CN114360222A - State early warning method, device, equipment and medium for rental equipment - Google Patents
State early warning method, device, equipment and medium for rental equipment Download PDFInfo
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Abstract
The embodiment of the invention discloses a method, a device, equipment and a medium for early warning the state of rental equipment. Collecting working state data of rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data; calculating at least one health work measurement index matched with the rental equipment according to the operating state description information; and dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter provides additional service to a renter of the renting equipment. The technical scheme of the embodiment of the invention provides a new technology for dynamically monitoring whether the leased equipment can work healthily or not so as to ensure that the leased equipment can provide services for a lessee efficiently, stably and effectively.
Description
Technical Field
The embodiment of the invention relates to an electric power metering technology, in particular to a state early warning method, device, equipment and medium of leasing equipment.
Background
With the strong support of the country on small and micro enterprises, particularly the manufacturing industry, small and medium-sized enterprises are well developed, and the equipment lease requirements of the small and medium-sized enterprises are more and more increased.
The equipment lease refers to that medium and heavy equipment which is temporarily unavailable for purchase by a medium and small enterprise is purchased by a lease service provider, and equipment use right is provided for an equipment renter enterprise in a form of charging rent. In the prior art, a rentable service provider manages each item of rentable equipment through a rentable equipment management platform, and an equipment renting enterprise can check information of the rentable equipment by logging in the rentable equipment management platform.
The inventor finds that the existing rental equipment management platform only carries out simple statistical analysis based on basic information of the rental equipment, mainly comprises longitude and latitude, equipment running state, equipment early warning and the like, can not effectively monitor the health working state of the rental equipment of each equipment rental enterprise, and can not ensure that the rental equipment can efficiently, stably and effectively provide services for tenants.
Disclosure of Invention
The embodiment of the invention provides a state early warning method, device, equipment and medium for leased equipment, which are used for ensuring that the leased equipment efficiently, stably and effectively provides services for a lessee.
In a first aspect, an embodiment of the present invention provides a state early warning method for rental equipment, where the method includes:
collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data;
calculating at least one health work measurement index matched with the rental equipment according to the operating state description information;
and dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter provides additional service to a renter of the renting equipment.
In a second aspect, an embodiment of the present invention further provides a state early warning apparatus for rental equipment, where the apparatus includes:
the operating state description information calculation module is used for collecting the working state data of the rental equipment in real time and calculating operating state description information matched with the rental equipment according to the working state data;
the health work measurement index calculation module is used for calculating at least one health work measurement index matched with the rental equipment according to the operating state description information;
and the early warning module is used for dynamically monitoring each health work measurement index, and providing matched early warning information for a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter can provide additional service for the renter of the renting equipment.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors implement a method for early warning of the state of rental equipment according to any embodiment of the invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a state warning method for rental equipment according to any embodiment of the present invention.
The method comprises the steps of collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data; calculating at least one health work measurement index matched with the rental equipment according to the operating state description information; the method comprises the steps of dynamically monitoring each health work measurement index, providing matched early warning information to a renter of the renting equipment when a monitoring result is determined to meet early warning conditions so as to provide a technical means for the renter to provide additional services for the renter of the renting equipment, solving the problems that the health working state of the renting equipment of each equipment renting enterprise cannot be effectively monitored and the renter cannot be efficiently, stably and effectively provided with services, and providing a new technology for dynamically monitoring whether the renter can work healthily so as to ensure that the renter can efficiently, stably and effectively provide services for the renter.
Drawings
Fig. 1 is a flowchart of a state early warning method for rental equipment according to an embodiment of the present invention;
fig. 2 is a flowchart of another method for warning status of rental equipment according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a state warning device for rental equipment according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a state warning method for rental equipment according to an embodiment of the present invention, where the method is applicable to monitoring a healthy operating state of the rental equipment, and the method can be executed by a state warning device for rental equipment, and the device can be implemented in a software and/or hardware manner. The device can be configured in a leasing equipment management platform, the leasing equipment management platform is used for uniformly managing each leasing equipment leased by a plurality of lessees in a leasing direction, and the leasing equipment management platform can simultaneously provide access channels for the leasers and the lessees so that the leasers or the lessees inquire each item of information of the leasing equipment. Correspondingly, the method specifically comprises the following steps:
s110, collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data.
The operating state data can refer to data synchronously generated by the rental equipment during the running operation, such as temperature data, amplitude data, current data and the like of the rental equipment. The start-up status description information may refer to status information of a tenant of the rental equipment performing a production job by operating the rental equipment, for example, information of a time when the tenant uses the rental equipment within one week. The start-up state description information may include at least one of: a rate of operation, a length of time of operation, and a peak time period of operation in at least one time unit. Wherein, the time unit can be day, week, month, etc.
Specifically, the working state data of the rental equipment can be collected in real time, and the matched start-up state description information is calculated according to the working state data of the rental equipment.
In an optional implementation manner of this embodiment, the collecting the operating state data of the rental equipment in real time may include: and collecting the amplitude data of the rental equipment in real time through an equipment bracelet arranged on the rental equipment, and/or collecting the current data of the rental equipment in real time through a current collecting device configured on a power grid line where the rental equipment is located.
Specifically, for a single rental device, amplitude data of the single rental device can be acquired in real time only through a device bracelet; the current data flowing through the rental equipment can be collected in real time only by a current collecting device on the power grid line; the amplitude data and the corresponding current data can be acquired.
In another optional implementation manner of this embodiment, calculating the operating status description information matched with the rental equipment according to the operating status data may include: acquiring equipment basic information of the rental equipment, and screening out a target working state identification model matched with the rental equipment from all working state identification models according to the equipment basic information; inputting the working state data into the target working state recognition model, and acquiring start-up state description information matched with the rental equipment;
the device basic information may include information such as a device brand, a device type, and a device model. The working state recognition model can be pre-trained and used for recognizing and calculating the start-up state description information of the rental equipment according to the working state data of the rental equipment, and the rental equipment corresponding to each type of equipment basic information can train one working state recognition model according to the matched working state data, so that all working state recognition models are formed. The target working state identification model can be a certain working state identification model which is screened from all the working state identification models and is matched with the equipment basic information of the rental equipment needing to calculate the operating state description information. The device basis information may be identification information of the screening target operation state recognition model.
Optionally, for the currently processed rental device of the tenant, the device basis information of the rental device may be obtained, and a target working state recognition model matched with the device basis information of the currently processed rental device is screened from all pre-trained working state recognition models corresponding to multiple rental devices by using the device basis information as an identifier; furthermore, the working state data of the rental equipment can be input into the screened target working state identification model, and the start-up state description information matched with the rental equipment is obtained.
For example, for a certain type of equipment, amplitude data of the equipment can be collected in real time through an equipment bracelet configured on the equipment, current data of the equipment can be collected in real time through a current collecting device on a power grid line where the equipment is located, and CPU temperature data of the equipment can be collected in real time through a temperature sensor configured on the equipment; and according to the model of the equipment, obtaining a working state identification model corresponding to the model, inputting the acquired amplitude data, current data and temperature data of the equipment into the working state identification model, and outputting the operating state description information of the equipment, such as the operating rate, the operating time, the operating peak time period and the like in each week.
And S120, calculating at least one health work measurement index matched with the rental equipment according to the operating state description information.
The health work measurement index may refer to a parameter for measuring whether the working state of the rental equipment is healthy, for example, parameters such as a maintenance cycle, an idle rate, and a power-limiting influence index.
At least one health work measurement index matched with the rental equipment can be calculated according to the start-up state description information obtained through the work state identification model.
In an optional implementation manner of this embodiment, calculating at least one health work measurement index matched with the rental equipment according to the operating status description information may include: acquiring a standard maintenance cycle matched with the rental equipment according to the equipment basic information of the rental equipment; and adjusting the standard maintenance cycle according to the start-up state description information and the working environment description information of the rental equipment to obtain the maintenance cycle of the rental equipment.
The standard maintenance cycle may be a maintenance cycle corresponding to the rental equipment in an ideal factory working state. Each rental device has a corresponding standard maintenance cycle. The operating environment description information may refer to information of an environment in which the rental apparatus is located when the tenant operates using the rental apparatus, for example, information of temperature and humidity. The maintenance cycle of the rental equipment can be a maintenance cycle of the rental equipment obtained by adaptively adjusting a standard maintenance cycle after judging the loss of the rental equipment according to the operating state description information and the working environment description information of the rental equipment after the renter takes the rental equipment.
Specifically, after the renter of the rented equipment obtains the standard maintenance cycle of the rented equipment according to the equipment basic information of the rented equipment, the consumed and estimated loss of the rented equipment can be further judged according to the operating state description information and the working environment description information of the rented equipment, which are obtained from the renter of the rented equipment, and the standard maintenance cycle of the rented equipment is adjusted to obtain the maintenance cycle of the rented equipment.
For example, the standard maintenance cycle of a certain rental device is 3 years, the renter of the rental device obtains the operating rate of the rental device per month of 50% and the operating duration of 264 hours according to the operating state description information and the operating environment description information used by the renter for the rental device, the average ambient temperature of the rental device per month is 35 ℃ and the average humidity is 45%, the loss and the estimated loss of the rental device can be judged, and the maintenance cycle of the rental device is adjusted to 2 and half years. Correspondingly, if the operating rate, the operating duration and other values of the rental equipment are small, and the description information value of the environment where the rental equipment is located is good, the rental equipment can be maintained according to the standard maintenance cycle.
Calculating at least one health work measurement index matched with the rental equipment according to the operating state description information, and further comprising: acquiring an industry field to which the rental equipment and/or the lessee belong, and acquiring an average work index matched with the industry field; and calculating the idle rate of the rental equipment according to the operating state description information and the average work index.
The average work index may be average operating state description information of the rental equipment in the industry field, for example, index information such as average operating rate and average operating duration. The idle rate of the rental equipment can be a ratio of the idle time of the rental equipment to the average work time of the rental equipment in the industry field relative to the average work index of the rental equipment.
Specifically, the average work index of the leased equipment in the industry field can be obtained according to the industry field of the leased equipment and/or the leaseholder of the leased equipment; and calculating the idle rate of the rental equipment by using the start-up state description information and the average work index of the rental equipment. For example, if the operating time of a rental device is 88 hours per month, and the average operating time index of the rental device in the industry field is 120 hours per month, the idle rate of the rental device can be calculated as (120-88)/120-27%.
If the working time of the rental equipment is lower than the average index of the industry field, but the difference is larger, the higher the idle rate of the rental equipment is; if the working time of the rental equipment is lower than the average index of the industry field, but the difference is smaller, the lower the idle rate of the rental equipment is. Of course, the working time of the rental equipment may also be higher than the average index of the industry field, and at this time, the rental equipment has no corresponding idle rate.
Calculating at least one health work measurement index matched with the rental equipment according to the operating state description information, and further comprising:
determining a non-operation time period matched with the rental equipment according to the operation state description information; and matching the non-operation time period with the power limiting time period published historically, and calculating a power limiting influence index according to a matching result.
The non-operation time period can be a time period in which the rental equipment does not work. The electricity-limited time period may refer to a time period in which a policy is issued to limit electricity usage for a particular enterprise. The electricity limit influence index can refer to the influence degree of the electricity limit time period issued by the policy on the operation of the rental equipment.
Specifically, the time period of the rental equipment without operation can be determined according to the operation state description information of the rental equipment of the lessee, the time period of the rental equipment without operation is matched with the power-limiting time period of the historical release, and the influence degree of the power-limiting time period on the rental equipment is calculated. If the matching degree (i.e. the time coincidence degree) of the non-operation time period and the power-limiting time period of the rental equipment is higher, the influence degree of the power-limiting time period on the operation of the rental equipment is deeper, i.e. the power-limiting influence index is larger; if the matching degree (i.e. the time coincidence degree) of the non-operation time period and the electricity-limiting time period of the rental equipment is lower, the influence degree of the electricity-limiting time period on the operation of the rental equipment is shallower, i.e. the electricity-limiting influence index is smaller.
S130, dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter can provide additional services to the renter of the renting equipment.
The early warning condition may refer to an upper limit value of each health work measurement index value of the rental equipment. The early warning information can be information displayed to the leasing party of the leasing equipment, and the information is used for warning the leasing party that a certain index or indexes of the leasing equipment reach the early warning condition. The additional service may refer to a service other than the rental service that the rental party of the rental device provides to the lessee.
Specifically, the calculated health work weighing indexes of the leasing equipment are dynamically monitored to obtain a monitoring result, if the health work weighing indexes meet the corresponding early warning conditions according to the monitoring result, corresponding early warning information can be generated and provided for the leasing party according to the health work weighing indexes meeting the early warning conditions, and the leasing party provides more humanized additional services for the leasing party of the leasing equipment according to the early warning information.
In an optional implementation manner of this embodiment, the dynamically monitoring each health work measurement index, and providing matched early warning information to the renter of the renting equipment when it is determined that the monitoring result satisfies the early warning condition, may include: and dynamically monitoring the maintenance cycle of the rental equipment, and providing maintenance early warning information to the renter when the rental equipment is determined to reach a maintenance time point.
The maintenance time point may be the latest maintenance time point of the rental device obtained after the renter rents a certain rental device and combines the maintenance period of the rental device. The maintenance early warning information can be information displayed to the leasing party and is used for warning the leasing party that certain leasing equipment reaches the latest maintenance time point and needs to be maintained.
Optionally, the maintenance cycle in the rental equipment health work measurement index is dynamically monitored, and when the current rental equipment arrives or is about to arrive at the maintenance time point, maintenance early warning information matched with the rental equipment can be generated and provided to the rental party.
The dynamically monitoring each health work measurement index, and providing the matched early warning information to the renter of the renting equipment when the monitoring result is determined to meet the early warning condition, may further include: dynamically monitoring the idle rate of the leased equipment, and providing equipment idle early warning for the leaser when the idle rate is determined to be greater than or equal to a first threshold; collecting a demand order matched with the rental equipment on a production order publishing platform, and detecting a full-load enterprise with the development rate being greater than or equal to a second threshold in the industry field; and providing the demand order and the full-load enterprise to the leasing party so that the leasing party can generate a working rate increasing scheme aiming at the leasing equipment.
The first threshold may refer to an upper limit of an idle rate of the rental equipment with respect to an industry domain average index. The equipment idle warning may be warning information indicating that a certain rental equipment is idle for too long. The second threshold may be an upper limit of the operating rate of all similar devices in the industry field where the rental device is located. The on-power boost scheme may be a scheme for reducing the idle rate of the leased device with too high idle rate.
Specifically, the idle rate in the health work measurement index of the rental equipment is dynamically monitored, and if the idle rate of the currently monitored rental equipment is determined to be greater than or equal to the upper limit value thereof, namely, when the first threshold value is determined, equipment idle early warning can be provided for the rental party of the rental equipment; the method can also be used for collecting a demand order matched with the currently monitored rental equipment in a production order publishing platform, and detecting enterprises with overhigh construction rate (namely, the construction rate is greater than or equal to a second threshold) in the industry field corresponding to the rental equipment, namely full-load enterprises; furthermore, the leasing party can generate a scheme for reducing the idle rate of the currently monitored leasing equipment according to the collected demand orders and the detected full-load enterprises, so that the operating rate of the leasing equipment is improved. It can be understood that the renter of the renting equipment can provide the information of the demand order, the full-load enterprises and the like in the industry field to the renter, and the renter can decide or select to contact the full-load enterprises to obtain more orders for the renting equipment.
The dynamically monitoring each health work measurement index, and providing the matched early warning information to the renter of the renting equipment when the monitoring result is determined to meet the early warning condition, may further include: and dynamically monitoring the electricity limiting influence index of the leasing equipment, and providing wind control early warning for the leasing party when the electricity limiting influence index is determined to be greater than or equal to a third threshold value.
The third threshold may refer to an upper limit value of the power limit influence index of the rental equipment. The wind-controlled early warning may refer to whether a tenant of the rental device has warning information for repaying the rental fee of the rental device.
Specifically, when the electricity-limiting influence index in the health work measurement index of the rental device is dynamically monitored, if it is determined that the electricity-limiting influence index of the rental device is too high, that is, the influence degree of the historically-issued electricity-limiting time period on the start of the rental device is greater than or equal to a third threshold, it is indicated that the limited electricity of the tenant of the rental device is deeply affected, and at this time, the tenant needs to consider whether the tenant has the ability of paying the rental fee in the future, so that risk control early warning information for the rental device can be generated.
According to the maintenance early warning, the idle early warning and the wind control early warning information, the renter can provide proper additional services for the renter, such as service reminding of reaching the maintenance time point, providing a demand order and full-load enterprise information, and service of replacing modes for paying the renting cost.
According to the technical scheme of the embodiment, the working state data of the rental equipment is collected in real time, and the operating state description information matched with the rental equipment is calculated according to the working state data; calculating at least one health work measurement index matched with the rental equipment according to the operating state description information; the method comprises the steps of dynamically monitoring each health work measurement index, providing matched early warning information to a renter of the renting equipment when a monitoring result is determined to meet early warning conditions so as to provide a technical means for the renter to provide additional services for the renter of the renting equipment, solves the problems that in the prior art, the health working state of the renting equipment of each equipment renting enterprise cannot be effectively monitored, and the renter cannot be efficiently, stably and effectively provided with services for the renter, and provides a new technology for dynamically monitoring whether the renter can work healthily so as to ensure that the renter can efficiently, stably and effectively provide services for the renter.
Example two
Fig. 2 is a flowchart of another method for early warning of the state of rental equipment according to a second embodiment of the present invention, where on the basis of the foregoing embodiments, preferably, after calculating the operating state description information matched with the rental equipment according to the operating state data, an operation is further added, and after calculating at least one health work measurement index matched with the rental equipment according to the operating state description information, an operation is further added, with reference to fig. 2, the method specifically includes:
s210, collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data.
And S220, calculating auxiliary start-up description information matched with the rental equipment according to the start-up state description information.
The auxiliary start-up description information may include information such as an industry start-up rate ranking, a region start-up rate ranking and a residual value range of the rental equipment. The industry operation rate ranking can refer to the operation rate of a lessee corresponding to the currently monitored rental equipment, and can be performed in at least one time unit in the industry field to which the industry operation rate ranking belongs. The regional operation rate ranking can refer to the operation rate of a lessee corresponding to the currently monitored leasing equipment, and the operation rate ranking of the similar equipment in a regional range where the operation rate ranking condition is planned to be known can be ranked under at least one time unit. The residual value range may refer to a corresponding value range of the rental device after being used for a period of time.
In this embodiment, the auxiliary start-up description information of the rental equipment can be calculated according to the start-up state description information of the rental equipment.
In an optional implementation manner of this embodiment, calculating, according to the start-up status description information, auxiliary start-up description information matched with the rental equipment may include: according to the industry fields to which the leased equipment and/or the lessee belong, the same-industry leased equipment matched with the leased equipment is screened out, and the industry operating rate ranking of the leased equipment is calculated according to the operating rate of each same-industry leased equipment; and according to the basic equipment information of the leased equipment, similar leased equipment matched with the leased equipment is screened out in a set region range, and the region operation rate ranking of the leased equipment is calculated according to the operation rate of each similar leased equipment.
Specifically, the operating rates of all the leased devices in the same industry matched with the leased device and all the leased devices in the same industry, which correspond to each other, can be obtained by screening from the leased device and/or the industry field to which the lessee belongs, so that the operating rate ranking of the leased device in the industry is obtained; and screening all similar leasing equipment and the operating rates corresponding to all the similar leasing equipment in a set region range according to the equipment basic information of the leasing equipment, so as to obtain the operating rate ranking of the leasing equipment in the set region range.
In another optional implementation manner of this embodiment, calculating, according to the start-up status description information, auxiliary start-up description information matched with the rental equipment may include: screening a target residual value estimation model matched with the rental equipment from all residual value estimation models according to the equipment basic information of the rental equipment; and inputting the start-up state description information of the rental equipment into the target residual value estimation model to obtain the residual value range of the rental equipment.
The residual value estimation model may be obtained by training using a device sample pre-labeled with a residual value range, where the device sample may include: and the start-up state description information and the matched residual value range labeling result correspond to the equipment of the target type and the associated equipment belonging to the same industry as the equipment of the target type. The target residual estimation model may be a target model selected from the total residual estimation models to match the currently processed rental equipment.
Specifically, the device basic information of the currently processed rental device may be used as the selection identifier, the required target residual value estimation model is selected from all the pre-trained residual value estimation models, and the operating state description information of the currently processed rental device is input into the selected target residual value estimation model, so as to obtain the residual value range of the rental device.
And S230, calculating at least one health work measurement index matched with the rental equipment according to the operating state description information.
S240, responding to an information query request of the lessee and/or the leaser, obtaining matched query information from the start-up state description information, the auxiliary start-up description information and the health work measurement index, and displaying the query information.
The information query request can be a query request of the renter and/or the renter for the information related to the renting equipment.
Specifically, when the lessee and/or the leasing party has a query requirement for the information of the leasing equipment, the information matched with the query requirement of the lessee and/or the leasing party can be obtained from the start-up state description information, the auxiliary start-up description information and the health work measurement index corresponding to the leasing equipment, and the information is displayed to the lessee and/or the leasing party.
And S250, dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter can provide additional service to the renter of the renting equipment.
According to the technical scheme of the embodiment, the working state data of the rental equipment is collected in real time, and the operating state description information matched with the rental equipment is calculated according to the working state data; calculating auxiliary start-up description information matched with the rental equipment according to the start-up state description information; calculating at least one health work measurement index matched with the rental equipment according to the operating state description information; responding to an information query request of the renter and/or the renter, acquiring matched query information from the start-up state description information, the auxiliary start-up description information and the health work measurement index, and displaying the query information; the method comprises the steps of dynamically monitoring each health work measurement index, providing matched early warning information to a renter of the renting equipment when a monitoring result is determined to meet early warning conditions so as to provide a technical means for the renter to provide additional services for the renter of the renting equipment, solves the problems that in the prior art, the health working state of the renting equipment of each equipment renting enterprise cannot be effectively monitored, and the renter cannot be efficiently, stably and effectively provided with services for the renter, and provides a new technology for dynamically monitoring whether the renter can work healthily so as to ensure that the renter can efficiently, stably and effectively provide services for the renter.
On the basis of the above embodiments, it is preferable that the method further includes: responding to a substitute equipment recommendation request of the lessee for the leased equipment, and acquiring an industry operation rate ranking and a region operation rate ranking of the leased equipment; screening and ranking target replacement equipment positioned in front of the leasing equipment from all equipment according to the industry operating rate ranking and the region operating rate ranking; and pushing the target replacement equipment to the lessee.
The substitute device recommendation request can refer to recommendation information which is desired by the lessee, and the recommendation information can comprise the substitute device of the device which is currently leased by the lessee. The target replacement device may refer to a replacement device that can implement the function of the current rental device while having performance, etc., superior to the current rental device.
Specifically, if the tenant has a replacement requirement for the current rental device, the industry operating rate rank and the region operating rate rank of the current rental device may be obtained, the target replacement device is screened from all devices located above the current rental device operating rate rank and recommended to the tenant, and finally whether the tenant rents the target replacement device or not may be determined by the tenant.
The advantage of this arrangement is that by recommending the target replacement device, a more comfortable service experience can be obtained for the lessee.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a state warning apparatus for rental equipment according to a third embodiment of the present invention, which is capable of executing a state warning method for rental equipment according to any embodiment of the present invention. Referring to fig. 3, the apparatus includes: the system comprises a start-up state description information calculation module 310, a health work measurement index calculation module 320 and an early warning module 330.
The start-up state description information calculation module 310 is used for collecting the working state data of the rental equipment in real time and calculating start-up state description information matched with the rental equipment according to the working state data;
a health work measurement index calculation module 320, configured to calculate at least one health work measurement index matched with the rental equipment according to the operating state description information;
the early warning module 330 is configured to dynamically monitor each health work measurement index, and when it is determined that the monitoring result meets an early warning condition, provide matching early warning information to a renter of the renting device, so that the renter provides additional services to a renter of the renting device.
According to the technical scheme of the embodiment of the invention, the working state data of the rental equipment is collected in real time, and the operating state description information matched with the rental equipment is calculated according to the working state data; calculating at least one health work measurement index matched with the rental equipment according to the operating state description information; the method comprises the steps of dynamically monitoring each health work measurement index, providing matched early warning information to a renter of the renting equipment when a monitoring result is determined to meet early warning conditions so as to provide a technical means for the renter to provide additional services for the renter of the renting equipment, solves the problems that in the prior art, the health working state of the renting equipment of each equipment renting enterprise cannot be effectively monitored, and the renter cannot be efficiently, stably and effectively provided with services for the renter, and provides a new technology for dynamically monitoring whether the renter can work healthily so as to ensure that the renter can efficiently, stably and effectively provide services for the renter.
In the above apparatus, optionally, the start-up state description information calculating module 310 may be specifically configured to:
collecting amplitude data of the rental device in real time through a device bracelet arranged on the rental device, and/or
And collecting the current data of the leasing equipment in real time through a current collecting device configured on a power grid line where the leasing equipment is located.
In the above apparatus, optionally, the start-up state description information calculating module 310 may be further specifically configured to:
acquiring equipment basic information of the rental equipment, and screening out a target working state identification model matched with the rental equipment from all working state identification models according to the equipment basic information;
inputting the working state data into the target working state recognition model, and acquiring start-up state description information matched with the rental equipment;
wherein the start-up state description information includes at least one of: a rate of operation, a length of time of operation, and a peak time period of operation in at least one time unit.
In the above apparatus, optionally, the health work measure index calculating module 320 may be specifically configured to:
acquiring a standard maintenance cycle matched with the rental equipment according to the equipment basic information of the rental equipment;
adjusting the standard maintenance cycle according to the start-up state description information and the working environment description information of the rental equipment to obtain the maintenance cycle of the rental equipment;
the early warning module 330 may be specifically configured to:
and dynamically monitoring the maintenance cycle of the rental equipment, and providing maintenance early warning information to the renter when the rental equipment is determined to reach a maintenance time point.
In the above apparatus, optionally, the health work measure index calculating module 320 may be further specifically configured to:
acquiring an industry field to which the rental equipment and/or the lessee belong, and acquiring an average work index matched with the industry field;
calculating the idle rate of the rental equipment according to the operating state description information and the average work index;
the early warning module 330 may be further specifically configured to:
dynamically monitoring the idle rate of the leased equipment, and providing equipment idle early warning for the leaser when the idle rate is determined to be greater than or equal to a first threshold;
collecting a demand order matched with the rental equipment on a production order publishing platform, and detecting a full-load enterprise with the development rate being greater than or equal to a second threshold in the industry field;
and providing the demand order and the full-load enterprise to the leasing party so that the leasing party can generate a working rate increasing scheme aiming at the leasing equipment.
In the above apparatus, optionally, the health work measure index calculating module 320 may be further specifically configured to:
determining a non-operation time period matched with the rental equipment according to the operation state description information;
matching the non-operation time period with a power limiting time period published historically, and calculating a power limiting influence index according to a matching result;
the early warning module 330 may be further specifically configured to:
and dynamically monitoring the electricity limiting influence index of the leasing equipment, and providing wind control early warning for the leasing party when the electricity limiting influence index is determined to be greater than or equal to a third threshold value.
In the above apparatus, optionally, the apparatus further includes an auxiliary operating description information calculating module, configured to, after calculating operating state description information matched with the rental device according to the operating state data:
calculating auxiliary start-up description information matched with the rental equipment according to the start-up state description information;
the system further comprises an inquiry information display module, which is used for calculating at least one health work measurement index matched with the rental equipment according to the operating state description information, and then:
responding to an information query request of the lessee and/or the leaser, obtaining matched query information from the start-up state description information, the auxiliary start-up description information and the health work measurement index, and displaying the query information.
In the above apparatus, optionally, the auxiliary start-up description information calculating module may be specifically configured to:
according to the industry fields to which the leased equipment and/or the lessee belong, the same-industry leased equipment matched with the leased equipment is screened out, and the industry operating rate ranking of the leased equipment is calculated according to the operating rate of each same-industry leased equipment; and
and according to the basic equipment information of the rental equipment, similar rental equipment matched with the rental equipment is screened out in a set region range, and the region operation rate ranking of the rental equipment is calculated according to the operation rate of each similar rental equipment.
In the above apparatus, optionally, the auxiliary start-up description information calculating module may be further specifically configured to:
screening a target residual value estimation model matched with the rental equipment from all residual value estimation models according to the equipment basic information of the rental equipment;
inputting the start-up state description information of the rental equipment into the target residual value estimation model to obtain a residual value range of the rental equipment;
the residual value estimation model is obtained by training an equipment sample which is labeled with a residual value range in advance, wherein the equipment sample comprises: and the start-up state description information and the matched residual value range labeling result correspond to the equipment of the target type and the associated equipment belonging to the same industry as the equipment of the target type.
In the above apparatus, optionally, the apparatus further includes a target replacement device pushing module, configured to:
responding to a substitute equipment recommendation request of the lessee for the leased equipment, and acquiring an industry operation rate ranking and a region operation rate ranking of the leased equipment;
screening and ranking target replacement equipment positioned in front of the leasing equipment from all equipment according to the industry operating rate ranking and the region operating rate ranking;
and pushing the target replacement equipment to the lessee.
The state early warning device for the rental equipment, provided by the embodiment of the invention, can execute the state early warning method for the rental equipment, provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of an electronic apparatus according to a fourth embodiment of the present invention, as shown in fig. 4, the electronic apparatus includes a processor 410, a storage device 420, an input device 430, and an output device 440; the number of the processors 410 in the device may be one or more, and one processor 410 is taken as an example in fig. 4; the processor 410, the storage 420, the input 430 and the output 440 of the apparatus may be connected by a bus or other means, as exemplified by the bus connection in fig. 4.
The storage device 420 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the method for early warning the status of rental equipment in the embodiment of the present invention (for example, the operating status description information calculating module 310, the health measure index calculating module 320, and the early warning module 330 in the status early warning device of rental equipment). The processor 410 executes various functional applications and data processing of the device by executing software programs, instructions and modules stored in the storage device 420, so as to implement the above state pre-warning method for the rental device, the method comprising:
collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data;
calculating at least one health work measurement index matched with the rental equipment according to the operating state description information;
and dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter provides additional service to a renter of the renting equipment.
The storage device 420 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 420 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the storage 420 may further include memory located remotely from the processor 410, which may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 430 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the apparatus. The output device 440 may include a display device such as a display screen.
EXAMPLE five
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is used to execute a method for early warning a state of rental equipment when executed by a computer processor, and the method includes:
collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data;
calculating at least one health work measurement index matched with the rental equipment according to the operating state description information;
and dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter provides additional service to a renter of the renting equipment.
Of course, the computer-readable storage medium provided in the embodiments of the present invention stores thereon a computer program, where the computer program is not limited to the method operations described above, and may also perform related operations in the state warning method for rental equipment provided in any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the state warning device for rental equipment, each unit and each module included in the embodiment are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (13)
1. A state early warning method for rental equipment is characterized by comprising the following steps:
collecting working state data of the rental equipment in real time, and calculating start-up state description information matched with the rental equipment according to the working state data;
calculating at least one health work measurement index matched with the rental equipment according to the operating state description information;
and dynamically monitoring each health work measurement index, and providing matched early warning information to a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter provides additional service to a renter of the renting equipment.
2. The method of claim 1, wherein collecting the operating status data of the rental device in real-time comprises:
collecting amplitude data of the rental device in real time through a device bracelet arranged on the rental device, and/or
And collecting the current data of the leasing equipment in real time through a current collecting device configured on a power grid line where the leasing equipment is located.
3. The method of claim 2, wherein calculating the operating status description information matching the rental device based on the operating status data comprises:
acquiring equipment basic information of the rental equipment, and screening out a target working state identification model matched with the rental equipment from all working state identification models according to the equipment basic information;
inputting the working state data into the target working state recognition model, and acquiring start-up state description information matched with the rental equipment;
wherein the start-up state description information includes at least one of: a rate of operation, a length of time of operation, and a peak time period of operation in at least one time unit.
4. The method of claim 3, wherein calculating at least one health measure index matching the rental device based on the operating status description information comprises:
acquiring a standard maintenance cycle matched with the rental equipment according to the equipment basic information of the rental equipment;
adjusting the standard maintenance cycle according to the start-up state description information and the working environment description information of the rental equipment to obtain the maintenance cycle of the rental equipment;
the dynamically monitoring each health work measurement index, and providing matched early warning information to the renter of the renting equipment when the monitoring result is determined to meet the early warning condition, comprises the following steps:
and dynamically monitoring the maintenance cycle of the rental equipment, and providing maintenance early warning information to the renter when the rental equipment is determined to reach a maintenance time point.
5. The method of claim 3, wherein calculating at least one health measure index matching the rental device based on the operating status description information comprises:
acquiring an industry field to which the rental equipment and/or the lessee belong, and acquiring an average work index matched with the industry field;
calculating the idle rate of the rental equipment according to the operating state description information and the average work index;
the dynamically monitoring each health work measurement index, and providing matched early warning information to the renter of the renting equipment when the monitoring result is determined to meet the early warning condition, comprises the following steps:
dynamically monitoring the idle rate of the leased equipment, and providing equipment idle early warning for the leaser when the idle rate is determined to be greater than or equal to a first threshold;
collecting a demand order matched with the rental equipment on a production order publishing platform, and detecting a full-load enterprise with the development rate being greater than or equal to a second threshold in the industry field;
and providing the demand order and the full-load enterprise to the leasing party so that the leasing party can generate a working rate increasing scheme aiming at the leasing equipment.
6. The method of claim 3, wherein calculating at least one health measure index matching the rental device based on the operating status description information comprises:
determining a non-operation time period matched with the rental equipment according to the operation state description information;
matching the non-operation time period with a power limiting time period published historically, and calculating a power limiting influence index according to a matching result;
the dynamically monitoring each health work measurement index, and providing matched early warning information to the renter of the renting equipment when the monitoring result is determined to meet the early warning condition, comprises the following steps:
and dynamically monitoring the electricity limiting influence index of the leasing equipment, and providing wind control early warning for the leasing party when the electricity limiting influence index is determined to be greater than or equal to a third threshold value.
7. The method of any of claims 1-6, further comprising, after calculating the operating state description information that matches the rental equipment based on the operating state data:
calculating auxiliary start-up description information matched with the rental equipment according to the start-up state description information;
after at least one health work measurement index matched with the rental equipment is calculated according to the operating state description information, the method further comprises the following steps:
responding to an information query request of the lessee and/or the leaser, obtaining matched query information from the start-up state description information, the auxiliary start-up description information and the health work measurement index, and displaying the query information.
8. The method of claim 7, wherein calculating auxiliary start-up description information matched with the rental equipment according to the start-up state description information comprises:
according to the industry fields to which the leased equipment and/or the lessee belong, the same-industry leased equipment matched with the leased equipment is screened out, and the industry operating rate ranking of the leased equipment is calculated according to the operating rate of each same-industry leased equipment; and
and according to the basic equipment information of the rental equipment, similar rental equipment matched with the rental equipment is screened out in a set region range, and the region operation rate ranking of the rental equipment is calculated according to the operation rate of each similar rental equipment.
9. The method of claim 7, wherein calculating auxiliary start-up description information matched with the rental equipment according to the start-up state description information comprises:
screening a target residual value estimation model matched with the rental equipment from all residual value estimation models according to the equipment basic information of the rental equipment;
inputting the start-up state description information of the rental equipment into the target residual value estimation model to obtain a residual value range of the rental equipment;
the residual value estimation model is obtained by training an equipment sample which is labeled with a residual value range in advance, wherein the equipment sample comprises: and the start-up state description information and the matched residual value range labeling result correspond to the equipment of the target type and the associated equipment belonging to the same industry as the equipment of the target type.
10. The method of claim 8, further comprising:
responding to a substitute equipment recommendation request of the lessee for the leased equipment, and acquiring an industry operation rate ranking and a region operation rate ranking of the leased equipment;
screening and ranking target replacement equipment positioned in front of the leasing equipment from all equipment according to the industry operating rate ranking and the region operating rate ranking;
and pushing the target replacement equipment to the lessee.
11. A state early warning device of rental equipment, characterized by comprising:
the operating state description information calculation module is used for collecting the working state data of the rental equipment in real time and calculating operating state description information matched with the rental equipment according to the working state data;
the health work measurement index calculation module is used for calculating at least one health work measurement index matched with the rental equipment according to the operating state description information;
and the early warning module is used for dynamically monitoring each health work measurement index, and providing matched early warning information for a renter of the renting equipment when the monitoring result is determined to meet the early warning condition so that the renter can provide additional service for the renter of the renting equipment.
12. An electronic device, characterized in that the electronic device comprises:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a method of status warning for a rental device as claimed in any of claims 1-10.
13. A computer-readable storage medium having stored thereon a computer program, wherein the program, when executed by a processor, implements a method for status warning of rental equipment as claimed in any one of claims 1-10.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115169610A (en) * | 2022-07-14 | 2022-10-11 | 中万恩科技有限公司 | Commercial dish washing machine diagnosis and monitoring method, device, control equipment and medium |
| CN117354354A (en) * | 2023-12-05 | 2024-01-05 | 泉州芸台科技有限公司 | Remote control method and system for construction protection platform |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005352661A (en) * | 2004-06-09 | 2005-12-22 | Hitachi Building Systems Co Ltd | Building maintenance contract maintenance support method |
| US20130197959A1 (en) * | 2012-01-31 | 2013-08-01 | Infosys Limited | System and method for effective equipment rental management |
| US20140257924A1 (en) * | 2013-03-08 | 2014-09-11 | Corelogic Solutions, Llc | Automated rental amount modeling and prediction |
| US9374660B1 (en) * | 2012-05-17 | 2016-06-21 | Amazon Technologies, Inc. | Intentional monitoring |
| CN109359866A (en) * | 2018-10-17 | 2019-02-19 | 平安国际融资租赁有限公司 | Risk hidden danger monitoring method, device and computer equipment based on leased equipment |
| JP2019197252A (en) * | 2018-05-07 | 2019-11-14 | 株式会社タス | Vacancy rate estimation device, method and computer program |
| CN110852569A (en) * | 2019-10-16 | 2020-02-28 | 湖南工研科技有限公司 | Equipment management method and system and electronic equipment |
| CN111882395A (en) * | 2020-07-29 | 2020-11-03 | 平安国际融资租赁有限公司 | Monitoring method and system for rental equipment, computer equipment and storage medium |
| CN112101662A (en) * | 2020-09-16 | 2020-12-18 | 珠海格力电器股份有限公司 | Equipment health condition and life cycle detection method, storage medium and electronic equipment |
| CN112435105A (en) * | 2021-01-27 | 2021-03-02 | 支付宝(杭州)信息技术有限公司 | Rental risk assessment method, device, equipment and system based on block chain |
-
2022
- 2022-01-18 CN CN202210055377.1A patent/CN114360222B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005352661A (en) * | 2004-06-09 | 2005-12-22 | Hitachi Building Systems Co Ltd | Building maintenance contract maintenance support method |
| US20130197959A1 (en) * | 2012-01-31 | 2013-08-01 | Infosys Limited | System and method for effective equipment rental management |
| US9374660B1 (en) * | 2012-05-17 | 2016-06-21 | Amazon Technologies, Inc. | Intentional monitoring |
| US20140257924A1 (en) * | 2013-03-08 | 2014-09-11 | Corelogic Solutions, Llc | Automated rental amount modeling and prediction |
| JP2019197252A (en) * | 2018-05-07 | 2019-11-14 | 株式会社タス | Vacancy rate estimation device, method and computer program |
| CN109359866A (en) * | 2018-10-17 | 2019-02-19 | 平安国际融资租赁有限公司 | Risk hidden danger monitoring method, device and computer equipment based on leased equipment |
| CN110852569A (en) * | 2019-10-16 | 2020-02-28 | 湖南工研科技有限公司 | Equipment management method and system and electronic equipment |
| CN111882395A (en) * | 2020-07-29 | 2020-11-03 | 平安国际融资租赁有限公司 | Monitoring method and system for rental equipment, computer equipment and storage medium |
| CN112101662A (en) * | 2020-09-16 | 2020-12-18 | 珠海格力电器股份有限公司 | Equipment health condition and life cycle detection method, storage medium and electronic equipment |
| CN112435105A (en) * | 2021-01-27 | 2021-03-02 | 支付宝(杭州)信息技术有限公司 | Rental risk assessment method, device, equipment and system based on block chain |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115169610A (en) * | 2022-07-14 | 2022-10-11 | 中万恩科技有限公司 | Commercial dish washing machine diagnosis and monitoring method, device, control equipment and medium |
| CN115169610B (en) * | 2022-07-14 | 2023-05-09 | 中万恩科技有限公司 | Commercial dish washer diagnosis and monitoring method, device, control equipment and medium |
| CN117354354A (en) * | 2023-12-05 | 2024-01-05 | 泉州芸台科技有限公司 | Remote control method and system for construction protection platform |
| CN117354354B (en) * | 2023-12-05 | 2024-03-26 | 泉州芸台科技有限公司 | Remote control method and system for construction protection platform |
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|---|---|
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