Elevator overload detection and adjustment method and system, computer equipment and storage medium

Abstract

The invention discloses an elevator overload detecting and adjusting method and system, computer equipment and a storage medium. The method comprises the steps that a current rope head deformation distance value collected by a distance measuring sensor is obtained in real time; a current car image, collected by the image sensor, in the car is obtained in real time, and image preprocessing is carried out; according to the current rope head deformation distance value and a preset running state rule, the running state of the current elevator is determined; if the running state of the current elevator is a no-load state, image reference comparison is carried out according to the preprocessed current elevator car image and a preset reference elevator car image so as to update the reference elevator car image; and if the running state of the current elevator is an overload state, overload adjustment optimization work is carried out according to the preprocessed current car image and a detection adjustment rule. The stability of elevator overload protection work can be improved, so that safe operation of an elevator is ensured, and the personal safety of passengers is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of elevator detection technology, and in particular to an elevator overload detection and adjustment method, system, computer equipment and storage medium. Background Art

[0002] In recent years, with the progress of social modernization, the use of elevators has been expanding, and elevators have become a common means of transportation for people to travel. However, elevators, like other means of transportation, have a certain load capacity. At present, when the elevator starts to load, the car bottom or the car rope end will undergo a certain amount of elastic deformation, causing it to contact the micro switch installed at the car bottom or the car rope end, thereby triggering its switch to send a signal. At this time, the elevator enters an overload state and is prohibited from running.

[0003] However, after the car has been running for a long time, the micro switch may become loose, resulting in displacement and misalignment, which affects the accuracy of judging whether the elevator is overloaded, and further affects the stability of the elevator overload protection. For example, when the elevator is overloaded by mistake or enters the overload state before reaching the load capacity, it will lead to low elevator utilization and affect people's travel time; or when it exceeds its load capacity but still does not enter the overload state and continues to run, this situation is likely to cause dangerous accidents and endanger personal safety; no matter which of the above situations occurs, manual timed transportation of weights is required for adjustment, which cannot be predicted in advance, greatly affecting the safe operation of the elevator, and subsequent maintenance will cost a lot of manpower, material resources and time, resulting in low elevator maintenance efficiency and high cost. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an elevator overload detection and adjustment method, system, computer equipment and storage medium, which can improve the stability of elevator overload protection work, thereby ensuring the safe operation of the elevator and protecting the personal safety of passengers.

[0005] In order to solve the above technical problems, the present invention provides an elevator overload detection and adjustment method, including: real-time acquisition of the current rope head deformation distance value collected by the distance measuring sensor; real-time acquisition of the current car image inside the car by the image sensor, and image preprocessing; determining the current operating state of the elevator according to the current rope head deformation distance value and preset operating state rules; if the current operating state of the elevator is an unloaded state, performing an image baseline comparison between the preprocessed current car image and a preset baseline car image to update the baseline car image; if the current operating state of the elevator is an overloaded state, performing overload adjustment optimization work according to the preprocessed current car image and the detection and adjustment rules.

[0006] As an improvement of the above scheme, the step of determining the current operating status of the elevator based on the current rope head deformation distance value and the preset operating status rules includes: judging whether the current rope head deformation distance value is less than or equal to the preset rope head deformation overload value; if it is judged as yes, it indicates that the elevator is currently in an overloaded state; if it is judged as no, judging whether there is no call signal within the preset time; if it is judged as yes, it indicates that the elevator is currently in an unloaded state.

[0007] As an improvement of the above scheme, the step of performing an image baseline comparison between the pre-processed current car image and a preset baseline car image to update the baseline car image includes: calculating the image similarity between the current car image and the preset baseline car image to obtain a first image similarity value; judging whether the first image similarity value is greater than a first preset similarity threshold, if so, the baseline car image remains unchanged, if not, performing image comparison and verification processing.

[0008] As an improvement of the above-mentioned scheme, the steps of the image comparison and verification processing include: reacquiring the current car image and performing image preprocessing; calculating the image similarity between the current car image and the benchmark car image; determining whether the new first image similarity value is less than or equal to a first preset similarity threshold, and if so, updating the current car image to a new benchmark car image, and if not, keeping the benchmark car image unchanged.

[0009] As an improvement of the above scheme, the step of performing overload adjustment optimization according to the preprocessed current car image and the detection adjustment rule includes: calculating the image similarity between the current car image and the preset reference car image to obtain a second image similarity value; when the second image similarity value is less than a second preset similarity threshold, adjusting the optimization formula X i =A*X i , in order to optimize and adjust the rope head deformation overload value, and send out early warning signals to the monitoring platform and / or maintenance platform, where X i is the rope head deformation overload value, A is a constant, and 0<A<1; when the second image similarity value is less than or equal to the third preset similarity threshold and greater than or equal to the second preset similarity threshold, the rope head deformation overload value remains unchanged, and an alarm signal is sent to the monitoring platform and / or maintenance platform; when the second image similarity value is greater than the third preset similarity threshold, the rope head deformation overload value remains unchanged.

[0010] As an improvement of the above solution, the data preprocessing step includes: performing image binarization processing on the collected current car image to obtain the preprocessed current car image.

[0011] As an improvement of the above scheme, if the current operating state of the elevator is a no-load state, it is determined whether the current rope head deformation distance value is less than a preset rope head deformation no-load value. If it is determined to be yes, the current rope head deformation distance value is updated to a new rope head deformation no-load value.

[0012] Correspondingly, the present invention also provides an elevator overload detection and adjustment system, comprising: a first acquisition module, used to acquire in real time the current rope head deformation distance value collected by the distance measuring sensor; a second acquisition module, used to acquire in real time the current car image collected by the image sensor inside the car, and perform image preprocessing; a state determination module, used to determine the current operating state of the elevator according to the current rope head deformation distance value and preset operating state rules; a first state execution module, used to, if the operating state of the current elevator is an unloaded state, perform an image baseline comparison between the preprocessed current car image and a preset baseline car image to update the baseline car image; a second state execution module, used to, if the operating state of the current elevator is an overloaded state, perform overload adjustment optimization work according to the preprocessed current car image and detection and adjustment rules.

[0013] Correspondingly, the present invention further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described above when executing the computer program.

[0014] Accordingly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0015] The implementation of the present invention has the following beneficial effects: The present invention adopts a distance measuring sensor to replace the traditional contact overload detection switch, which has high detection accuracy and low installation cost. The current rope head deformation distance value collected by the distance measuring sensor and the preset operation status rule can automatically detect and determine the current operation status of the elevator, and corresponding detection and adjustment work can be performed according to different elevator operation states, thereby improving the stability of the elevator overload protection work, thereby ensuring the safe operation of the elevator and protecting the personal safety of passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the elevator overload detection and adjustment method of the present invention; Figure 2 It is a structural schematic diagram of the elevator overload detection and adjustment system of the present invention; Figure 3 is a structural schematic diagram of a second acquisition module of the present invention; Figure 4 is a structural diagram of a state determination module of the present invention; Figure 5 is a structural diagram of a first state execution module of the present invention; Figure 6 is a structural schematic diagram of a first state processing unit of the present invention; Figure 7 It is a structural diagram of the second state execution module of the present invention. DETAILED DESCRIPTION

[0017] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

[0018] like Figure 1 As shown, a specific embodiment of the present invention provides an elevator overload detection and adjustment method, comprising: S101, obtaining in real time the current rope head deformation distance value collected by the distance measuring sensor; It should be noted that the distance sensor is set at one end of the elevator car rope head structure. The distance sensor is used to detect the deformation distance between one end and the other end of the rope head structure to determine the loading condition of the car; the smaller the current rope head deformation distance value is, the greater the weight of the car. By using a distance sensor to replace the traditional contact overload detection switch (such as a micro switch), it has the advantages of convenient detection operation, high detection accuracy and low installation cost.

[0019] Preferably, in other embodiments, the distance measuring sensor may also be arranged on the rope head structure of the car bottom.

[0020] Preferably, the distance measuring sensor may be an infrared distance measuring sensor or a laser distance measuring sensor, but is not limited thereto.

[0021] S102, acquiring a current car image inside the car by using an image sensor in real time, and performing image preprocessing; It should be noted that the image sensor disposed in the car can collect images of the interior of the car in real time, and the loading status of the car can be analyzed and determined based on the current car image. The image sensor is preferably a camera device having the image sensor.

[0022] Specifically, the data preprocessing step includes: performing image binarization processing on the collected current car image to obtain the preprocessed current car image.

[0023] It should be noted that image binarization is performed on each collected image to obtain a binary image, which can reduce the amount of data processing and highlight important features of the image.

[0024] S103, determining the current operating state of the elevator according to the current rope head deformation distance value and a preset operating state rule; Specifically, the step of determining the current operating state of the elevator according to the current rope head deformation distance value and the preset operating state rule includes: Determine whether the current rope head deformation distance value is less than or equal to a preset rope head deformation overload value, If the answer is yes, it means the elevator is currently overloaded. If the judgment is no, it is determined whether there is no call signal within the preset time. If the judgment is yes, it indicates that the elevator is currently in an unloaded state.

[0025] It should be noted that when the current rope head deformation distance value obtained in real time is less than or equal to the preset rope head deformation overload value, it means that the elevator is currently in an overloaded state and needs to be overloaded; otherwise, it means that the elevator is currently in a non-overloaded state. In this state, it is determined whether there is a call signal within the preset time. If there is no call signal, it means that the elevator is currently in an unloaded state, and the benchmark parameter correction processing of the unloaded state can be performed.

[0026] Among them, the preset time may preferably be 30 minutes, 1 hour, 2 hours, 3 hours or 4 hours, etc., without too many restrictions here.

[0027] Preferably, the preset time may also be a detection time period of one month, half a month, or one day of a week, such as a time period in the early morning when there are few people to perform no-load state detection and benchmark parameter adjustment.

[0028] S104, if the current running state of the elevator is an unloaded state, performing an image benchmark comparison between the preprocessed current car image and a preset benchmark car image to update the benchmark car image; Specifically, the step of performing image benchmark comparison between the preprocessed current car image and a preset benchmark car image to update the benchmark car image includes: Step 1: Calculate the image similarity between the current car image and a preset reference car image to obtain a first image similarity value; It should be noted that the image similarity between the current car image and the preset reference car image is calculated based on pixel comparison to obtain a first image similarity value F. The first image similarity value F can be used to measure the car loading condition. The closer the F value is to 1, the higher the similarity, that is, it is closer to an empty condition. The closer the F value is to 0, the lower the similarity, that is, it is closer to an overloaded condition.

[0029] The preset reference car image is an original image of the floor in the car collected by the image sensor when the elevator is unloaded and the illumination is the same, and the image is used as the reference car image after image preprocessing.

[0030] Step 2: determine whether the first image similarity value is greater than a first preset similarity threshold value. If so, the reference car image remains unchanged. If not, perform image comparison and verification processing.

[0031] It should be noted that when the first image similarity value is greater than the first preset similarity threshold, it means that the current car image is similar to the reference car image. At this time, the reference car image does not need to be updated or replaced and can remain unchanged; when the first image similarity value is less than or equal to the first preset similarity threshold, image comparison and verification processing is performed.

[0032] The image comparison and verification process includes: Step 1: Re-acquire the current car image and perform image preprocessing; Step 2: Calculate the image similarity between the current car image and the reference car image; Step 3: determine whether the new similarity value of the first image is less than or equal to a first preset similarity threshold; if so, update the current car image to a new reference car image; if not, keep the reference car image unchanged.

[0033] It should be noted that when performing image comparison and verification processing, the current car image is reacquired and image preprocessing is performed to obtain a new current car image; the image similarity between the current car image and the preset reference car image is calculated based on pixel comparison to obtain a new first image similarity value; when the first image similarity value is still greater than or equal to the first preset similarity threshold, the new current car image is updated to a new reference car image, otherwise the reference car image remains unchanged. The above-mentioned method can avoid large errors in the calculated image similarity value due to changes in the interior of the car during use, thereby affecting the determination of the car device status and reducing the detection accuracy. Among them, changes in the interior of the car include changes in the illumination of the lights in the car or changes in the objects or floor patterns inside the car.

[0034] Preferably, the first preset similarity threshold is preferably 0.9, but is not limited thereto.

[0035] Furthermore, if the current operation state of the elevator is an unloaded state, it is also possible to determine whether the current rope head deformation distance value is less than the preset rope head deformation unloaded value. If it is determined to be yes, the current rope head deformation distance value is updated to a new rope head deformation unloaded value to adapt to the unloaded changes of the car, such as a large change in the weight of the decoration on the elevator floor; otherwise, the rope head deformation unloaded value remains unchanged, and the elevator is in an overall unloaded state. The above-mentioned rope head deformation unloaded value detection and correction process can facilitate maintenance personnel or monitoring personnel to clearly know the unloaded changes of the elevator, thereby facilitating elevator monitoring and management.

[0036] S105: If the current operating state of the elevator is an overload state, overload adjustment optimization is performed according to the pre-processed current car image and detection adjustment rules.

[0037] Specifically, the step of performing overload adjustment optimization according to the preprocessed current car image and the detection adjustment rule includes: Step 1: Calculate the image similarity between the current car image and a preset reference car image to obtain a second image similarity value; It should be noted that the relationship between the car area, rated load and number of passengers of conventional elevators in the art can be estimated. For example, for a passenger elevator with a rated load of 800kg, the maximum car area is 2.00m². According to this standard, it is assumed that the weight of one person is 75kg, the number of passengers that can be carried is 10, and the area occupied by one person standing is about 0.2m². When in an overloaded state, the image similarity between the current car image and the preset reference car image can be calculated based on pixel comparison to obtain the second image similarity value F K , the F K The value can be estimated as the remaining loading area S1 of the car at this time is 2*F K .

[0038] Step 2: When the second image similarity value is less than the second preset similarity threshold, by adjusting the optimization formula X i =A*X i , in order to optimize and adjust the rope head deformation overload value, and send out early warning signals to the monitoring platform and / or maintenance platform, where X i is the rope head deformation overload value, A is a constant, and 0<A<1; It should be noted that when the second image similarity value is less than the second preset similarity threshold, it means that there are still 2*F K The loading area is large, but it has been overloaded. At this time, abnormal detection or misdetection may occur. In order to ensure the safe operation of the current elevator, the rope head deformation overload value can be adaptively adjusted, that is, by adjusting the optimization formula X i =A*X i , in order to optimize and adjust the rope head deformation overload value, so that the current rope head deformation distance value is greater than the preset rope head deformation overload value. At this time, the elevator is in a non-overload state, and the elevator can continue to run. There is no need to implement elevator overload alarm measures and stop operation measures, so as to avoid unnecessary disturbance to passengers and affect passengers' travel; at the same time, an early warning signal can be sent to the monitoring platform and / or maintenance platform in time, and the monitoring personnel and / or maintenance personnel can be notified in time to conduct verification and processing, such as checking the car loading situation and confirming whether the car overload value is appropriate. If it is not appropriate, arrange to manually adjust the rope head deformation overload value. If it is appropriate, the motor continues to run safely.

[0039] Preferably, the A value is 0.99, but is not limited thereto.

[0040] Preferably, the second preset similarity threshold is preferably 0.5, but is not limited thereto. K When it is less than 0.5, it means that there is still 1m² of loading area left in the car, but it is overloaded at this time, and this abnormal situation needs to be checked and handled.

[0041] Step 3: When the second image similarity value is less than or equal to the third preset similarity threshold and greater than or equal to the second preset similarity threshold, the rope head deformation overload value remains unchanged, and an alarm signal is sent to the monitoring platform and / or maintenance platform; It should be noted that when the second image similarity value is less than or equal to the third preset similarity threshold and greater than or equal to the second preset similarity threshold, it means that the elevator may be overloaded. The elevator will stop running and issue an overload alarm until the passengers reduce the number of passengers on their own. At the same time, an alarm signal will be promptly sent to the monitoring platform and / or maintenance platform to promptly notify the monitoring personnel and / or maintenance personnel to confirm whether it is necessary to adjust the benchmark parameters, that is, the rope head deformation overload value. If necessary, the parameter value will be manually adjusted, otherwise no processing is required.

[0042] Preferably, the third preset similarity threshold is preferably 0.8, but is not limited thereto.

[0043] Step 4: When the second image similarity value is greater than a third preset similarity threshold, the rope head deformation overload value remains unchanged.

[0044] It should be noted that when the similarity value of the second image is greater than the third preset similarity threshold, it means that the elevator is in a normal overload state. At this time, the elevator will stop running and issue an overload alarm until the passengers reduce the number of passengers by themselves. At this time, the rope head deformation overload value remains unchanged.

[0045] like Figure 2 As shown, the present invention also provides an elevator overload detection and adjustment system, comprising: The first acquisition module 1 is used to obtain the current rope head deformation distance value collected by the distance measuring sensor in real time; It should be noted that the distance sensor is set at one end of the elevator car rope head structure. The distance sensor is used to detect the deformation distance between one end and the other end of the rope head structure to determine the loading condition of the car; the smaller the current rope head deformation distance value is, the greater the weight of the car. By using a distance sensor to replace the traditional contact overload detection switch (such as a micro switch), it has the advantages of convenient detection operation, high detection accuracy and low installation cost.

[0046] Preferably, in other embodiments, the distance measuring sensor may also be arranged on the rope head structure of the car bottom.

[0047] Preferably, the distance measuring sensor may be an infrared distance measuring sensor or a laser distance measuring sensor, but is not limited thereto.

[0048] The second acquisition module 2 is used to acquire the current car image captured by the image sensor inside the car in real time and perform image preprocessing; It should be noted that the image sensor disposed in the car can collect images of the interior of the car in real time, and the loading status of the car can be analyzed and determined based on the current car image. The image sensor is preferably a camera device having the image sensor.

[0049] Specifically, Figure 3 As shown, the second acquisition module 2 includes: The preprocessing unit 21 is used to perform image binarization processing on the collected current car image to obtain the preprocessed current car image.

[0050] It should be noted that image binarization is performed on each collected image to obtain a binary image, which can reduce the amount of data processing and highlight important features of the image.

[0051] A state determination module 3, used to determine the current operating state of the elevator according to the current rope head deformation distance value and a preset operating state rule; Specifically, Figure 4 As shown, the state determination module 3 includes: The state processing unit 31 is used to determine whether the current rope head deformation distance value is less than or equal to a preset rope head deformation overload value. If the answer is yes, it means the elevator is currently overloaded. If the judgment is no, it is determined whether there is no call signal within the preset time. If the judgment is yes, it indicates that the elevator is currently in an unloaded state.

[0052] It should be noted that when the current rope head deformation distance value obtained in real time is less than or equal to the preset rope head deformation overload value, it means that the elevator is currently in an overloaded state and needs to be overloaded; otherwise, it means that the elevator is currently in a non-overloaded state. In this state, it is determined whether there is a call signal within the preset time. If there is no call signal, it means that the elevator is currently in an unloaded state, and the benchmark parameter correction processing of the unloaded state can be performed.

[0053] Among them, the preset time may preferably be 30 minutes, 1 hour, 2 hours, 3 hours or 4 hours, etc., without too many restrictions here.

[0054] Preferably, the preset time may also be a detection time period of one month, half a month, or one day of a week, such as a time period in the early morning when there are few people to perform no-load state detection and benchmark parameter adjustment.

[0055] The first state execution module 4 is used for, if the current running state of the elevator is an unloaded state, performing an image benchmark comparison between the preprocessed current car image and a preset benchmark car image to update the benchmark car image; Specifically, Figure 5 As shown, the first state execution module 4 includes: A first state calculation unit 41 is used to calculate the image similarity between the current car image and a preset reference car image to obtain a first image similarity value; It should be noted that the image similarity between the current car image and the preset reference car image is calculated based on pixel comparison to obtain a first image similarity value F. The first image similarity value F can be used to measure the car loading condition. The closer the F value is to 1, the higher the similarity, that is, it is closer to an empty condition. The closer the F value is to 0, the lower the similarity, that is, it is closer to an overloaded condition.

[0056] The preset reference car image is an original image of the floor in the car collected by the image sensor when the elevator is unloaded and the illumination is the same, and the image is used as the reference car image after image preprocessing.

[0057] The first state processing unit 42 is used to determine whether the first image similarity value is greater than a first preset similarity threshold. If it is determined to be yes, the reference car image remains unchanged. If it is determined to be no, an image comparison and verification process is performed.

[0058] It should be noted that when the first image similarity value is greater than the first preset similarity threshold, it means that the current car image is similar to the reference car image. At this time, the reference car image does not need to be updated or replaced and can remain unchanged; when the first image similarity value is less than or equal to the first preset similarity threshold, image comparison and verification processing is performed.

[0059] Among them, Figure 6 As shown, the first state processing unit 42 includes: An acquisition subunit 421 is used to reacquire the current car image and perform image preprocessing; A calculation subunit 422, configured to calculate the image similarity between the current car image and the reference car image; The image processing subunit 423 is used to determine whether the new first image similarity value is less than or equal to a first preset similarity threshold. If so, the current car image is updated to a new reference car image. If not, the reference car image remains unchanged.

[0060] It should be noted that when performing image comparison and verification processing, the current car image is reacquired and image preprocessing is performed to obtain a new current car image; the image similarity between the current car image and the preset reference car image is calculated based on pixel comparison to obtain a new first image similarity value; when the first image similarity value is still greater than or equal to the first preset similarity threshold, the new current car image is updated to a new reference car image, otherwise the reference car image remains unchanged. The above-mentioned method can avoid large errors in the calculated image similarity value due to changes in the interior of the car during use, thereby affecting the determination of the car device status and reducing the detection accuracy. Among them, changes in the interior of the car include changes in the illumination of the lights in the car or changes in the objects or floor patterns inside the car.

[0061] Preferably, the first preset similarity threshold is preferably 0.9, but is not limited thereto.

[0062] Furthermore, if the current running state of the elevator is an unloaded state, the first state execution module 4 can also determine whether the current rope head deformation distance value is less than the preset rope head deformation unloaded value. If it is determined to be yes, the current rope head deformation distance value is updated to a new rope head deformation unloaded value to adapt to the unloaded changes of the car, such as a large change in the weight of the decoration on the elevator floor; otherwise, the rope head deformation unloaded value remains unchanged, and the elevator is in an overall unloaded state. The above-mentioned rope head deformation unloaded value detection and correction processing can facilitate maintenance personnel or monitoring personnel to clearly know the unloaded changes of the elevator, thereby facilitating elevator monitoring and management.

[0063] The second state execution module 5 is used to perform overload adjustment optimization work according to the pre-processed current car image and detection adjustment rules if the current operating state of the elevator is an overload state.

[0064] Specifically, Figure 7 As shown, the second state execution module 5 includes: A second state calculation unit 51 is used to calculate the image similarity between the current car image and a preset reference car image to obtain a second image similarity value; It should be noted that the relationship between the car area, rated load and number of passengers of conventional elevators in the art can be estimated. For example, for a passenger elevator with a rated load of 800kg, the maximum car area is 2.00m². According to this standard, it is assumed that the weight of one person is 75kg, the number of passengers that can be carried is 10, and the area occupied by one person standing is about 0.2m². When in an overloaded state, the image similarity between the current car image and the preset reference car image can be calculated based on pixel comparison to obtain the second image similarity value F K , the F K The value can be estimated as the remaining loading area S1 of the car at this time is 2*FK .

[0065] The first processing unit 52 is configured to adjust the optimization formula X when the second image similarity value is less than a second preset similarity threshold. i =A*X i , in order to optimize and adjust the rope head deformation overload value, and send out early warning signals to the monitoring platform and / or maintenance platform, where X i is the rope head deformation overload value, A is a constant, and 0<A<1; It should be noted that when the second image similarity value is less than the second preset similarity threshold, it means that there are still 2*F K The loading area is large, but it has been overloaded. At this time, abnormal detection or misdetection may occur. In order to ensure the safe operation of the current elevator, the rope head deformation overload value can be adaptively adjusted, that is, by adjusting the optimization formula X i =A*X i , in order to optimize and adjust the rope head deformation overload value, so that the current rope head deformation distance value is greater than the preset rope head deformation overload value. At this time, the elevator is in a non-overload state, and the elevator can continue to run. There is no need to implement elevator overload alarm measures and stop operation measures, so as to avoid unnecessary disturbance to passengers and affect passengers' travel; at the same time, an early warning signal can be sent to the monitoring platform and / or maintenance platform in time, and the monitoring personnel and / or maintenance personnel can be notified in time to conduct verification and processing, such as checking the car loading situation and confirming whether the car overload value is appropriate. If it is not appropriate, arrange to manually adjust the rope head deformation overload value. If it is appropriate, the motor continues to run safely.

[0066] Preferably, the A value is 0.99, but is not limited thereto.

[0067] Preferably, the second preset similarity threshold is preferably 0.5, but is not limited thereto. K When it is less than 0.5, it means that there is still 1m² of loading area left in the car, but it is overloaded at this time, and this abnormal situation needs to be checked and handled.

[0068] A second processing unit 53 is configured to keep the rope head deformation overload value unchanged and send an alarm signal to a monitoring platform and / or a maintenance platform when the second image similarity value is less than or equal to a third preset similarity threshold and greater than or equal to a second preset similarity threshold; It should be noted that when the second image similarity value is less than or equal to the third preset similarity threshold and greater than or equal to the second preset similarity threshold, it means that the elevator may be overloaded. The elevator will stop running and issue an overload alarm until the passengers reduce the number of passengers on their own. At the same time, an alarm signal will be promptly sent to the monitoring platform and / or maintenance platform to promptly notify the monitoring personnel and / or maintenance personnel to confirm whether it is necessary to adjust the benchmark parameters, that is, the rope head deformation overload value. If necessary, the parameter value will be manually adjusted, otherwise no processing is required.

[0069] Preferably, the third preset similarity threshold is preferably 0.8, but is not limited thereto.

[0070] The third processing unit 54 is configured to keep the rope head deformation overload value unchanged when the second image similarity value is greater than a third preset similarity threshold.

[0071] It should be noted that when the similarity value of the second image is greater than the third preset similarity threshold, it means that the elevator is in a normal overload state. At this time, the elevator will stop running and issue an overload alarm until the passengers reduce the number of passengers by themselves. At this time, the rope head deformation overload value remains unchanged.

[0072] Correspondingly, the present invention further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described above when executing the computer program.

[0073] Accordingly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0074] The implementation of the present invention has the following beneficial effects: In summary, the present invention adopts a distance measuring sensor to replace the traditional contact overload detection switch, which has high detection accuracy and low installation cost. The current rope head deformation distance value and preset operating status rules collected by the distance measuring sensor can automatically detect and determine the current operating status of the elevator. According to different elevator operating states, corresponding detection and adjustment work can be performed to improve the stability of the elevator overload protection work, thereby ensuring the safe operation of the elevator and protecting the personal safety of passengers.

[0075] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An elevator overload detection and adjustment method, characterized in that: include: Obtain the current rope head deformation distance value collected by the distance measuring sensor in real time; The real-time image sensor collects the current car image inside the car and performs image preprocessing; Determine the current operating state of the elevator according to the current rope deformation distance value and the preset operating state rule; If the current running state of the elevator is an unloaded state, an image benchmark comparison is performed based on the preprocessed current car image and a preset benchmark car image to update the benchmark car image; If the current running state of the elevator is an overload state, overload adjustment optimization work is performed according to the preprocessed current car image and detection adjustment rules.

2. The elevator overload detection and adjustment method according to claim 1, characterized in that: The step of determining the current running state of the elevator according to the current rope head deformation distance value and the preset running state rule comprises: It is determined whether the current rope head deformation distance value is less than or equal to the preset rope head deformation overload value. If it is determined to be yes, it indicates that the elevator is currently in an overload state. If the judgment is no, it is determined whether there is no call signal within the preset time. If the judgment is yes, it indicates that the elevator is currently in an unloaded state.

3. The elevator overload detection and adjustment method according to claim 1, characterized in that: The step of performing image benchmark comparison between the preprocessed current car image and a preset benchmark car image to update the benchmark car image comprises: Calculating the image similarity between the current car image and a preset reference car image to obtain a first image similarity value; It is determined whether the first image similarity value is greater than a first preset similarity threshold value. If it is determined to be yes, the reference car image remains unchanged. If it is determined to be no, an image comparison and verification process is performed.

4. The elevator overload detection and adjustment method according to claim 3 is characterized in that: The steps of image comparison and verification processing include: Reacquire the current car image and perform image preprocessing; Calculating the image similarity between the current car image and the reference car image; It is determined whether the new similarity value of the first image is less than or equal to a first preset similarity threshold value. If it is determined to be yes, the current car image is updated to a new reference car image. If it is determined to be no, the reference car image remains unchanged.

5. The elevator overload detection and adjustment method according to claim 1, characterized in that: The step of performing overload adjustment optimization according to the pre-processed current car image and detection adjustment rules comprises: Calculating the image similarity between the current car image and a preset reference car image to obtain a second image similarity value; When the second image similarity value is less than the second preset similarity threshold, by adjusting the optimization formula X i =A*X i , in order to optimize and adjust the rope head deformation overload value, and send out early warning signals to the monitoring platform and / or maintenance platform, where X i is the rope head deformation overload value, A is a constant, and 0<A<1; When the second image similarity value is less than or equal to the third preset similarity threshold and greater than or equal to the second preset similarity threshold, the rope head deformation overload value remains unchanged, and an alarm signal is sent to the monitoring platform and / or maintenance platform; When the second image similarity value is greater than a third preset similarity threshold, the rope head deformation overload value remains unchanged.

6. The elevator overload detection and adjustment method according to claim 1, characterized in that: The data preprocessing step includes: The collected current car image is subjected to image binarization processing to obtain the pre-processed current car image.

7. The elevator overload detection and adjustment method according to claim 1 or 2, characterized in that: If the current running state of the elevator is a no-load state, it is determined whether the current rope head deformation distance value is less than a preset rope head deformation no-load value. If it is determined to be yes, the current rope head deformation distance value is updated to a new rope head deformation no-load value.

8. An elevator overload detection and adjustment system, characterized in that: include: The first acquisition module is used to obtain the current rope head deformation distance value collected by the distance measuring sensor in real time; The second acquisition module is used to acquire the current car image captured by the image sensor inside the car in real time and perform image preprocessing; A state determination module, used to determine the current operating state of the elevator according to the current rope head deformation distance value and a preset operating state rule; A first state execution module is used for, if the current running state of the elevator is an unloaded state, performing an image benchmark comparison between the preprocessed current car image and a preset benchmark car image to update the benchmark car image; The second state execution module is used to perform overload adjustment optimization work according to the pre-processed current car image and detection adjustment rules if the current operating state of the elevator is an overload state.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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