operating loads.

[0089] Among them, the operating deviation benchmark parameter refers to the threshold standard used to determine whether the operating deviation parameter constitutes an anomaly.

[0090] Different historical operating loads correspond to different operating deviation benchmark parameters. The larger the historical operating load, the larger the allowable deviation range corresponding to the operating deviation benchmark parameter.

[0091] The load ratio is calculated by comparing the historical operating load with the preset baseline load. The product of the load ratio with the preset unit baseline value for each index type is then calculated. The results are then used to form a dataset as the benchmark parameter for operating deviation, which is convenient for subsequent use.

[0092] The reference load refers to the initial load preset by the operator, which is set in advance according to actual needs. The unit reference value corresponding to each indicator type refers to the specific value of key indicators such as drive motor current, response time, and stroke accuracy under the reference load. The unit reference value is obtained by the operator pre-testing and collecting data from several motion seats based on the reference load and then calculating the average value.

[0093] S304: Determine the location of the abnormal operation based on the comparison between the operating deviation parameters and the operating deviation reference parameters.

[0094] Among them, the abnormal operation location point refers to the location corresponding to the abnormal operation of the motion seat.

[0095] By analyzing the comparison results between the operating deviation parameters and the operating deviation benchmark parameters, the location points of operating abnormalities can be determined, which will facilitate subsequent use.

[0096] S305: Determine the number of self-test values ​​based on the remaining self-test time.

[0097] Among them, the number of self-check values ​​refers to the number of values ​​that the motion seat can perform a self-check within the remaining self-check time.

[0098] The quotient between the remaining self-inspection time value and the preset self-inspection unit time value is calculated and used as the self-inspection batch. Then, the product between the self-inspection batch and the preset single self-inspection value is calculated and used as the self-inspection value, which is convenient for subsequent use.

[0099] The self-test unit time value refers to the time required to perform self-tests on the same batch of motion seats simultaneously. The single self-test count value refers to the maximum number of motion seats that can be controlled simultaneously for loading self-tests in a single batch. Both the self-test unit time value and the single self-test count value are obtained after pre-input by the operator.

[0100] S306: Based on the self-test values, select and adjust the abnormal location points to obtain the abnormal selection location points, and use the abnormal selection location points as historical selection location points.

[0101] Among them, the abnormal selection location point refers to the location point corresponding to the selected abnormal location point after adjustment.

[0102] By analyzing and adjusting the selected abnormal location points based on the self-check values, the abnormal selection location points are determined and used as historical selection location points, thereby improving the accuracy of the obtained historical selection location points.

[0103] To further ensure the rationality of the abnormal operation location points, it is necessary to perform further separate analysis and calculation on the abnormal operation location points, which will be explained in detail through the following steps.

[0104] The method for determining the location of the runtime anomaly includes the following steps: S400: Based on the comparison between the operating deviation parameters and the operating deviation reference parameters, determine the reference deviation value and the corresponding reference deviation type.

[0105] The benchmark deviation value refers to the difference between the deviation value of a single indicator and its corresponding allowable deviation range. The benchmark deviation type refers to the type of indicator corresponding to the benchmark deviation value.

[0106] By retrieving the deviation values ​​corresponding to each index type in the operational deviation parameters and calculating the difference between the deviation value and the nearest value of the corresponding deviation tolerance range as the benchmark deviation value, the index type corresponding to the benchmark deviation value is used as the benchmark deviation type for convenient subsequent use.

[0107] S401: Determine the category benchmark coefficient based on the category of benchmark deviation.

[0108] Among them, the category benchmark coefficient refers to the differentiated weighting factor pre-assigned to each category of benchmark deviation.

[0109] By inputting the type of benchmark deviation into a preset type benchmark lookup table, the type benchmark coefficient is obtained for easy subsequent use.

[0110] The category benchmark comparison table is pre-stored with different benchmark deviation categories and their corresponding category benchmark coefficients. The category benchmark comparison table is pre-set by the operator according to actual needs.

[0111] For example, the category reference table can be set as follows: the category reference coefficient is 1.2 when the reference deviation category is the real-time current value, the category reference coefficient is 0.9 when the reference deviation category is the thrust feedback value of the servo actuator, and the category reference coefficient is 1.3 when the reference deviation category is the response time of the moving part.

[0112] S402: Calculate the product between the baseline deviation value and the category baseline coefficient and use it as a reference value for a single category.

[0113] Among them, the single-category reference value refers to the comprehensive quantitative score of the deviation range between the deviation value corresponding to a single indicator type and the normal deviation boundary.

[0114] The product of the baseline deviation value and the category baseline coefficient is calculated, and the calculation result is used as a single category reference value for convenient subsequent use.

[0115] S403: Calculate the sum of all individual reference values ​​corresponding to the same operating deviation parameter and use it as the reference value for position selection.

[0116] The reference value for location selection refers to the comprehensive quantitative score corresponding to the existence of deviation in the same operational deviation parameter.

[0117] The sum of the individual reference values ​​corresponding to the same operating deviation parameter is calculated, and the calculation result is used as the reference value for position selection, which is convenient for subsequent use.

[0118] S404: Based on the comparison result between the selected location reference value and the preset selection benchmark reference value, determine the reference selection location point and use the selected location point as the abnormal operation location point.

[0119] The selected baseline reference value refers to the baseline reference value at which the operating parameters begin to develop towards an abnormal situation. The selected baseline reference value is obtained through pre-input by the operator.

[0120] By analyzing the comparison results between the selected position reference value and the preset selection benchmark reference value, and taking the dynamic seat position corresponding to the operation deviation parameter when the selected position reference value is greater than the selection benchmark reference value as the reference selected position point, and then taking the selected position point as the operation abnormal position point, the accuracy of the obtained operation abnormal position point is improved.

[0121] To further ensure the rationality of the abnormally selected location points, it is necessary to perform further separate analysis and calculation on the abnormally selected location points, which will be explained in detail through the following steps.

[0122] The method for determining the location of anomalies includes the following steps: S500: Retrieves the number of abnormal locations based on the abnormal location points.

[0123] Among them, the number of abnormal locations refers to the number of values ​​corresponding to the abnormal location points in the operation.

[0124] By counting the abnormal locations during operation and using the count results as the number of abnormal locations, it is convenient for subsequent use.

[0125] S501: Calculate the difference between the number of abnormal locations and the number of self-checks, and use it as the additional number of self-checks.

[0126] The additional self-check values ​​refer to the values ​​required for additional self-checks.

[0127] The difference between the number of abnormal locations and the number of self-checks is calculated, and the result is used as the additional number of self-checks. S502: Determine if the additional self-test values ​​are negative. If yes, proceed to S503; if no, proceed to S505.

[0128] Specifically, the system determines whether additional data needs to be added by checking whether the extra self-check values ​​are negative.

[0129] S503: Combine additional self-test values ​​and location to select reference values ​​to determine additional supplementary location points.

[0130] Among them, additional supplementary location points refer to location points that need to be added for self-checking.

[0131] When the extra self-check value is negative, it means that the number of abnormal positions is less than the number of self-check values, so it needs to be supplemented. Therefore, the number of extra self-check values ​​and the position selection reference value that is closer to the selected benchmark reference value are selected as the dynamic seat position as the extra supplementary position point for convenient use later.

[0132] S504: Combine additional supplementary location points with abnormal operation location points and use them as historical selection location points.

[0133] In this method, additional supplementary location points are combined with abnormal location points to form a location set, and this location set is used as historical selection location points to improve the accuracy of the obtained historical selection location points.

[0134] S505: Use the location of the abnormal operation as the historical selection location, and adjust and update the remaining self-test time value based on the additional self-test values.

[0135] When the additional self-check value is not negative, it means that the number of abnormal locations is not less than the number of self-check values, so no additional supplementation is needed. Therefore, the abnormal location point is used as the historical selection location point. Then, the quotient between the additional self-check value and the single self-check value is calculated, and the product of the quotient and the self-check unit time value is used as the additional time value. The sum of the additional time value and the remaining self-check time value is calculated, and the sum is used to replace and update the remaining self-check time value, thereby improving the accuracy of the obtained remaining self-check time value and the historical selection location point.

[0136] To further ensure the rationality of the failed selection of location points, it is necessary to perform further separate analysis and calculation on the failed selection of location points, which will be explained in detail through the following steps.

[0137] The method for determining the location of a failed selection includes the following steps: S600: Determine whether the historical selected location points include location points where no-load self-test failed. If yes, proceed to S601; if no, proceed to S605.

[0138] Specifically, the system determines whether historically selected location points can be used directly by checking whether they include locations where the no-load self-test failed.

[0139] S601: The historical selected location point that is consistent with the location point of no-load self-test failure is taken as the failure consistent location point, and the historical selected location point other than the failure consistent location point is taken as the historical success location point.

[0140] When the historical selected location points include the location points of no-load self-test failure, it means that the historical selected location points cannot be used directly at this time. Therefore, the failure consistent location points and the historical success location points are defined to facilitate their use in the future.

[0141] S602: Based on the comparison between historically selected location points and preset overall seat location points, determine the remaining historical location points.

[0142] The overall seat position points refer to the set of positions corresponding to all motion seats. These overall seat position points are obtained through pre-input by the operator. The remaining historical position points refer to the set of positions corresponding to motion seats excluding historically selected position points.

[0143] By comparing the historically selected location points with the preset overall seat location points, the positions corresponding to the dynamic seats other than the historically selected location points are used as the remaining historical location points for convenient use later.

[0144] S603: Select adjacent historical remaining location points based on the failed consistent location points and use them as failed adjacent location points.

[0145] Among them, the adjacent position point of failure refers to the remaining historical position point that is adjacent to the position point that is consistent with failure.

[0146] By selecting adjacent points to the failed points, it becomes easier to use them later.

[0147] S604: Combine the failed adjacent position points with the historical successful position points and use them as the failed selection position points.

[0148] This method improves the accuracy of obtaining failed selection points by combining adjacent failed locations with historical successful locations to form a location set, and then using this location set as the failed selection location point.

[0149] S605: Use historical selected position points as failed selection position points.

[0150] When the historical selected location points do not include the location points of the no-load self-test failure, it means that the historical selected location points can be used directly at this time. Therefore, the historical selected location points are used as the failure selected location points to improve the accuracy of the obtained failure selected location points.

[0151] To further ensure the rationality of selecting failed adjacent points, it is necessary to perform further separate analysis and calculation on the selected adjacent points, which will be explained in detail through the steps shown below.

[0152] After selecting the adjacent points of the failed selection, the following steps are also included: S700: Retrieves historical loading self-check time points based on adjacent failure locations.

[0153] Among them, the historical loading self-check time point refers to the time point corresponding to the self-check of the adjacent position point of failure.

[0154] By querying adjacent locations of failures and retrieving historical loading self-check timestamps, it is convenient for subsequent use.

[0155] S701: Calculate the time interval between the historical load self-test time point and the current time point and use it as the historical self-test interval value.

[0156] Among them, the historical self-check interval value refers to the time interval between the historical loading self-check time point and the current time point.

[0157] Calculating historical self-test interval values ​​facilitates subsequent use.

[0158] S702: Determine the self-test baseline interval value based on the current running segment.

[0159] Among them, the self-test baseline interval value refers to the standard threshold determined by the current running segment for judging whether the time interval between the last load self-test and the current time interval of a seat is too long.

[0160] By analyzing the current runtime segment, if the current runtime segment is a power-on runtime segment, the preset next-day baseline interval value is output and used as the runtime self-test baseline interval value. If the current runtime segment is not a power-on runtime segment, the preset daily baseline interval value is output and used as the runtime self-test baseline interval value.

[0161] Both the next-day baseline interval and the current-day baseline interval are preset by the operator according to actual needs, and the next-day baseline interval is greater than the current-day baseline interval.

[0162] S703: Determine whether the historical self-test interval value is greater than the operational self-test baseline interval value. If yes, proceed to S704; if no, proceed to S705.

[0163] Specifically, by judging whether the historical self-test interval value is greater than the running self-test baseline interval value, it is determined whether it is necessary to adjust the adjacent positions of the failure.

[0164] S704: Continue outputting adjacent points of failure.

[0165] When the historical self-test interval value is greater than the running self-test baseline interval value, it means that there is no need to adjust the adjacent position points of failure at this time, so the adjacent position points of failure continue to be output.

[0166] S705: Based on the failed consistent location point, reselect the adjacent remaining historical location points and update and replace the failed adjacent location points.

[0167] When the historical self-test interval value is not greater than the running self-test baseline interval value, it indicates that the adjacent failure position points need to be adjusted. Therefore, another adjacent historical remaining position point is selected through the consistent failure position point, and the newly selected historical remaining position point is used to update and replace the adjacent failure position points, thereby improving the accuracy of the obtained adjacent failure position points.

[0168] To further ensure the rationality of determining the remaining historical location points, it is necessary to perform further separate analysis and calculations after determining the remaining historical location points, which will be explained in detail through the steps shown below.

[0169] After determining the remaining historical location points, the following steps are also included: S800: Determine the distribution area of ​​successful locations based on historical successful location points.

[0170] Among them, the successful location distribution area refers to one or more continuous geographical areas formed by historical successful location points.

[0171] By merging historically successful locations that are physically adjacent, a distribution area of ​​successful locations without hollow areas is formed, which facilitates subsequent use.

[0172] S801: Determine the remaining location distribution area by comparing the successful location distribution area with the preset overall seat location points.

[0173] The remaining location distribution area refers to the area excluding the successful location distribution area.

[0174] By comparing the successful location distribution area with the preset overall seat location points, the area other than the successful location distribution area is retrieved and used as the remaining location distribution area for convenient subsequent use.

[0175] S802: Determine the distribution location points based on the historical remaining location points and the distribution area of ​​the remaining locations.

[0176] Among them, the distribution landing point refers to the historical remaining position point when it falls into the remaining position distribution area.

[0177] By analyzing the historical remaining location points and the distribution area of ​​remaining locations, the historical remaining location points that fall within the distribution area of ​​remaining locations are used as the distribution location points for convenient subsequent use.

[0178] S803: Calculate the distance between the distribution fall-in location and the adjacent failure consistent location and use it as the distribution fall-in distance value.

[0179] The distribution fall-in distance value refers to the distance between the distribution fall-in location and the adjacent failure consistency location.

[0180] Calculating the distance values ​​of the distribution falls into the ground facilitates subsequent use.

[0181] S804: Retrieve the number of failed consistent values ​​based on the failed consistent location point.

[0182] Among them, the number of failures with consistent values ​​refers to the number of values ​​corresponding to the failure with consistent values ​​location points.

[0183] By counting the failed consistency points and using the count as the number of failed consistency points, it is convenient to use them later.

[0184] S805: Combine the number of failures with the distribution's distance from the point of failure to determine the location of the distribution.

[0185] Among them, the selected location point refers to the location point corresponding to the selected location point after the failure of the consistent location point is selected according to the distribution.

[0186] By selecting the dynamic seats that fall closest to the distribution value based on the number of consecutive failures, a set of locations is obtained, thereby determining the distribution selection location points for convenient subsequent use.

[0187] S806: Select location points based on distribution and combine them with historical successful location points, and use them as failed selection location points.

[0188] Specifically, by combining the selected location points with historical successful location points to form a location set, and then using this location set as the failed selection location points, the accuracy of the obtained failed selection location points is improved.

[0189] To further ensure the rationality of the loading self-test scheme and loading self-test benchmark parameters, it is necessary to conduct further separate analysis and calculation of the loading self-test scheme and loading self-test benchmark parameters, which will be explained in detail through the following steps.

[0190] Reference Figure 3 The method for determining the loading self-test scheme and loading self-test baseline parameters includes the following steps: S900: Calculate the average of the estimated weight values ​​of the operators and use it as the average estimated weight.

[0191] The average estimated weight refers to the average of the weight values ​​estimated by the operators.

[0192] The average value of the estimated weight is calculated to facilitate subsequent use.

[0193] S901: Retrieve the number of self-test position values ​​based on the loaded self-test position points.

[0194] Among them, the number of self-test positions refers to the number of values ​​corresponding to the self-test position points.

[0195] By counting the self-test position points, and using the count result as the number of self-test positions, it is convenient for subsequent use.

[0196] S902: Determine the self-test number adjustment coefficient based on the number of self-test positions.

[0197] The self-inspection number adjustment factor is a factor used to correct the weight based on the number of self-inspections.

[0198] The smaller the number of self-check positions, the closer the adjustment coefficient for the number of self-check positions is to 1; the larger the number of self-check positions, the less the adjustment coefficient for the number of self-check positions is to 1.

[0199] The number of self-test positions is entered into a preset number adjustment table to obtain the self-test number adjustment coefficient, which is convenient for subsequent use.

[0200] The number adjustment table is pre-stored with different self-test position values ​​and corresponding self-test number adjustment coefficients. The number adjustment table can be preset by the operator according to actual needs.

[0201] For example, the number adjustment table can be set as follows: when the number of self-check positions is 1, the self-check number adjustment coefficient is 1; when the number of self-check positions is less than 5, the self-check number adjustment coefficient is 0.9; when the number of self-check positions is less than 10, the self-check number adjustment coefficient is 0.8; and when the number of self-check positions is greater than 10, the self-check number adjustment coefficient is 0.6.

[0202] S903: Calculate the product between the self-inspection number adjustment factor and the estimated average weight and use it as the estimated weight adjustment value.

[0203] The estimated weight adjustment value refers to the weight value after the weight has been adjusted.

[0204] The product of the self-inspection number adjustment factor and the estimated average weight is calculated, and the result is used as the estimated weight adjustment value for convenient subsequent use.

[0205] S904: Determine the average weight baseline parameter and weight relative to load value based on the estimated weight adjustment value.

[0206] Among them, the average weight benchmark parameter refers to the set of core reference indicators used to judge whether the loading self-test is qualified. The weight relative to the load value refers to the load value relative to the estimated weight adjustment value.

[0207] The estimated weight adjustment value is calculated by multiplying the estimated weight adjustment value with the preset load weight coefficient, and the result is used as the weight relative to the load value. The estimated weight adjustment value is then input into the preset weight reference table to match the average weight reference parameter for easy use later.

[0208] S905: A loading self-test scheme is formed based on the weight relative to the load value, and the average weight reference parameter is used as the loading self-test reference parameter.

[0209] Specifically, by using the weight relative to the load value as a load control command to form a loading self-test scheme, and then using the average weight reference parameter as the loading self-test reference parameter, the accuracy of the obtained loading self-test scheme and loading self-test reference parameter is improved.

[0210] Based on the same inventive concept, embodiments of the present invention provide a status self-checking system for an immersive on-site interactive device, comprising: The data acquisition module is used to collect idle self-test parameters, the current time point, and loading self-test parameters. The memory stores a program for implementing a state self-checking method for an immersive field interactive device as described above; The processor loads and executes programs stored in memory.

[0211] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0212] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A self-checking method for the status of an immersive on-site interactive device, characterized in that, include: In response to the power-on signal, the system performs a status self-check on each motion seat based on the preset no-load seat self-check scheme and collects no-load self-check parameters. The no-load self-test result is determined by comparing the no-load self-test parameters with the preset seat self-test benchmark parameters. Collect the current time point, and determine the current running segment based on the current time point's occurrence with the preset device running segment; The loading self-test location point is determined by combining the current running segment and the no-load self-test results, and the loading self-test scheme and loading self-test benchmark parameters are determined based on the loading self-test location point; Perform load self-test based on the load self-test scheme and collect load self-test parameters; The loading self-test result is determined based on the comparison between the loading self-test parameters and the loading self-test baseline parameters; The overall self-inspection result is determined by combining the no-load self-inspection results and the loaded self-inspection results. Based on the comprehensive self-inspection results, the recommended operation information and operation and maintenance information are determined and output to the terminal held by the administrator.

2. The self-checking method for the status of an immersive on-site interactive device according to claim 1, characterized in that, The methods for determining the self-test location point include: Based on the current runtime segment, retrieve the historical operating parameters of each motion seat, and determine the remaining self-test time value according to the current runtime segment; The historical selection location point is selected by combining the remaining self-test time value and historical operating parameters. Determine whether all no-load self-test results are preset successful self-test results; If so, the historical selected location point will be used as the loading self-check location point; If not, retrieve the location of the no-load self-test failure based on the no-load self-test result; Based on the location point of the no-load self-test failure, the historical selection location points are adjusted to determine the failed selection location points, and the failed selection location points are used as the loading self-test location points.

3. The self-checking method for the status of an immersive on-site interactive device according to claim 2, characterized in that, The methods for determining historical location points include: Historical operating loads are retrieved based on historical operating parameters, and the estimated weight value for operators is determined based on the historical operating loads. Determine the operating baseline parameters based on the weight values ​​estimated by the operators; Based on the comparison results between historical operating parameters and operating baseline parameters, the operating deviation parameters are determined; Determine the baseline parameters for operational deviation based on historical operating loads; Based on the comparison between the operating deviation parameters and the operating deviation benchmark parameters, the location points of the operating anomalies are determined. Determine the number of self-test values ​​based on the remaining self-test time; Based on the self-check values, the abnormal operation location points are selected and adjusted to obtain the abnormal selection location points, and the abnormal selection location points are used as historical selection location points.

4. The self-checking method for the status of an immersive on-site interactive device according to claim 3, characterized in that, Methods for determining the location of runtime anomalies include: By comparing the operating deviation parameters with the operating deviation benchmark parameters, the benchmark deviation value and the corresponding benchmark deviation type are determined. Determine the category benchmark coefficient based on the category of benchmark deviation; Calculate the product between the baseline deviation value and the category baseline coefficient, and use it as a single category reference value; Calculate the sum of all individual reference values ​​corresponding to the same operating deviation parameter and use it as the reference value for position selection; Based on the comparison between the selected location reference value and the preset selection benchmark reference value, a reference selection location point is determined, and the selected location point is used as the abnormal operation location point.

5. The self-checking method for the status of an immersive on-site interactive device according to claim 4, characterized in that, The methods for determining abnormal selection locations include: Retrieve values ​​at the abnormal locations based on the abnormal location points; Calculate the difference between the number of abnormal locations and the number of self-checks, and use this difference as the additional number of self-checks. Determine if any of the additional self-check values ​​are negative; If so, then combine the additional self-check values ​​and positions to select reference values ​​to determine additional supplementary location points; The additional supplementary location points are combined with the abnormal operation location points and used as historical selection location points; If not, the abnormal location point will be used as the historical selection location point, and the remaining self-check time value will be adjusted and updated based on the additional self-check values.

6. The self-checking method for the status of an immersive on-site interactive device according to claim 2, characterized in that, The methods for determining the location of a failed selection include: Determine whether the historical selected location points include locations where no-load self-test failed; If so, the historical selected location point that is consistent with the location point of the no-load self-test failure will be taken as the failure consistent location point, and the historical selected location point other than the failure consistent location point will be taken as the historical success location point. The remaining historical location points are determined by comparing them with the preset overall seat location points. Based on the failed consistent location point, select the adjacent historical remaining location points and use them as the failed adjacent location points; The failed adjacent positions are combined with historical successful positions and used as the failed selection positions. If not, then the historical selected position point will be considered a failed selection position point.

7. The self-checking method for the status of an immersive on-site interactive device according to claim 6, characterized in that, After selecting the failed adjacent location points, the following is also included: Retrieve historical loading self-check time points based on adjacent locations of failures; Calculate the time interval between the historical loading self-test time point and the current time point, and use it as the historical self-test interval value; Determine the baseline interval value for runtime self-test based on the current runtime segment; Determine whether the historical self-test interval value is greater than the operational self-test baseline interval value; If yes, continue outputting the adjacent positions of the failure; If not, then based on the failed consistent location point, a new adjacent historical remaining location point is selected and the failed adjacent location point is updated and replaced.

8. The self-checking method for the status of an immersive on-site interactive device according to claim 6, characterized in that, After determining the remaining historical location points, the following is also included: Determine the distribution area of ​​successful locations based on historical successful locations; The remaining location distribution area is determined by comparing the successful location distribution area with the preset overall seat location points; Based on the historical remaining location points and the distribution area of ​​remaining locations, the distribution and placement locations are determined; Calculate the distance between the distribution landing point and the adjacent failure consistent point and use it as the distribution landing distance value; Retrieve the number of failed consistent values ​​based on the failed consistent location points; The location point for distribution selection is determined by combining the number of consistent failures with the distance value from the distribution's fall point. The selected location points are combined with historical successful location points and used as failed selection location points.

9. The self-checking method for the status of an immersive on-site interactive device according to claim 3, characterized in that, The methods for determining the loading self-test scheme and loading self-test baseline parameters include: Calculate the average of the estimated weight values ​​by the operators and use it as the average estimated weight; Retrieve values ​​for each self-test position based on the loaded self-test position points; Determine the self-inspection number adjustment coefficient based on the number of self-inspection locations; Calculate the product between the self-inspection number adjustment factor and the estimated average weight, and use it as the estimated weight adjustment value. Determine the average weight baseline parameters and weight relative to load value based on the estimated weight adjustment value; A loading self-test scheme is formed based on the weight relative to the load value, and the average weight benchmark parameter is used as the loading self-test benchmark parameter.

10. A status self-checking system for an immersive on-site interactive device, characterized in that, include: The data acquisition module is used to collect idle self-test parameters, the current time point, and loading self-test parameters. The memory stores a program for implementing a state self-checking method for an immersive field interactive device as described in any one of claims 1 to 9; The processor loads and executes programs stored in memory.

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