JP5665635B2 - Parameter and equipment recommendation equipment for building facilities - Google Patents

Description

  The present invention relates to the setting of parameters for control devices in building facilities that require maintenance such as elevators, air conditioning equipment, security systems, and solar power generation, and retrofit optional equipment to be added later while the parameters are in operation. The present invention relates to a device and a device recommendation device in a building facility recommended for (user).

  In building equipment such as elevators, when there are multiple parameters (hereinafter also referred to as control parameters) and optional equipment (additional equipment), the usage status of the equipment and Depending on the installation environment, it will be necessary to enhance the functions by setting control parameters and adding optional retrofit equipment. However, in many cases, the control parameters are set assuming a general situation in the factory shipment state, or are set so as not to cause a problem in various situations. In addition, as for retrofitted optional equipment, only a minimum is often added assuming a general situation or taking into consideration the intention of the right to decide the equipment introduction. However, the evaluation criteria for performing better operations are generally diverse.

  For example, taking an elevator as an example, while there is a standard for operation efficiency such as waiting time, there are various standards such as a standard for usability such as ease of use and user friendliness, and a standard for security and energy saving performance. As measures to improve individual values of these standards, control parameter adjustment and retrofit optional equipment are available, but not only there are restrictions on adjustment and introduction cost, but also control parameter adjustment and The addition of optional equipment may improve certain standards but may worsen other standards, and it is necessary to determine control parameters and retrofit optional equipment while balancing the changes in multiple standards and introduction costs. There is. In addition, regarding priorities among multiple standards, static factors such as external factors such as the social environment and the location where equipment is installed, for example, the type of building (eg, office, condominium, commercial facility, or factory), etc. Although it is determined based on dynamic factors such as operational factors and facility operating conditions, the above factors are often not clear. Therefore, it is necessary to determine control parameters and additional equipment and make adjustments in consideration of the above factors.

  2. Description of the Related Art Conventionally, there is a system that includes WWW communication software in an elevator control device and enables a service that changes the specifications of the elevator control software from a communication terminal device that can be connected to the Internet (see, for example, Patent Document 1).

  Also, in order to collect the building data input for each building, extract the optimum operation data of the building equipment from the data analysis result based on the collected building data, and use it for each building, maintenance data of each building equipment There is a system having a function of indicating an average value as a recommended time for replacement (for example, for example), a collecting means for collecting data, an analyzing means for analyzing collected data, and a providing means for providing analysis results (for example, Patent Document 2).

  In addition, by analyzing the trend of changes in history data up to the failure when the device breaks down, monitoring the history change in the measurement data of the same type of device from the analysis result, the failure is predicted, and the FTA There is an apparatus having a function of detecting a fault location using a (fault tolerant tree) (see, for example, Patent Document 3).

  In addition, there is an apparatus having a function of diagnosing an operating state of elevators and building equipment installed in a building equipment group to be diagnosed from operating histories of elevators installed in a plurality of building equipment groups (for example, , See Patent Document 4).

JP 2003-182946 A JP 2004-94299 A JP 2004-133553 A JP 2006-143359 A

  In Patent Document 1, the specification can only be changed by a terminal on the Internet, and no function for presenting how to change the specification is provided.

  Further, Patent Document 2 only presents data analysis results, and does not include a control parameter change or a recommended function for a retrofit optional device. Moreover, the function which estimates the effect at the time of applying a recommendation content is not provided.

  Further, Patent Document 3 has a failure prediction function and a failure location detection function, but does not have a control parameter change function or a retrofit optional device recommendation function.

  In Patent Document 4, although the operation state is diagnosed, the control parameter change and the recommended function of the retrofit optional device are not provided.

  As described above, conventionally, data analysis reflecting the use (operation) status in other buildings is performed, but the control parameter change and the recommended function of the retrofit optional device are not provided. Further, even if the control parameters and retrofit optional equipment obtained by the above data analysis are applied to the target building facility, it is not guaranteed that the performance of the target building facility will be improved.

  The present invention has been made in order to solve these problems, and provides a device for recommending parameters and equipment in a building facility capable of recommending control parameters and retrofit optional equipment for improving the performance of the target building equipment. For the purpose.

In order to solve the above-described problems, the device for recommending parameters and equipment in a building facility according to the present invention includes operation history data of a plurality of building facilities including a recommended building facility and other building facilities other than the recommended building facility. Building equipment parameter options, including an operation history data storage section to be stored, a building equipment status data storage section to store building equipment status data, which is information on the installation status of building equipment, and control information of building equipment and information on optional equipment Based on the building equipment parameter option data storage unit that accumulates data, operation history data, building equipment status data, and building equipment parameter option data, control parameter change values and additional option equipment for the recommended building equipment are recommended candidates Parameters and device recommendation candidates to be extracted as And the detection section, and the recommended candidate, on the basis of the operation history data of the recommendation target building facilities, and simulation evaluation unit for performing the evaluation by simulation in the case of applying the recommended candidate to the recommendation target building equipment, the simulation evaluation unit An evaluation result determination unit that determines whether or not to recommend a recommendation candidate based on the evaluation result, and a recommendation that outputs the recommendation candidate when the evaluation result determination unit determines that the recommendation candidate is recommended A result output unit.

According to the present invention, the operation history data storage unit that stores the operation history data of a plurality of building facilities including the recommended building facilities and other building facilities other than the recommended building facilities, and information on the installation status of the building facilities Building equipment status data storage section for storing building equipment status data, building equipment parameter option data storage section for storing building equipment parameter option data including building equipment control parameters and information on optional equipment, operation history data, building A parameter / device recommendation candidate extraction unit that extracts a change value of a control parameter or an additional option device as a recommendation candidate based on the facility status data and the building facility parameter option data, a recommendation candidate, and a recommendation target on the basis of the operation history data of the building equipment, the recommendation target And simulation evaluation unit for performing evaluation by simulation in the case of applying the recommendation candidates against Le facilities, based on the results of the evaluation of the simulation evaluation unit, the evaluation result determination unit determines whether or not to recommend recommendation candidates And a recommendation result output unit that outputs the recommendation candidate when it is determined by the evaluation result determination unit that the recommendation candidate is recommended. Recommendations are possible.

It is a figure which shows an example of a structure of the recommendation apparatus of the control parameter in the building installation by the embodiment of this invention, and retrofit optional equipment. It is a figure which shows an example of the input table of collaborative filtering in the parameter and apparatus recommendation candidate extraction part by embodiment of this invention. It is a flowchart which shows the extraction operation | movement of the parameter and the option recommendation candidate in the parameter and apparatus recommendation candidate extraction part by embodiment of this invention. It is a flowchart which shows the estimation operation | movement of the parameter and option in the parameter and apparatus recommendation candidate extraction part by embodiment of this invention. It is a flowchart which shows the correction operation | movement of the parameter and option recommendation candidate extraction in the parameter and apparatus recommendation candidate extraction part by embodiment of this invention. It is a flowchart which shows the parameter and the option re-estimation operation | movement in the parameter and apparatus recommendation candidate extraction part by embodiment of this invention. It is a figure which shows an example of a structure of the recommendation apparatus of the control parameter in the building installation by the embodiment of this invention, and retrofit optional equipment.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a diagram illustrating an example of a configuration of a control parameter and retrofit option device recommendation device 1 in a building facility according to an embodiment of the present invention. In FIG. 1, elevator facilities 2-1 to 2 -N (hereinafter also simply referred to as an elevator facility 2) are installed in the same or different building as the recommendation device 1. Here, N indicates the number of elevators 2 targeted by the recommendation device 1. In the present embodiment, an elevator is described as an example of target building equipment, but building equipment other than an elevator may be used.

  First, the configuration of the recommendation device 1 will be described.

  As shown in FIG. 1, the recommendation device 1 according to the present embodiment includes a movement history receiving unit 3, an operation history data storage unit 4, a building equipment status data storage unit 5, a building equipment parameter option storage unit 6, and a parameter. A device recommendation candidate extraction unit 7, a simulation evaluation unit 8, an evaluation result determination unit 9, a recommendation candidate extraction condition correction unit 10, a recommendation result output unit 11, and a recommendation result request unit 12 are provided.

  The operation history receiving unit 3 is communicably connected to the elevator facility 2 (building facility) via the Internet or a telephone line, and acquires operation history data of the elevator facility 2 from each building. The data to be acquired may be data processed to indicate the performance and usage status of the elevator equipment 2, such as the number of times the elevator is started, the number of passengers, the number of passengers getting off, and the waiting time, or a car position signal, a landing call signal, a car Signal data of a control device (not shown) of the elevator facility 2 such as a call signal and a door opening / closing signal may be used.

  The operation history data storage unit 4 stores the operation history data received by the operation history reception unit 3. As the operation history data accumulation method, the data input from the operation history reception unit 3 may be accumulated as it is, or for example, signal data may be stored in the elevator facility 2 such as the number of activations, the number of passengers, the number of people getting off, and the waiting time. Data indicating performance and usage status may be processed and accumulated. Moreover, you may accumulate | store the cumulative value, average value, etc. of the data which show the performance and utilization condition of the elevator installation 2. FIG.

  Unlike the operation history data stored in the operation history data storage unit 4, the building facility state data storage unit 5 stores static building facility state data that is information on the installation state of the elevator facility 2. The building facility status data may be, for example, data related to the size of the building such as the height of the building, the number of floors, and the floor area. Further, it may be data relating to a building use or data relating to characteristics of an installation location (for example, data relating to topography such as whether it is along a coast, data such as an urban area, a residential area, a rural area, or a prefecture name). Moreover, the specification data of the elevator equipment 2 such as the elevator hoistway distance, the number of service floors, the number of cars, the speed, the number of cars, the presence / absence of a machine room, and the model name may be used. However, data represented by other than numerical values is given numerical IDs, converted into numerical data, and stored.

  For example, for the building usage data, values such as office building = 1, apartment = 2, commercial building = 3, and hospital = 4 are set. Also, if there are multiple elements such as office / condominium complex building = 1.5, apartment / commercial complex building = 2.5, the value between each building use may be taken, or office / condominium complex building You may set the numerical value which is not related to the element included, such as a building = 5 and an apartment / commercial complex building = 6.

  Similarly, the data regarding the characteristics of the installation location may be set as urban area = 1, residential area = 2, rural area = 3. If the data is related to the prefecture name, Hokkaido = 1, Aomori = 11, Iwate. = 12, ..., Tokyo = 21, Chiba = 22, etc. Numbering the second digit (ten's place) based on the local name, and numbering the first digit (first place) for each prefecture And may be quantified. The presence / absence of a machine room provided in each building may be quantified such that there is a machine room = 1 and no machine room = 0.

  The building equipment parameter option storage section 6 (building equipment parameter option data storage section) indicates the presence / absence of optional equipment in the elevator equipment 2 (information on optional equipment) and the status of variable parameters of the control device (control parameters of the elevator equipment 2). The building equipment parameter option data shown is stored. In the building equipment parameter option data, the set numerical value is set for the control parameter, the presence / absence of optional equipment is set to “1”, and the blank is left blank.

  Each data stored in the operation history data storage unit 4, the building equipment status data storage unit 5, and the building equipment parameter option storage unit 6 is stored with a common ID assigned to each elevator or each building. And it is comprised so that the correlation of said data regarding the same elevator installation 2 may become easy.

  The recommendation result request unit 12 requests recommendation of control parameters and optional equipment for an optional elevator 2-K. Here, K is an integer satisfying 0 <K ≦ N. As a recommendation request trigger, the recommendation result request unit 12 may include a user interface, or may be connected to a terminal via a network so that a recommendation request command may be transmitted from the terminal. Moreover, according to the preset schedule, you may request | require the recommendation of a control parameter or a retrofit option apparatus in order about the elevators 2-1 to 2-N.

  The parameter / equipment recommendation candidate extraction unit 7 uses the operation history data, building equipment status data, and building equipment parameter option data regarding the elevator equipment 2 to control parameters for any one elevator equipment 2 (recommended building equipment). Change proposals and option addition proposals are extracted as recommendation candidates. In other words, the parameter / equipment recommendation candidate extraction unit 7 adds the control parameter change value and the retrofitted optional equipment (additional) for the elevator equipment 2 to be recommended based on the operation history data, building equipment status data, and building equipment parameter option data. Optional devices) are extracted as recommended candidates.

  As an extraction method, for example, there is a method using collaborative filtering. Collaborative filtering is, for example, estimating an unknown evaluation value of an item for a certain user in consideration of the similarity between the user and the item from evaluation values assigned to each item by a plurality of users (for example, , "Information Processing Vol. 48, No. 9, September 2007, P.957-P.965").

  In the collaborative filtering described above, “user” corresponds to each elevator facility 2 of the present embodiment, and “item” includes the operation history data storage unit 4, building facility status data storage unit 5, building facility parameter of the present embodiment. The “evaluation value” corresponds to the value of each data for each elevator according to the present embodiment, corresponding to each data item stored in the option storage unit 6. Further, when signal data is stored in the operation history data storage unit 4, it is converted into data indicating the performance and usage status of the elevator equipment 2 such as the number of activations, the number of passengers, the number of passengers getting off, and the waiting time. set to target.

  FIG. 2 is a diagram showing an example of an input table for collaborative filtering in the parameter / device recommendation candidate extraction unit 7 according to the embodiment of the present invention. In FIG. 2, the horizontal direction indicates individual elevator equipment 2 that is a user, and the vertical direction indicates items (operation history data storage unit 4, building facility status data storage unit 5, and building facility parameter option storage unit 6. Data items). Moreover, in FIG. 2, although the value of each element is shown as it is, you may normalize (normalize) each item so that it may become a value between 1 and 0, for example. For example, it can be normalized by the following equations (1) to (3).

P_max (m) = max (P (1, l), P (2, l), ..., P (K_max, M)) (1)
P_min (m) = min (P (m, 1), P (m, 2), .... P (K_max, M)) (2)
P (k, m) = (P (k, m) -P_min (m)) / (P_max (m) P_min (m)) (3)
In the above formulas (1) to (3), P (k, l) is the evaluation value of the kth user's lth item, P_max (m) is the maximum value for all users of the mth item, P_min ( m) is the minimum value for all users of the mth item, K_max is the number of users, M is the number of items, max is a function for extracting the maximum value, and min is a function for extracting the minimum value.

  There are a plurality of collaborative filtering algorithms. User-based method that estimates based on similarity between users, item-based method that estimates based on similarity between items, and the difference in evaluation values between items is the same for all users A slope-one method that calculates an average deviation of evaluation values between items and estimates a target evaluation value from a known evaluation value of the prediction target user and the average deviation, and maps the evaluation value of each user to the number of items Then, there is a singular value decomposition method in which the feature plane is derived by singular value decomposition and an unknown evaluation value is obtained so that the evaluation value of each item of a certain user is closest to the feature plane. Further, there are a method using clustering and a probabilistic method such as a Bayesian network or an EM algorithm.

  Next, with reference to FIG. 3, the recommended candidate extraction operation when a control parameter or a retrofit optional device is requested for an arbitrary elevator 2-K will be described.

  FIG. 3 is a flowchart showing the operation of extracting the control parameters and the recommended candidates for the retrofit optional device in the parameter / device recommendation candidate extraction unit 7 according to the embodiment of the present invention. As shown in FIG. 3, in step S301, the estimated value of each parameter (control parameter) and the estimated value of the option (optional device) are obtained using collaborative filtering. Here, the estimated value estimated by leaving the value of each parameter in the input data for collaborative filtering (see FIG. 2) blank is assumed to be the estimated value of that parameter. Details will be described later with reference to FIG.

  In step S302, an optional evaluation value p (i) is substituted for the determination score. The i-th option evaluation value p (i) is stored in the determination score X (i). However, the evaluation value of the optional equipment already installed at the time of evaluation is 0. Therefore, a value is substituted into X (i) of the determination score based on the following formula (4) or formula (5).

X (i) = P '(K, L + i) (When the i-th option is not installed) (4)
X (i) = 0 (when i-th option is already installed) (5)
Here, L is the number of the last item (item) of the building facility status data in FIG. P ′ (K, L + i) is an estimated value of the i-th option of the K-th user estimated in step S301. In this way, the determination score is created in addition to the input table shown in FIG.

  In step S303, it is determined whether the evaluation value is assigned to the determination score by applying the formula (4) or the formula (5) to all the option devices, and the substitution is completed for all the options. If YES in step S304, the flow advances to step S304. If substitution has not been completed, the flow returns to step S302.

  In step S304, based on the estimated value of each parameter, for example, a value to be substituted into the determination score is calculated according to the following equation (6).

X (I + j) = (P (K, L + I + j) − (original value of parameter j))
/ (Maximum value that parameter j can take) (6)
Further, the value of the determination score may be calculated according to the following equation (7).

X (I + j) = (P (K, L + I + j) − (original value of parameter j))
/ (Original value of parameter j) (7)
Note that the judgment score of the jth parameter is stored in X (j + L). Here, I is the number of options, and P (K, L + I + j) is an estimated value of the evaluation value for the elevator 2-K, j-th parameter.

  In step S305, it is determined whether the evaluation value is assigned to the determination score by applying the formula (6) or the formula (7) to all the parameters, and the substitution is completed for all the parameters. If so, the process proceeds to step S306, and if the substitution is not completed, the process returns to step S304.

  In step S306, the parameter or option with the largest determination score value is selected and set as a recommendation candidate.

  Next, an estimation procedure of estimated values of each parameter and optional evaluation values will be described.

  FIG. 4 is a flowchart showing parameter and option estimation operations in the parameter / device recommendation candidate extraction unit 7 according to the embodiment of the present invention.

  As shown in FIG. 4, the parameter / equipment recommendation candidate extraction unit 7 reads operation history data from the operation history data storage unit 4 (step S401), and reads building facility status data from the building facility status data storage unit 5 (step S401). S402), the building equipment parameter option data is read from the building equipment parameter option storage unit 6 (steps S403 and S404), and the input table IT shown in FIG. 2 is created. Each element of the input table IT is indicated by an evaluation value P (k, l) of the l-th item of the k-th user. Note that the input table IT normalized according to the equations (1) to (3) may be created.

  In steps S405 and S406, the evaluation values of all the options that are blank in the input table IT are estimated for an arbitrary elevator 2-K using a collaborative filtering algorithm (step S301 in FIG. 3). Corresponding).

  In step S405, if the value of the evaluation value P (K, i) relating to the elevator 2-K and option i in the input table IT is blank, the value of the blank is calculated, and P '(K, L + i) is entered. Substitute (corresponding to step S302). When P (K, i) = 1, P ′ (K, L + i) = 0 is set (see Expression (4) and Expression (5)).

  In step S406, it is determined whether or not the estimation in step S405 has been performed for all options. If completed, the process proceeds to step S407. If not completed, the process returns to step S405.

  In steps S407 to S413, values are blank for each parameter in the original input table IT, an estimated evaluation value is calculated using a collaborative filtering algorithm, and the calculated value is used as an estimated parameter value.

  In step S407, 0 is substituted into variable j.

  In step S408, the variable j is incremented by one.

  In step S409, the input table IT is copied to the table IT1 having the same size as the input table IT.

  In step S410, the j-th parameter is selected and set as the evaluation target parameter p.

  In step S411, the evaluation value P (K, L + I + j) of the evaluation target parameter p of the elevator 2-K is left blank.

  In step S412, the value of P (K, L + I + j) is estimated using an algorithm for collaborative filtering, and is substituted into P ′ (K, L + I + j).

  In step S413, in order to determine whether or not evaluation values have been estimated for all parameters, it is determined whether or not j <J. If j is smaller than J, the process returns to step S408, where j is J In the above case, the process ends. J is the number of parameters.

  Recommendation candidates are extracted according to the above procedure (FIGS. 3 and 4), and the extracted recommendation items and their estimated values are output to the simulation evaluation unit 8 as recommendation candidates. That is, the parameter / equipment recommendation candidate extraction unit 7 determines the control parameter change value in the elevator facility (recommended building facility) to be recommended based on the operation history data, the building facility status data, and the building facility parameter option data. A retrofit optional device (additional optional device) is extracted as a recommendation candidate.

  In the simulation evaluation unit 8, the operation history data of the elevator 2 -K, the building facility status data stored in each of the operation history data storage unit 4, the building facility status data storage unit 5, and the building facility parameter option storage unit 6, Using the building facility parameter option data and the recommendation candidates extracted by the parameter / equipment recommendation candidate extraction unit 7, the simulation is performed before and after the recommendation candidates are applied, and the simulation results are output to the evaluation result determination unit 9. To do. That is, the simulation evaluation unit 8 is extracted by the operation history data, building facility status data, building facility parameter option data, and parameter / equipment recommendation candidate extraction unit 7 of the recommended elevator facility 2 (recommended building facility). Based on the recommended candidates, evaluation is performed by simulation when the recommended candidates are applied to the elevator equipment 2 to be recommended. The simulation evaluation unit 8 performs evaluation by simulation based on at least the recommendation candidates extracted by the parameter / equipment recommendation candidate extraction unit 7 and the operation history data of the recommended elevator equipment 2 (recommended building equipment). May be performed.

  In order to perform an elevator simulation, data on human movement and a model of an elevator device are required. Data relating to the movement of the person is obtained from elevator operation history data. For example, the number of passengers on the floor and the number of people in the car can be calculated from the amount of change in car load data when the car is stopped (see, for example, Japanese Patent Application Laid-Open No. 2008-247597). In addition, as a method for creating data related to the movement of people from the number of people, for example, there is a method of estimating OD data representing the movement of people from the number of people getting on and off (see, for example, WO99 / 018025).

  Also, as a simulation method, based on the above-mentioned data of human movement, a passenger moving from one floor to another floor at a certain time is generated, a call is generated on the floor where the passenger is generated, and a group management algorithm is applied. The car will run according to the assigned call, and the car will open according to the assigned call.When the call arrives, the door will be opened, the passenger will be placed, the passenger's destination floor will be registered, the door will be closed, and the car will go to the destination floor. It can be realized by sequentially executing a series of events such as opening the door after arrival at the destination floor, lowering the passenger, and closing the door. At this time, the processing time of each event is calculated from a physical model, for example, the speed, acceleration and moving distance of the car, and as the simulation time is advanced, the waiting time and moving time of the passenger are calculated. It is possible. In addition, the number of people in the car can be calculated, and it is also possible to predict the occurrence of a crowded situation or an awkward situation when two people ride. In addition, the time from the generation of passengers to the closing of the door can be calculated from the simulation, and it is possible to be pinched by the door or to estimate the running state.

  The simulation evaluation unit 8 determines, as a simulation result, a value related to the waiting time such as a waiting time, a long waiting rate, a value related to the power consumption, the number of times the door open button is operated, and the number of times the passenger gets on after the door starts to close Output values related to user safety and convenience.

  The evaluation result determination unit 9 compares the simulation results before and after the recommendation candidate application, and determines whether or not the recommendation candidate is actually recommended. That is, it is determined whether or not to recommend a recommendation candidate based on the result of the evaluation by the simulation evaluation unit 8. For example, it may be determined to be recommended when all values included in the simulation result have not deteriorated. In addition, an allowable range may be set in advance for each value included in the simulation result, and recommendation may be made when each value is within the allowable range. In addition, for the recommended item and the recommended option or parameter value, a value included in the simulation result to be improved according to the recommended content is defined in advance, and whether or not the value is improved or the improvement amount is Whether or not to make a recommendation may be determined by determining whether or not the threshold value is equal to or greater than a preset threshold value.

  When the evaluation result determination unit 9 determines to recommend, the recommendation candidate and the simulation result are output to the recommendation result output unit 11 as a recommendation result. When it is determined not to recommend, the recommendation candidate is recommended. The result is output to the candidate extraction condition correction unit 10.

  In the recommendation candidate extraction condition correction unit 10, the evaluation result determination unit 9 receives the estimated value of each parameter as shown in FIG. 4 performed by the parameter / device recommendation candidate extraction unit 7 or an instruction to correct the estimation of the optional evaluation value. The input recommendation candidate is output to the parameter / device recommendation candidate extraction unit 7 as a recommendation exclusion parameter or recommendation exclusion option, and the parameter / device recommendation candidate extraction unit 7 is instructed to perform extraction correction (re-extraction) of the recommendation candidate. To do. That is, the recommendation candidate extraction condition correction unit 10 outputs a recommendation correction instruction to the parameter / device recommendation candidate extraction unit 7 when the evaluation result determination unit 9 determines that the recommendation candidate is not recommended.

  In the parameter / device recommendation candidate extraction unit 7, when a recommendation candidate extraction / correction instruction is input from the recommendation candidate extraction condition correction unit 10, the input recommendation exclusion option or recommendation exclusion parameter is stored, as shown in FIG. 5. In the procedure, extraction and correction of parameters and option candidates are performed. FIG. 5 is a flowchart showing a correction operation of parameter / option recommendation candidate extraction in the parameter / device recommendation candidate extraction unit 7 according to the embodiment of the present invention. 5 is the same as FIG. 3 except for step S501. In step S501, the estimated values of the parameters and the optional evaluation values are estimated according to the procedure shown in FIG.

  FIG. 6 is a flowchart showing parameter and option re-estimation operations in the parameter / device recommendation candidate extraction unit 7 according to the embodiment of the present invention. 6 is the same as FIG. 4 except for step S605 and step S612. As shown in FIG. 6, when the recommendation exclusion option is stored, the evaluation value of the option related to the elevator 2-K is set to 0 in step S605. If the recommendation exclusion parameter is stored, in step S612, if the parameter to be evaluated is the recommendation exclusion parameter stored, the process returns to step S609. As described above, the parameter / device recommendation candidate extraction unit 7 again extracts recommendation candidates other than the recommendation candidates based on the correction instruction input from the recommendation candidate extraction condition correction unit 10.

  When correction of parameter and option candidate extraction is completed in the parameter / device recommendation candidate extraction unit 7, the re-extracted recommendation candidates are output to the simulation evaluation unit 8 again.

  In the recommendation result output unit 11, for example, when the input recommendation result relates to the parameter, the elevator 2-K is instructed to correct the parameter value to the estimated value of the recommendation result. The parameter value correction instruction may also be output to the building equipment parameter option storage unit 6. Moreover, you may make it produce the parameter correction proposal with respect to the owner of elevator 2-K.

  If the recommendation candidate is related to an option, an option proposal may be created for the owner of the elevator 2-K.

  As shown in FIG. 7, the recommendation result output unit 11 is communicably connected to the sales staff and the external terminal 14 of the owner of the elevator 2-K and the elevator equipment 2 via an information network such as the Internet. When the recommendation candidate is output to the recommendation result output unit 11 from the external terminal 14 and the recommendation candidate is output to the recommendation result output unit 11 with respect to the simulation result, the recommendation candidate application instruction is used as the recommendation target elevator facility 2 (recommendation target building). It may be output to (equipment).

  Further, when the recommendation result output unit 11 is communicably connected to the external terminal 14 and the ordering system 15 and a recommendation candidate application instruction is input from the external terminal 14 to the recommendation result output unit 11, the recommendation candidate becomes a recommendation target. You may output to the ordering system 15 so that the ordering process for applying to the elevator equipment 2 (recommended building equipment) may be performed.

  From the above, according to the present embodiment, the control parameter value of the building equipment (building equipment) such as an elevator and the retrofit optional equipment (additional optional equipment) are installed in other buildings as well. Because it was configured to select recommendation candidates based on the operation history, installation status, specifications, control parameters, or option trends of the equipment, verify the effect by simulation, correct the recommendation candidates, and make recommendations It is possible to select a control parameter or a retrofit optional device that is used in other buildings and has a high introduction effect, and can be recommended to the owner or applied to the building. That is, it is possible to recommend control parameters and retrofit optional equipment that improve the performance of the target equipment.

  1 recommendation device, 2 elevator equipment, 3 operation history receiving unit, 4 operation history data storage unit, 5 building facility status data storage unit, 6 building facility parameter option storage unit, 7 parameter / equipment recommendation candidate extraction unit, 8 simulation evaluation unit , 9 Evaluation result judgment unit, 10 Recommendation candidate extraction condition correction unit, 11 Recommendation result output unit, 12 Recommendation result request unit, 13 Recommendation result request unit, 14 External terminal, 15 Ordering system.

Claims (4)

An operation history data storage unit that stores operation history data of a plurality of building facilities including a recommended building facility and other building facilities other than the recommended building facility ;
A building equipment status data storage unit for storing building equipment status data which is information on the installation status of the building equipment;
A building equipment parameter option data storage unit for storing building equipment parameter option data including control parameters of the building equipment and information on optional equipment;
The operation history data, the building equipment status data, and based on the building equipment parameter option data, the recommended target buildings extracted parameter equipment recommendation candidates extracted to the change value and in optional devices of the control parameters as recommendation candidates in facilities And
A simulation evaluation unit that performs evaluation by simulation when the recommendation candidate is applied to the recommendation target building facility based on the recommendation candidate and the operation history data of the recommendation target building facility;
An evaluation result determination unit that determines whether or not to recommend the recommendation candidate based on the evaluation result in the simulation evaluation unit;
A recommendation result output unit that outputs the recommendation candidate when the evaluation result determination unit determines to recommend the recommendation candidate;
A device for recommending parameters and equipment in a building facility, comprising: When the evaluation result determination unit determines not to recommend the recommendation candidate, the evaluation result determination unit further includes a recommendation candidate extraction condition correction unit that outputs a correction instruction for the recommendation candidate to the parameter / device recommendation candidate extraction unit,
The parameter / device recommendation candidate extraction unit re-extracts a recommendation candidate other than the recommendation candidate based on the correction instruction input from the recommendation candidate extraction condition correction unit. Equipment for recommending parameters and equipment in building facilities   The recommendation result output unit is communicably connected to the building facility and an external terminal. When the recommendation candidate application instruction is input from the external terminal, the recommendation candidate application instruction is output to the recommendation target building facility. The device for recommending parameters and equipment in a building facility according to claim 1 or 2, characterized in that:   The recommendation result output unit is communicably connected to an external terminal and an ordering system, and when an instruction to apply the recommendation candidate is input from the external terminal, an order for applying the recommendation candidate to the recommendation target building facility The device for recommending parameters and equipment in a building facility according to claim 1, wherein the device is output to the ordering system so as to perform processing.

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