State detection method and device of weighing equipment, storage medium and electronic equipment

Abstract

The invention discloses a state detection method and device of weighing equipment, a storage medium and electronic equipment, and the method comprises the steps: obtaining the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing equipment in a group of weighing equipment; normal distribution fitting is carried out based on a group of weight relative errors corresponding to each weighing equipment pair in the plurality of weighing equipment pairs, so that a target standard deviation corresponding to each weighing equipment pair can be obtained; each weight relative error corresponding to each weighing equipment pair is a ratio of a difference value between the vehicle weights of the same target vehicle detected by two weighing equipment in each weighing equipment pair to the vehicle weight of the same target vehicle detected by at least one weighing equipment; and determining a standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detecting the device state of each weighing device based on the determined standard deviation corresponding to each weighing device.

Description

Technical Field

[0001] The present application relates to the technical field of weight measurement. Specifically, it relates to a method and device for detecting the state of a weighing device, a storage medium, and an electronic device. Background Art

[0002] Currently, dynamic weighing technology can be applied to scenarios such as overloading control at entrances, detection at fixed overloading control stations, source supervision, and non-site law enforcement. The key device among them is the weighing device for weighing (for example, a dynamic truck scale).

[0003] The weighing device needs to be periodically calibrated. In related technologies, the standard deviation measured by the weighing device is calculated based on the difference between the weights of a group of vehicles measured by the weighing device and the actual weights of a group of vehicles, and then the state of the weighing device is determined. However, in actual application processes, firstly, the calibration usually has a certain cycle and the calibration process cannot be carried out in real time. When there are deviations in the weighing device, they are often not discovered in time. Secondly, a specific group of vehicles is usually used during calibration, and it may not be possible to evaluate whether all vehicles are accurate. However, in actual use, it is often impossible to accurately obtain the actual weights of a group of vehicles, resulting in the inability to detect the state of the weighing device through the standard deviation measured by the weighing device.

[0004] It can be seen that the method for detecting the state of a weighing device in related technologies has the technical problem of poor accuracy in detecting the device state. Summary of the Invention

[0005] Embodiments of the present application provide a method and device for detecting the state of a weighing device, a storage medium, and an electronic device, so as to at least solve the technical problem of poor accuracy in detecting the state of a weighing device in related technologies.

[0006] According to one aspect of the embodiments of the present application, there is provided a method for detecting the state of a weighing device, including: obtaining the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing device in a group of weighing devices; performing a normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair among a plurality of weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair, where each weighing device pair includes two different weighing devices in the group of weighing devices, the plurality of weighing device pairs includes the group of weighing devices, and each weight relative error in the set of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio of the difference to the vehicle weight of the same target vehicle detected by at least one of the two weighing devices in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair; determining the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detecting the device state of each weighing device based on the determined standard deviation corresponding to each weighing device.

[0007] Another aspect of the embodiments of the present application provides a device for detecting the state of a weighing device, including: an obtaining unit configured to obtain the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing device in a group of weighing devices; a fitting unit configured to perform a normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair among a plurality of weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair, where each weighing device pair includes two different weighing devices in the group of weighing devices, the plurality of weighing device pairs includes the group of weighing devices, and each weight relative error in the set of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio of the difference to the vehicle weight of the same target vehicle detected by at least one of the two weighing devices in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair; an execution unit configured to determine the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detect the device state of each weighing device based on the determined standard deviation corresponding to each weighing device.

[0008] As an alternative solution, the fitting unit includes: an execution module, configured to perform the following normal distribution fitting operation on each weighing device pair as the current weighing device pair to obtain a target standard deviation corresponding to each weighing device pair, where the two weighing devices of the current weighing device pair are a first weighing device and a second weighing device respectively: determining a first weight relative error corresponding to each target vehicle, where the first weight relative error corresponding to each target vehicle is the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the first weighing device, and the weight difference corresponding to each target vehicle is the difference between the vehicle weight of each target vehicle detected by the first weighing device and the vehicle weight of the same target vehicle detected by the second weighing device; performing a normal distribution fitting on the first weight relative error corresponding to each target vehicle to obtain a first standard deviation corresponding to the current weighing device pair, where the target standard deviation corresponding to the current weighing device pair includes the first standard deviation corresponding to the current weighing device pair.

[0009] As an alternative solution, the execution module is further configured to, when the total number of weighing device pairs that the set of weighing devices can form is less than or equal to the total number of weighing devices included in the set of weighing devices, for each target weighing device pair in at least one target weighing device pair among the multiple weighing device pairs, determine a second weight relative error corresponding to each target vehicle, where the second weight relative error corresponding to each target vehicle is the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the second weighing device; performing a normal distribution fitting on the second weight relative error corresponding to each target vehicle to obtain a second standard deviation corresponding to the current weighing device pair, where the target standard deviation corresponding to the current weighing device pair further includes the second standard deviation corresponding to the current weighing device pair.

[0010] As an alternative solution, the device further includes: a selection unit, configured to, before performing a normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair among multiple weighing device pairs, when the total number of weighing device pairs that the set of weighing devices can form is greater than the total number of weighing devices included in the set of weighing devices, select a target number of weighing device pairs from the weighing device pairs that the set of weighing devices can form to obtain the set of weighing device pairs, where the target number is greater than or equal to the total number of weighing devices included in the set of weighing devices.

[0011] As an alternative, the execution unit includes: a solving module, configured to solve an overdetermined system of equations using the least squares method to obtain a standard deviation corresponding to each weighing device, where one side of each equation in the overdetermined system of equations is the square of a target standard deviation corresponding to one weighing device pair among the multiple weighing device pairs, and the other side is the sum of the squares of the standard deviations corresponding to the two weighing devices included in the one weighing device pair.

[0012] As an alternative, the execution unit includes: a first determination module, configured to determine that a first weighing device is in an abnormal state when there is a first weighing device in the group of weighing devices whose corresponding standard deviation is greater than or equal to a preset standard deviation threshold; a second determination module, configured to determine that a second weighing device is in a normal state when there is a second weighing device in the group of weighing devices whose corresponding standard deviation is less than the preset standard deviation threshold.

[0013] As an alternative, the acquisition unit includes: a matching module, configured to match the vehicle weights of historical vehicles detected by each weighing device based on a set of preset parameters to obtain the vehicle weights of each target vehicle detected by each weighing device, where the set of preset parameters includes at least one of the following: license plate number, vehicle passing time, vehicle passing speed, distance between different weighing devices, driving direction, speed limit information of the road between different weighing devices, and each target vehicle is a historical vehicle for which the group of weighing devices have all detected matching vehicle weights.

[0014] According to another aspect of the embodiments of the present application, there is provided a computer-readable storage medium, where the computer-readable storage medium includes a stored program, and when the program runs, it executes the steps in any one of the above method embodiments.

[0015] According to another aspect of the embodiments of the present application, there is provided an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to execute the steps in any one of the above method embodiments through the computer program.

[0016] In an embodiment of the present application, the vehicle weight of each target vehicle in a set of target vehicles detected by each weighing device in a set of weighing devices is obtained; a normal distribution fitting is performed based on a set of weight relative errors corresponding to each pair of weighing devices among multiple pairs of weighing devices to obtain a target standard deviation corresponding to each pair of weighing devices, where each pair of weighing devices includes two different weighing devices in the set of weighing devices, the multiple pairs of weighing devices include the set of weighing devices, and each weight relative error in the set of weight relative errors corresponding to each pair of weighing devices is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each pair of weighing devices, the ratio of the difference to the vehicle weight of the same target vehicle detected by at least one of the weighing devices in each pair of weighing devices, and the square of the target standard deviation corresponding to each pair of weighing devices is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each pair of weighing devices; a standard deviation corresponding to each weighing device is determined based on the target standard deviation corresponding to each pair of weighing devices, and the device state of each weighing device is detected based on the determined standard deviation corresponding to each weighing device; since the actual weight of the target vehicle is not involved, the solution of this embodiment can directly determine the standard deviation corresponding to each weighing device, and then determine the state of each weighing device in combination with the standard deviation, thereby solving the technical problem of poor accuracy in detecting the device state in the state detection method of weighing devices in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application.

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 is a schematic diagram of an optional state detection system for weighing devices according to an embodiment of the present application;

[0020] Figure 2 is a schematic flowchart of an optional state detection method for weighing devices according to an embodiment of the present application;

[0021] Figure 3 is a schematic diagram of an optional state detection method for weighing devices according to an embodiment of the present application;

[0022] Figure 4 is a schematic diagram of another optional state detection method for weighing devices according to an embodiment of the present application;

[0023] Figure 5 It is a schematic diagram of another optional method for detecting the state of a weighing device according to an embodiment of the present application;

[0024] Figure 6 It is a schematic diagram of another optional method for detecting the state of a weighing device according to an embodiment of the present application;

[0025] Figure 7 It is a block diagram of the structure of an optional device for detecting the state of a weighing device according to an embodiment of the present application;

[0026] Figure 8 It is a block diagram of the computer system of an optional electronic device according to an embodiment of the present application. Detailed implementation manners

[0027] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] According to one aspect of the embodiments of the present application, a method for detecting the state of a weighing device is provided. Optionally, in this embodiment, the above method for detecting the state of a weighing device can be applied to, for example, Figure 1 the hardware environment shown in the figure including a weighing device 102 and a data processor 104. As Figure 1As shown, the data processor 104 is connected to the weighing device 102 via a network and can be used to detect the device status of the weighing device based on the vehicle data detected by the weighing device 102. A data storage component (the data can be stored in a database) can be set on or independent of the data processor 104 to provide data storage services for the data processor 104. Here, both the weighing device 102 and the data processor 104 can belong to the status detection system of the weighing device.

[0030] The above network can include but is not limited to at least one of the following: wired network, wireless network. The above wired network can include but is not limited to at least one of the following: wide area network, metropolitan area network, local area network. The above wireless network can include but is not limited to at least one of the following: WIFI (Wireless Fidelity), Bluetooth. In addition to being connected via a network, the weighing device 102 and the data processor 104 can also be connected via a network cable or a serial port. The weighing device 102 can be a dynamic vehicle scale, a column type weighing sensor, a narrow strip type weighing sensor, or a combined weighing sensor, etc.

[0031] The above weighing device 102 can be a weighing device applying dynamic weighing technology. Dynamic weighing technology is now widely used in entrance overloading control, fixed overloading control station detection, source supervision, and non-site law enforcement. Taking the dynamic vehicle scale as an example, the dynamic vehicle scale is a key weighing device. The following takes the weighing device as a dynamic vehicle scale as an example for illustration. In the related technology, the dynamic vehicle scale can only be used after passing the metrological verification, and the period of metrological verification is generally half a year or one year. There is no good monitoring method to judge the use status of the dynamic vehicle scale during two adjacent verification periods. Especially at present, the number of unattended overloading control stations is increasing continuously, and there is no effective real-time monitoring means, which will lead to untimely discovery and handling of problems, resulting in inaccurate vehicle weighing.

[0032] Although the dynamic vehicle scale has regular metrological verification, there is no method to automatically and timely discover problems during the verification period. In the related technology, the standard deviation measured by the weighing device is calculated based on the difference between the weight of a group of vehicles measured by the weighing device and the actual weight of a group of vehicles, and then the status of the weighing device is determined; however, in the actual application process, it is often impossible to accurately obtain the actual weight of a group of vehicles, resulting in the inability to detect the status of the weighing device through the standard deviation measured by the weighing device.

[0033] To at least partially solve the above technical problems, in this embodiment, normal distribution fitting is respectively performed on the relative errors of the weights of the same vehicle detected by different weighing devices, and based on the fact that the square of the standard deviation measured by the weighing device is equal to the sum of the squares of the standard deviations measured by individual weighing devices, the standard deviation measured by each weighing device is solved, so that the state of the weighing device can be detected by the standard deviation measured by the weighing device. When a problem occurs with the weighing device, real-time and accurate warnings can be given to abnormal devices, so as to improve the equipment maintenance efficiency and ensure the continuous and stable operation of the weighing system.

[0034] The method for detecting the state of the weighing device according to the embodiment of the present application can be executed by the data processor 104, or can be jointly executed by the data processor 104 and the weighing device 102. Taking the execution of the method for detecting the state of the weighing device in this embodiment by the data processor 104 as an example, Figure 2 It is a schematic flowchart of an optional method for detecting the state of a weighing device according to an embodiment of the present application, as Figure 2 shown. The process of this method can include the following steps:

[0035] Step S202, obtain the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing device in a group of weighing devices.

[0036] Based on the positional relationship between the weighing devices, a group of weighing devices can be selected. Here, each weighing device in a group of weighing devices can be located at different speed measurement sites. For example, for 4 speed measurement sites, each site is equipped with a weighing device, and the weighing device can be a dynamic vehicle scale. These 4 weighing devices together form a group of weighing devices. The selection conditions for a group of weighing devices can be based on the distance between different weighing devices, the order of the weighing devices determined based on the driving direction, etc. The selected group of weighing devices can detect the vehicle weight of the same vehicle, or the probability of detecting the vehicle weight of the same vehicle is relatively high. A group of weighing devices can be selected manually or automatically based on an algorithm, and this embodiment does not limit this.

[0037] To determine the device status of each weighing device, the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing device can be obtained. A target vehicle refers to a vehicle that passes through all the weighing devices in a group of weighing devices (the time for passing through adjacent weighing devices conforms to the time constraint, that is, it is consistent with the time difference determined based on information such as the distance between adjacent weighing devices and the speed limit of the vehicle). The time of the vehicle weight of each target vehicle detected by each weighing device can be within the target time period, and the target time period can be between the times of two periodic detections. The way to obtain the vehicle weight of each target vehicle detected by each weighing device can be: first, based on vehicle information (such as at least part of information such as license plate, detection time, vehicle contour, vehicle weight, etc.) for vehicle matching to determine a group of target vehicles, and then determine the vehicle weight of each target vehicle detected by each weighing device respectively.

[0038] Step S204: Perform normal distribution fitting based on a group of weight relative errors corresponding to each weighing device pair in multiple weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair. Each weighing device pair includes two different weighing devices in a group of weighing devices, and multiple weighing device pairs include a group of weighing devices. Each weight relative error in the group of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio of the difference to the vehicle weight of the same target vehicle detected by at least one of the weighing devices in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair.

[0039] For a set of weighing devices, two weighing devices can form a weighing device pair, and each weighing device pair contains two different weighing devices from the set of weighing devices. All the weighing device pairs allowed by the set of weighing devices can be determined as multiple weighing device pairs, or some of them can be selected and determined as multiple weighing device pairs. The multiple weighing device pairs can cover all the weighing devices in the set of weighing devices. For each weighing device pair, a normal distribution fitting can be performed based on a set of weight relative errors corresponding to each weighing device pair to obtain the target standard deviation corresponding to each weighing device pair. Each weight relative error corresponding to each weighing device pair is the ratio of the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair to the vehicle weight of the same target vehicle detected by at least one of the weighing devices in each weighing device pair. Here, the ratio of the difference between the vehicle weights of the same vehicle detected by the two weighing devices to the vehicle weight of this vehicle detected by any one of the weighing devices conforms to the normal distribution. Therefore, a normal distribution fitting can be performed on a set of weight relative errors corresponding to each weighing device pair to fit the required normal distribution curve, thereby obtaining the corresponding standard deviation.

[0040] For example, as Figure 3 shown, the number of weighing devices whose device status needs to be determined is 4, namely weighing device A, weighing device B, weighing device C, and weighing device D. All the allowed weighing device pairs contain 6 pairs, namely weighing device A and weighing device B, weighing device A and weighing device C, weighing device A and weighing device D, weighing device B and weighing device C, weighing device B and weighing device D, and weighing device C and weighing device D. The target standard deviations corresponding to all the 6 weighing device pairs can be respectively fitted. Or some of the weighing device pairs can be selected (for example, 4 weighing device pairs are selected, as Figure 4 shown), and only the selected partial weighing device pairs are subjected to the normal distribution fitting operation.

[0041] Since the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair, and the multiple weighing device pairs can cover all the weighing devices in the set of weighing devices, therefore, the calculated target standard deviations corresponding to the multiple weighing device pairs are all related to the standard deviations corresponding to all the weighing devices. Therefore, the standard deviations corresponding to all the weighing devices can be estimated.

[0042] Step S206, determine the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detect the device status of each weighing device based on the determined standard deviation corresponding to each weighing device.

[0043] Based on the target standard deviation corresponding to each weighing device, the standard deviation corresponding to each weighing device can be determined. Here, determining the standard deviation corresponding to each weighing device can be achieved by solving a system of equations to calculate the standard deviation corresponding to each weighing device, or by solving an overdetermined system of equations to estimate the standard deviation corresponding to each weighing device. Here, an overdetermined system of equations refers to a system of equations where the number of equations is greater than the number of unknowns. Each of the above-mentioned weighing device pairs can correspond to an equation with two position quantities, and the number of weighing device pairs among multiple weighing device pairs is not less than the number of weighing devices included in a set of weighing devices, so that the standard deviation corresponding to each weighing device can be solved by solving the system of equations or the overdetermined system of equations.

[0044] Here, for each weighing device, the standard deviation corresponding to each weighing device can be calculated in the following way:

[0045] Let W A be the vehicle weight measured by weighing device A for the target vehicle, GVW be the true weight of the vehicle, and assume then the standard deviation of weighing device A is

[0046] The standard deviation corresponding to each weighing device can indicate the state of the weighing device. When the standard deviation corresponding to the weighing device is large, it indicates that the deviation between the vehicle weight data measured by the weighing device and the actual vehicle weight data is large. Therefore, the device state of each weighing device can be detected based on the determined standard deviation corresponding to each weighing device.

[0047] Through the embodiments provided in this application, the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing device in a group of weighing devices is obtained; based on the normal distribution fitting of a group of weight relative errors corresponding to each weighing device pair among multiple weighing device pairs, a target standard deviation corresponding to each weighing device pair is obtained, where each weighing device pair includes two different weighing devices in a group of weighing devices, multiple weighing device pairs include a group of weighing devices, and each weight relative error in the group of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio of the difference to the vehicle weight of the same target vehicle detected by at least one weighing device in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair; based on the target standard deviation corresponding to each weighing device pair, the standard deviation corresponding to each weighing device is determined, and the device state of each weighing device is detected based on the determined standard deviation corresponding to each weighing device, which solves the technical problem of poor accuracy in detecting the device state in the state detection method of weighing devices in the related art and improves the accuracy of detecting the device state of weighing devices.

[0048] As an alternative solution, based on the normal distribution fitting of a group of weight relative errors corresponding to each weighing device pair among multiple weighing device pairs, obtaining the target standard deviation corresponding to each weighing device pair includes:

[0049] S11, taking each weighing device pair as the current weighing device pair to perform the normal distribution fitting operation, and obtaining the target standard deviation corresponding to each weighing device pair.

[0050] For the current weighing device pair, the two weighing devices it includes are the first weighing device and the second weighing device respectively. When performing the normal distribution fitting operation, the normal distribution fitting can be performed based on the ratio of the weight difference of the same vehicle detected by the two weighing devices to the weight of the vehicle detected by a certain weighing device, and the obtained standard deviation can be used as a standard deviation corresponding to the current weighing device pair.

[0051] Optionally, the first relative weight error corresponding to each target vehicle may be determined first. The first relative weight error corresponding to each target vehicle is the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the first weighing device. The weight difference corresponding to each target vehicle is the difference between the vehicle weight of each target vehicle detected by the first weighing device and the vehicle weight of the same target vehicle detected by the second weighing device. Then, a normal distribution fitting is performed on the first relative weight error corresponding to each target vehicle to obtain the first standard deviation corresponding to the current weighing device pair. Here, the target standard deviation corresponding to the current weighing device pair includes the first standard deviation corresponding to the current weighing device pair. The first weighing device used to calculate the first standard deviation may be any one of the weighing devices in the current weighing device pair.

[0052] For example, when the two weighing devices included in the current weighing device pair are weighing device A and weighing device B, and the vehicle weights obtained by weighing device A and weighing device B detecting the same vehicle are W A and W B , then the first relative weight error is Performing a normal distribution fitting on the first relative weight error corresponding to each vehicle can obtain the first standard deviation σ corresponding to the current weighing device pair AB .

[0053] Through this embodiment, it is possible to obtain the target standard deviation corresponding to the current weighing device pair without the need to determine the actual weight of the target vehicle.

[0054] As an optional solution, the total number of weighing devices included in a group of weighing devices is greater than or equal to 2, and there may be various relationships between the total number of weighing device pairs allowed to be formed by a group of weighing devices (referred to as the first total number) and the total number of weighing devices included in a group of weighing devices (referred to as the second total number). The first relationship is: the first total number is greater than the second total number (for the case where the second total number is greater than or equal to 4). The second relationship is: the first total number is equal to the second total number (for the case where the second total number is greater than or equal to 3). The third relationship is: the first total number is less than the second total number (for the case where the second total number is greater than or equal to 2). For the first relationship, the first standard deviation corresponding to each weighing device pair can be directly used as the target standard deviation corresponding to each weighing device pair for subsequent processing.

[0055] For example, as Figure 5 shown, when a group of weighing devices includes weighing device A, weighing device B, and weighing device C, the allowed weighing device pairs are: weighing device A and weighing device B, weighing device A and weighing device C, weighing device B and weighing device C. Then, the total number of weighing device pairs is the same as the total number of weighing devices.

[0056] For another example, as Figure 6 shown, when a set of weighing devices includes weighing device A and weighing device B, the allowable weighing device pairs formed are: weighing device A and weighing device B, and the total number of weighing device pairs is less than the total number of weighing devices.

[0057] For the second relationship, if the standard deviation corresponding to each weighing device is determined in the aforementioned manner, the determined standard deviation corresponding to each weighing device is a specific value. Affected by data accuracy, there is likely to be a large difference between the actual standard deviation. For the third relationship, there will be a problem that the standard deviation corresponding to each weighing device cannot be determined. Therefore, for the second relationship and the third case, other methods can also be used to determine the second standard deviation corresponding to at least some of the weighing device pairs to improve the accuracy of standard deviation determination.

[0058] In this embodiment, if the total number of allowable weighing device pairs in a set of weighing devices is less than or equal to the total number of weighing devices included in a set of weighing devices, for each target weighing device pair in at least one target weighing device pair among multiple weighing device pairs, taking each target weighing device pair as the current weighing device pair to perform a normal distribution fitting operation, it further includes:

[0059] S21. Determine the second weight relative error corresponding to each target vehicle, where the second weight relative error corresponding to each target vehicle is the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the second weighing device;

[0060] S22. Perform a normal distribution fitting on the second weight relative error corresponding to each target vehicle to obtain the second standard deviation corresponding to the current weighing device pair, where the target standard deviation corresponding to the current weighing device pair further includes the second standard deviation corresponding to the current weighing device pair.

[0061] For each target weighing device pair, when performing the normal distribution fitting operation on it, the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the second weighing device can also be determined to obtain the second weight relative error corresponding to each target vehicle, and a normal distribution fitting is performed on the second weight relative error corresponding to each target vehicle to obtain the second standard deviation corresponding to the current weighing device pair. The process of determining the second standard deviation corresponding to the current weighing device pair is similar to the process of determining the first standard deviation corresponding to the current weighing device pair, except that the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the second weighing device is used. At this time, for each target weighing device pair, the determined target standard deviation includes the first standard deviation and the second standard deviation.

[0062] Here, the number of standard deviations corresponding to a set of weighing devices represents the number of equations, while the total number of weighing devices included in a set of weighing devices represents the number of unknowns. When the number of equations is less than or equal to the number of unknowns, it will lead to inability to solve or a large deviation between the solution result and the actual situation. When the number of equations is greater than the number of unknowns, by solving the overdetermined system of equations, the standard deviation corresponding to each weighing device can be evaluated, improving the accuracy of determining the standard deviation corresponding to each weighing device.

[0063] For example, when a set of weighing devices includes weighing device A, weighing device B, and weighing device C, the first standard deviation can be calculated by the above method, that is, σ AB 、σ AC 、σ BC . Since the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair, the obtained system of equations is as shown in formula (1):

[0064]

[0065] Since the number of equations is 3 and the unknowns are σ A 、σ B 、σ C , a total of 3, and the number of equations is the same as the number of unknowns, the difference between the solved standard deviation and the actual standard deviation may be relatively large. In this regard, the second standard deviation can be calculated by the above method, that is, Performing a normal distribution fitting on E BA to obtain the second standard deviation σ BA . By analogy, σ CA and σ CB can also be obtained. Combining the aforementioned σ AB 、σ AC 、σ BC , the obtained overdetermined system of equations is as shown in formula (2):

[0066]

[0067] Since the number of equations is greater than the number of unknowns at this time, this overdetermined system of equations can be solved by the least squares method to obtain the standard deviations corresponding to weighing device A, weighing device B, and weighing device C, that is, obtaining σ A 、σ B 、σ C .

[0068] Through this embodiment, determining another standard deviation corresponding to at least some of the weighing device pairs based on the vehicle weight detected by another weighing device can improve the accuracy of determining the standard deviation corresponding to the weighing device.

[0069] As an alternative, before fitting a normal distribution to a set of relative weight errors corresponding to each weighing device pair among multiple weighing device pairs, the above method further includes:

[0070] S31. When the total number of weighing device pairs allowed to be formed by a set of weighing devices is greater than the total number of weighing devices included in a set of weighing devices, select a target number of weighing device pairs from the weighing device pairs allowed to be formed by the set of weighing devices to obtain a set of weighing device pairs, where the target number is greater than or equal to the total number of weighing devices included in the set of weighing devices.

[0071] The number of standard deviations corresponding to a set of weighing device pairs represents the number of equations. To reduce the difficulty of solving the equations, if the total number of weighing device pairs allowed to be formed by a set of weighing devices is greater than the total number of weighing devices included in the set of weighing devices, at least some of the weighing device pairs can be selected as a set of weighing device pairs to perform the subsequent processing flow. The number of selected weighing device pairs is the target number, and the target number is greater than or equal to the total number of weighing devices included in the set of weighing devices.

[0072] Optionally, the target number is configured based on the total number of weighing devices included in a set of weighing devices. For example, if the total number of weighing devices included in a set of weighing devices is 5, the target number can be 8; if the total number of weighing devices included in a set of weighing devices is 6, the target number can be 9. This is only an example here, and the target number can be configured as needed and is not specifically limited herein.

[0073] Through this embodiment, for the case where the total number of weighing device pairs allowed to be formed by a set of weighing devices is greater than the total number of weighing devices included in the set of weighing devices, at least some of the weighing device pairs can be selected as a set of weighing device pairs to perform the subsequent standard deviation determination operation, which can improve the convenience of standard deviation determination.

[0074] As an alternative, determining the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair includes:

[0075] S41. Use the least squares method to solve the overdetermined equations to obtain the standard deviation corresponding to each weighing device, where one side of each equation of the overdetermined equations is the square of the target standard deviation corresponding to one of the weighing device pairs among the multiple weighing device pairs, and the other side is the sum of the squares of the standard deviations corresponding to the two weighing devices included in one weighing device pair.

[0076] In this embodiment, the standard deviation corresponding to each weighing device can be determined by solving an overdetermined system of equations. An overdetermined system of equations refers to a system of equations in which the number of equations is greater than the number of unknowns. Here, for each equation in the overdetermined system of equations, one side is the square of the target standard deviation corresponding to a weighing device pair, and the other side is the sum of the squares of the standard deviations corresponding to the two weighing devices included in a weighing device pair. There are various ways to solve the overdetermined system of equations. To improve the convenience of solving the system of equations, the least squares method can be used to solve the overdetermined system of equations to obtain the standard deviation corresponding to each weighing device.

[0077] Through this embodiment, by using the least squares method to solve the overdetermined system of equations and determining the standard deviation corresponding to each weighing device, the convenience of solving the system of equations can be improved.

[0078] As an alternative solution, based on the determined standard deviation corresponding to each weighing device, the device state of each weighing device is detected, including:

[0079] S51, in a group of weighing devices, when there is a first weighing device whose corresponding standard deviation is greater than or equal to a preset standard deviation threshold, it is determined that the first weighing device is in an abnormal state;

[0080] S52, in a group of weighing devices, when there is a second weighing device whose corresponding standard deviation is less than the preset standard deviation threshold, it is determined that the second weighing device is in a normal state.

[0081] After determining the standard deviation corresponding to each weighing device, the device state of the corresponding weighing device can be determined based on the determined standard deviation corresponding to each weighing device. If, in a group of weighing devices, there is a first weighing device whose corresponding standard deviation is greater than or equal to the preset standard deviation threshold, it means that the deviation of the vehicle weight data measured by the first weighing device from the true vehicle data is relatively large. At this time, it can be determined that the first weighing device is in an abnormal state. If, in a group of weighing devices, there is a second weighing device whose corresponding standard deviation is greater than or equal to the preset standard deviation threshold, it means that the deviation of the vehicle weight data measured by the second weighing device from the true vehicle data is relatively small. At this time, it can be determined that the second weighing device is in a normal state.

[0082] Through the embodiment provided by this application, based on the determined standard deviation corresponding to the weighing device and the corresponding standard deviation threshold to determine the device state of the weighing device, the convenience of device state detection can be improved.

[0083] As an alternative solution, obtaining the vehicle weight of each target vehicle in a group of target vehicles detected by each weighing device in a group of weighing devices includes:

[0084] S61. Match the vehicle weights of historical vehicles detected by each weighing device based on a set of preset parameters to obtain the vehicle weight of each target vehicle detected by each weighing device. Here, the set of preset parameters includes at least one of the following: license plate number, passing time, passing speed, distance between different weighing devices, driving direction, speed limit information of the road between different weighing devices. Each target vehicle is a historical vehicle for which the vehicle weight has been matched by a set of weighing devices.

[0085] In this embodiment, in order to determine the vehicle weight data used for device status determination, the vehicle weights of historical vehicles detected by each weighing device can be matched based on a set of preset parameters to obtain the vehicle weight of each target vehicle detected by each weighing device. Here, the set of preset parameters includes at least one of the following: license plate number, passing time, passing speed, distance between different weighing devices, driving direction, speed limit information of the road between different weighing devices. The method of matching the vehicle weights can be: match the vehicle weights of historical vehicles with the same set of preset parameters. If the vehicle weights match, the vehicle weight of the matched historical vehicle can be determined as the vehicle weight of a target vehicle.

[0086] Optionally, the same set of preset parameters means: the license plate numbers are the same, the passing time, passing speed (or the speed limit information of the road between different weighing devices) match the driving direction and the distance between the weighing devices. The vehicle weight match means that the weight difference between the vehicle weights is less than or equal to the set weight difference threshold. And each target vehicle is a historical vehicle for which the vehicle weight has been matched by a set of weighing devices.

[0087] Through this embodiment, by matching the vehicle weights detected by each weighing device according to a set of preset parameters, the vehicle weight of the historical vehicle used for device status determination can be selected, which can improve the accuracy of device status determination.

[0088] The following explains the state detection method of the weighing device in this embodiment with reference to optional examples. In this optional example, the weighing device can be a dynamic vehicle scale, and a set of weighing devices includes weighing device A, weighing device B, weighing device C, and weighing device D.

[0089] Taking the weighing device pair consisting of weighing device A and weighing device B as an example, the first standard deviation corresponding to the weighing device pair is calculated using formula (3):

[0090]

[0091] where, W A is the vehicle weight of the target vehicle measured by weighing device A, W Bis the weight of the target vehicle measured by the weighing device B; assuming GVW is the true weight of the vehicle, Substituting into formula (3), we get:

[0092] When E B is much less than 1, we can obtain formula (4):

[0093] E AB ≈E A -E B (4)

[0094] Since the error of the weighing device is generally not very large, formula (4) generally holds.

[0095] Based on this, the standard deviation σ AB of E AB can be expressed by formula (5).

[0096]

[0097] Here, i is the number of target vehicles included in a group of target vehicles detected by the weighing device A. Here, E A and E B are normal distribution data with a mean of 0, then formula (6) can be obtained.

[0098]

[0099] Substituting formula (6) into formula (5), formula (7) can be obtained.

[0100]

[0101] Adjusting formula (7), formula (8) can be obtained.

[0102] σ AB 2 ≈σ A 2 +σ B 2 (8)

[0103] Extending formula (8) to the case where a group of weighing devices includes weighing device A, weighing device B, weighing device C, and weighing device D, formula (9) can be obtained.

[0104]

[0105] In the system of equations of formula (9), σ AB 2 、σ BC 2 、……、σ BD2 It can be calculated through data matching among weighing device A, weighing device B, weighing device C, and weighing device D. Substituting it into the system of equations, an overdetermined system of equations can be obtained. Solving this overdetermined system of equations using the least squares method can solve for σ A 2 、σ B 2 、σ C 2 、σ D 2 , and further obtain the standard deviations of the weighing effects of the four weighing devices.

[0106] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0107] Through the description of the above implementation manners, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such an understanding, the technical solution of the embodiments of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), and includes several instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0108] According to another aspect of the embodiments of this application, a state detection device for a weighing device is further provided. This device is used to implement the state detection method of the weighing device provided in the above embodiments, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0109] Figure 7 is a structural block diagram of an optional state detection device for a weighing device according to the embodiments of this application. As Figure 7 shown, this device includes:

[0110] An acquisition unit 702, configured to acquire the vehicle weight of each target vehicle in a set of target vehicles detected by each weighing device in a set of weighing devices;

[0111] A fitting unit 704, configured to perform a normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair in a plurality of weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair, where each weighing device pair includes two different weighing devices in a set of weighing devices, the plurality of weighing device pairs includes the set of weighing devices, each weight relative error in the set of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio between the vehicle weight of the same target vehicle detected by at least one of the two weighing devices in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair;

[0112] An execution unit 706, configured to determine the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detect the device state of each weighing device based on the determined standard deviation corresponding to each weighing device.

[0113] Through the embodiments of the present application, the vehicle weight of each target vehicle in a set of target vehicles detected by each weighing device in a set of weighing devices is acquired; a normal distribution fitting is performed based on a set of weight relative errors corresponding to each weighing device pair in a plurality of weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair, where each weighing device pair includes two different weighing devices in a set of weighing devices, the plurality of weighing device pairs includes the set of weighing devices, each weight relative error in the set of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio between the vehicle weight of the same target vehicle detected by at least one of the two weighing devices in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair; the standard deviation corresponding to each weighing device is determined based on the target standard deviation corresponding to each weighing device pair, and the device state of each weighing device is detected based on the determined standard deviation corresponding to each weighing device; the technical problem that the state detection method of the weighing device in the related art has poor accuracy in device state detection is solved, and the accuracy of the state detection of the weighing device is improved.

[0114] As an optional solution, the fitting unit includes:

[0115] A fitting module, which is used to take each pair of weighing devices as the current pair of weighing devices and perform the following normal distribution fitting operations to obtain a target standard deviation corresponding to each pair of weighing devices. The two weighing devices of the current pair of weighing devices are the first weighing device and the second weighing device respectively: determine a first weight relative error corresponding to each target vehicle, where the first weight relative error corresponding to each target vehicle is the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the first weighing device, and the weight difference corresponding to each target vehicle is the difference between the vehicle weight of each target vehicle detected by the first weighing device and the vehicle weight of the same target vehicle detected by the second weighing device; perform a normal distribution fitting on the first weight relative error corresponding to each target vehicle to obtain a first standard deviation corresponding to the current pair of weighing devices, where the target standard deviation corresponding to the current pair of weighing devices includes the first standard deviation corresponding to the current pair of weighing devices.

[0116] As an optional solution, the fitting module is further used to, when the total number of pairs of weighing devices that a group of weighing devices can form is less than or equal to the total number of weighing devices included in a group of weighing devices, for each target pair of weighing devices in at least one target pair of weighing devices among multiple pairs of weighing devices, determine a second weight relative error corresponding to each target vehicle, where the second weight relative error corresponding to each target vehicle is the ratio of the weight difference corresponding to each target vehicle to the vehicle weight of each target vehicle detected by the second weighing device; perform a normal distribution fitting on the second weight relative error corresponding to each target vehicle to obtain a second standard deviation corresponding to the current pair of weighing devices, where the target standard deviation corresponding to the current pair of weighing devices further includes the second standard deviation corresponding to the current pair of weighing devices.

[0117] As an optional solution, the above device further includes:

[0118] A selection unit, which is used to, before performing a normal distribution fitting based on a group of weight relative errors corresponding to each pair of weighing devices among multiple pairs of weighing devices, when the total number of pairs of weighing devices that a group of weighing devices can form is greater than the total number of weighing devices included in a group of weighing devices, select a target number of pairs of weighing devices from the pairs of weighing devices that a group of weighing devices can form to obtain a group of pairs of weighing devices, where the target number is greater than or equal to the total number of weighing devices included in a group of weighing devices.

[0119] As an optional solution, the execution unit includes:

[0120] A solving module, configured to solve an overdetermined system of equations using the least squares method to obtain a standard deviation corresponding to each weighing device, where one side of each equation in the overdetermined system of equations is the square of the target standard deviation corresponding to one weighing device pair among multiple weighing device pairs, and the other side is the sum of the squares of the standard deviations corresponding to the two weighing devices included in one weighing device pair.

[0121] As an alternative solution, the execution unit includes:

[0122] A first determination module, configured to determine that a first weighing device is in an abnormal state when there is a first weighing device in a group of weighing devices whose corresponding standard deviation is greater than or equal to a preset standard deviation threshold;

[0123] A second determination module, configured to determine that a second weighing device is in a normal state when there is a second weighing device in a group of weighing devices whose corresponding standard deviation is less than the preset standard deviation threshold.

[0124] As an alternative solution, the acquisition unit includes:

[0125] A matching module, configured to match the vehicle weights of the historical vehicles detected by each weighing device based on a set of preset parameters to obtain the vehicle weight of each target vehicle detected by each weighing device, where the set of preset parameters includes at least one of the following: license plate number, passing vehicle time, passing vehicle speed, distance between different weighing devices, driving direction, speed limit information of the road between different weighing devices, and each target vehicle is a historical vehicle for which the vehicle weights detected by a group of weighing devices are matched. It should be noted that the above-mentioned various modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: all the above modules are located in the same processor; or, the above-mentioned various modules are separately located in different processors in any combination form.

[0126] According to another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored program, and when the program runs, it executes the steps in any one of the above method embodiments.

[0127] In an exemplary embodiment, the above computer-readable storage medium may include, but is not limited to: USB flash drive, read-only memory (ROM for short), random access memory (RAM for short), mobile hard disk, magnetic disk, or optical disc, etc., various media that can store computer programs.

[0128] According to another aspect of the embodiments of the present application, there is also provided an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to execute the steps in any of the above method embodiments through the computer program.

[0129] In an exemplary embodiment, the above electronic device may further include a transmission device and an input / output device. Among them, the transmission device is connected to the above processor, and the input / output device is connected to the above processor.

[0130] Specific examples in this embodiment may refer to the examples described in the above embodiments and exemplary embodiments, and will not be repeated here.

[0131] According to one aspect of the present application, there is provided a computer program product, which includes a computer program / instructions. The computer program / instructions include program codes for executing the method shown in the flowchart. In such an embodiment, refer to Figure 8 , the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit 801, it executes various functions provided by the embodiments of the present application. The above serial numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0132] Refer to Figure 8 , Figure 8 is a structural block diagram of a computer system of an optional electronic device according to an embodiment of the present application.

[0133] Figure 8 Schematically shows a structural block diagram of a computer system of an electronic device for implementing the embodiments of the present application. As Figure 8 shown, the computer system 800 includes a central processing unit 801 (Central Processing Unit, CPU), which can execute various appropriate actions and processes according to the program stored in the read-only memory 802 (Read-Only Memory, ROM) or the program loaded from the storage part 808 into the random access memory 803 (Random Access Memory, RAM). In the random access memory 803, various programs and data required for system operation are also stored. The central processing unit 801, the read-only memory 802, and the random access memory 803 are connected to each other through a bus 804. The input / output interface 805 (Input / Output interface, that is, I / O interface) is also connected to the bus 804.

[0134] The following components are connected to the input / output interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a local area network card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output interface 805 as required. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as required so that a computer program read therefrom can be installed into the storage section 808 as required.

[0135] Specifically, according to an embodiment of the present application, the processes described in each of the method flowcharts can be implemented as computer software programs. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809, and / or installed from the removable medium 811. When the computer program is executed by the central processing unit 801, various functions defined in the system of the present application are executed.

[0136] It should be noted that Figure 8 The computer system 800 of the electronic device shown is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.

[0137] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the embodiments of the present application can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device, so that they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order than here, or they can be separately made into individual integrated circuit modules, or multiple modules or steps among them can be made into a single integrated circuit module to implement. Thus, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0138] The above are only the preferred embodiments of the present application and are not used to limit the embodiments of the present application. For those skilled in the art, the embodiments of the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the principle of the embodiments of the present application shall be included in the protection scope of the embodiments of the present application.

Claims

1. A method for detecting the state of a weighing device, characterized in that, Including: Obtaining the vehicle weight of each target vehicle in a set of target vehicles detected by each weighing device in a set of weighing devices; Performing normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair among multiple weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair, where each weighing device pair includes two different weighing devices in the set of weighing devices, the multiple weighing device pairs include the set of weighing devices, and each weight relative error in the set of weight relative errors corresponding to each weighing device pair is the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair, the ratio between the difference and the vehicle weight of the same target vehicle detected by at least one of the weighing devices in each weighing device pair, and the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair; Determining the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detecting the device state of each weighing device based on the determined standard deviation corresponding to each weighing device.

2. The method according to claim 1, characterized in that, The performing normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair among multiple weighing device pairs to obtain a target standard deviation corresponding to each weighing device pair includes: Taking each weighing device pair as the current weighing device pair to perform the following normal distribution fitting operation to obtain the target standard deviation corresponding to each weighing device pair, where the two weighing devices of the current weighing device pair are the first weighing device and the second weighing device respectively: Determining a first weight relative error corresponding to each target vehicle, where the first weight relative error corresponding to each target vehicle is the ratio between the weight difference corresponding to each target vehicle and the vehicle weight of each target vehicle detected by the first weighing device, and the weight difference corresponding to each target vehicle is the difference between the vehicle weight of each target vehicle detected by the first weighing device and the vehicle weight of the same target vehicle detected by the second weighing device; Performing normal distribution fitting on the first weight relative error corresponding to each target vehicle to obtain a first standard deviation corresponding to the current weighing device pair, where the target standard deviation corresponding to the current weighing device pair includes the first standard deviation corresponding to the current weighing device pair.

3. The method according to claim 2, characterized in that In the case where the total number of weighing device pairs that can be formed by the set of weighing devices is less than or equal to the total number of weighing devices included in the set of weighing devices, for each target weighing device pair among at least one target weighing device pair in the multiple weighing device pairs, taking each target weighing device pair as the current weighing device pair to perform the normal distribution fitting operation further includes: Determine a second relative weight error corresponding to each of the target vehicles, where the second relative weight error corresponding to each of the target vehicles is the ratio of the weight difference corresponding to each of the target vehicles to the vehicle weight of each of the target vehicles detected by the second weighing device; Perform a normal distribution fitting on the second relative weight error corresponding to each of the target vehicles to obtain a second standard deviation corresponding to the current weighing device pair, where the target standard deviation corresponding to the current weighing device pair further includes the second standard deviation corresponding to the current weighing device pair.

4. The method according to claim 1, wherein Before performing the normal distribution fitting based on a set of relative weight errors corresponding to each weighing device pair in a plurality of weighing device pairs, the method further includes: When the total number of weighing device pairs allowed to be formed by the set of weighing devices is greater than the total number of weighing devices included in the set of weighing devices, select a target number of weighing device pairs from the weighing device pairs allowed to be formed by the set of weighing devices to obtain the set of weighing device pairs, where the target number is greater than or equal to the total number of weighing devices included in the set of weighing devices.

5. The method according to claim 1, characterized in that, The determining the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair includes: Use the least squares method to solve the overdetermined system of equations to obtain the standard deviation corresponding to each weighing device, where one side of each equation of the overdetermined system of equations is the square of the target standard deviation corresponding to one of the weighing device pairs in the plurality of weighing device pairs, and the other side is the sum of the squares of the standard deviations corresponding to the two weighing devices included in the one weighing device pair.

6. The method according to claim 2, wherein The detecting the device state of each weighing device based on the determined standard deviation corresponding to each weighing device includes: When there is a first weighing device in the set of weighing devices whose corresponding standard deviation is greater than or equal to a preset standard deviation threshold, determine that the first weighing device is in an abnormal state; When there is a second weighing device in the set of weighing devices whose corresponding standard deviation is less than the preset standard deviation threshold, determine that the second weighing device is in a normal state.

7. The method according to any one of claims 1 to 6, characterized in that The obtaining the vehicle weight of each of the target vehicles in a set of target vehicles detected by each weighing device in a set of weighing devices includes: Match the vehicle weights of the historical vehicles detected by each weighing device based on a set of preset parameters to obtain the vehicle weight of each of the target vehicles detected by each weighing device, where the set of preset parameters includes at least one of the following: license plate number, passing time, passing speed, distance between different weighing devices, driving direction, speed limit information of the road between different weighing devices, and each of the target vehicles is a historical vehicle for which the vehicle weights are detected and matched by all weighing devices in the set of weighing devices.

8. A state detection device for a weighing device, characterized in that, Includes: An obtaining unit, configured to obtain the vehicle weight of each of the target vehicles in a set of target vehicles detected by each weighing device in a set of weighing devices; A fitting unit, configured to perform normal distribution fitting based on a set of weight relative errors corresponding to each weighing device pair among multiple weighing device pairs, to obtain a target standard deviation corresponding to each weighing device pair, where each weighing device pair includes two different weighing devices in the set of weighing devices, the multiple weighing device pairs include the set of weighing devices, and each weight relative error in the set of weight relative errors corresponding to each weighing device pair is the ratio of the difference between the vehicle weights of the same target vehicle detected by the two weighing devices in each weighing device pair to the vehicle weight of the same target vehicle detected by at least one weighing device in each weighing device pair; the square of the target standard deviation corresponding to each weighing device pair is equal to the sum of the squares of the standard deviations corresponding to the two weighing devices included in each weighing device pair; An execution unit, configured to determine the standard deviation corresponding to each weighing device based on the target standard deviation corresponding to each weighing device pair, and detect the device state of each weighing device based on the determined standard deviation corresponding to each weighing device.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, where the program, when running, executes the steps of the method according to any one of claims 1 to 7.

10. An electronic device, comprising a memory and a processor, characterized in that, A computer program is stored in the memory, and the processor is configured to execute the steps of the method according to any one of claims 1 to 7 through the computer program.

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