EP3736517A1 - Method for condition monitoring, condition evaluation and automatic maintenance request for refrigerated cabinets - Google Patents

Abstract

Method for condition monitoring, condition assessment and automatic maintenance request of locally widely distributed refrigeration units (2) with a measuring box (1) assigned to the respective refrigeration unit (2), which comprises a microcontroller (10) and a transmitter / receiver unit (12) in which the measuring box (1) is installed between the mains connection of a refrigerated cabinet and the power plug of the refrigerated cabinet, the measuring box (1) records the electrical current and voltage characteristics of the refrigerated cabinet (12), the recorded characteristics are further processed by the microcontroller (10) into compressed data packets, which Data packets are forwarded to a higher-level central server (3) via a transmitting / receiving unit (12), the data packets provided are evaluated by means of software and a status assessment of the refrigerated appliance (2) is carried out on the basis of the evaluation. In this way, maintenance and repair of the locally widely distributed refrigeration units (2) can be optimized to a high degree.

Description

The invention relates to a method for condition monitoring, condition assessment and maintenance of locally widely distributed refrigerated cabinets with a measurement box assigned to the respective refrigerated cabinet, which comprises a microcontroller and a transmitting / receiving unit.

In the food wholesaling or retailing sector, industrial central systems were originally mainly used for the operation of refrigerators and freezers (interconnected systems). The condition monitoring of these large central systems is carried out by means of their own control system or a higher-level building management system. The safety requirements are very high due to the enormous failure costs in the event of a fault. The effort for this continuous condition monitoring is therefore also economically justifiable.

With more and more frequent concept changes on the sales floor and the legal requirements (F-gas regulation), the use of self-sufficient small cooling units with environmentally friendly refrigerants makes more and more sense. The smaller mobile, so-called plug-in refrigeration units, can be designed as refrigerators and / or freezers. The plug-in refrigerated cabinets have the advantage that they can be used flexibly, as they only need a power connection in the vicinity and can therefore be adapted to the requirements of the end customer in wholesale and retail. In this way, the end customers can present the refrigeration units as needed, for the respective goods, at the optimal location on their sales area. The plug-in refrigeration units have very different design criteria, inconsistent controls with non-standardized interfaces and often changing details of the technical equipment. The variety of manufacturers and thus also the number of device variants is very large, especially in the European market. The end customer expects an optimal maintenance service, whereby this should, if possible, be carried out by a provider of this service and not by different and changing manufacturers of the refrigeration units.

Under these circumstances, it is impossible to enforce a uniform control standard with standardized status parameters and an equally standardized data transmission interface in the respective refrigerated cabinets for a wide range of customers and technologies, and in this way to implement continuous status monitoring of the different model types. The integration into the local infrastructure (WiFi or ISDN connection) is often not possible and would require a technician to reconfigure it every time the refrigerated cabinet is moved.

The end customer expects trouble-free operation without constantly having to find out about the status of their devices. The end customer is basically responsible for the proper cleaning of the refrigerated cabinets and their surroundings, but the proper preventive cleaning of the refrigerated cabinets and their surroundings cannot always be guaranteed. In addition, required cleaning in the housing is only permitted by trained specialist personnel.

The plug-in refrigerated cabinets are also exposed to a wide variety of environmental conditions. They can be used on a mobile basis, so that on the one hand their place of use can change on the sales floor, but on the other hand it is not uncommon for them to be set up at a completely different sales location. Due to these different environmental conditions, a mere condition estimate based on the time of use is extremely imprecise.

All this has the consequence that either very low maintenance intervals have to be selected to check the condition of the system and, if necessary Carry out maintenance measures, or a relatively high risk of failure of the refrigerator and the associated costs in the form of loss of goods and / or replacement of the refrigerator or the unit of the refrigerator must be accepted.

It is therefore the object of the invention, based on a method of the type mentioned at the beginning, to develop a particularly easy-to-install, universally applicable system that can be retrofitted without structural changes and a method to be carried out with it, and consequently to enable the condition assessment of locally widely distributed refrigeration units of the most varied of model types , as well as automatically requesting the maintenance service based on the condition assessment and optimizing material procurement.

To solve this problem, the invention proposes a method with a measurement box assigned to the respective refrigeration unit, which comprises a microcontroller and a mobile radio interface, in which the measurement box is installed between the mains connection of a refrigeration unit and the power connector of the refrigeration unit, the measuring box the electrical current - and voltage characteristics of the refrigeration unit are recorded, the recorded characteristics are further processed by the microcontroller to form compressed data packets, the data packets are forwarded to a higher-level central server via the mobile radio interface, the data packets provided are evaluated using software and a status assessment of the refrigeration unit is carried out on the basis of the evaluation .

The measuring box is therefore simply connected, using plug-and-play, between the power supply and the connector of the refrigerated cabinet. To reduce the amount of data, the measured current and voltage characteristics are compressed into data packets. This does not have to include all of the measured data. Rather, they can be filtered based on time or also according to certain events, such as a significant change in power consumption or the like. From the current and voltage characteristics, the microcontroller can also use the microcontroller to determine the performance parameters, such as the effective power factor and the effective and Reactive power can be calculated. The data packets preprocessed in this way are then forwarded to the higher-level server via the cellular radio interface. With the data packets received, the server can use stored samples to evaluate the condition of the refrigerated cabinet.

Furthermore, it is useful if the measuring box recognizes the model type of the refrigerated appliance when it is switched on for the first time after installation based on stored sample characteristics and the characteristics recorded after switching on and transmits it to the server. With this automatic detection it is not necessary to manually set on the measuring box which model type the measuring box is connected to. It also makes the use of the measuring box even more flexible, because the connected model types can be changed as often as required.

The possibility of program and data updates from a higher-level server via the existing radio interface means that new samples can be reloaded as well as program optimization via remote maintenance.

Based on the information determined in this way, namely the condition assessment, the location of the measuring box and the model type, as well as a maintenance tour database and personnel database (availability and skills), the optimal time for the next maintenance can now be determined using software. In this way, the maintenance tours of the employees can be optimized without running the risk of failure of the refrigerated cabinet due to late maintenance. Due to the high number of monitored refrigerated cabinets and their extensive local distribution, there is a high potential for optimization in the condition assessment in connection with the maintenance tours that are already planned.

It also makes sense if, on the basis of the data determined in connection with a warehouse database, a timed and locally determined material procurement is automatically initiated. Through this measure, storage and material procurement can be optimized in such a way that, on the one hand, storage costs are minimized and, on the other hand, always the right ones Spare parts are available at the right time and in sufficient quantities.

Furthermore, it is advantageous if the ambient temperature is also recorded by the measuring box and made available to the higher-level server. This allows further conclusions to be drawn about the usage and environmental conditions of the refrigerated cabinet. They also serve to improve the modeling in the higher-level computer.

Figur 1:

Ein Blockschaltbild eines Aufbaus zur Durchführung eines erfindungsgemäßen Verfahrens;

Figur 2:

Ablaufdiagramm einer Initialisierung bei einem erfindungsgemäßen Verfahren;

Figur 3:

Ablaufdiagramm bei der laufenden Datenerfassung

Figur 4:

Ablaufdiagramm des serverseitigen Datenempfangs

Figur 5:

Ablaufdiagramm der serverseitigen Datenverarbeitung

Figur 6 und 7:

Diagramme exemplarischer Messwerte

A further development of the method according to the invention provides that the measurement box can transmit its location to the server. This measure has the advantage that the measuring box can be used flexibly at different locations. In addition, by determining the location, conclusions can be drawn about the ambient conditions of the refrigerated cabinet. Transmitter / receiver unit and diagrams explained in more detail. Show it:

Figure 1:

A block diagram of a structure for carrying out a method according to the invention;

Figure 2:

Flow diagram of an initialization in a method according to the invention;

Figure 3:

Flowchart for ongoing data acquisition

Figure 4:

Flow diagram of the server-side data reception

Figure 5:

Flow diagram of the server-side data processing

Figure 6 and 7:

Diagrams of exemplary measured values

In Figure 1 a measuring box is denoted by the reference number 1. The measuring box 1 has a power supply input 11, a radio interface 12 and a power supply output 13. The power supply output 13 is connected to the power supply input 21 of a refrigerator 2. The measuring box 1 detects the performance data of the refrigerated cabinet 2 by means of a current and voltage detection unit 14. In addition, the measuring box 1 has additional sensors 15 which, for example, detect the ambient temperature or humidity. The recorded data are preprocessed and compressed by a microcontroller 10. The freely programmable microcontroller 10 of the measuring box 1 is equipped with an algorithm that enables the acquisition and evaluation of the raw data, the calculation of the performance parameters and the intermediate storage of the calculated data. For example, the microcontroller 10 is able to recognize incorrect measurements and to compensate for them. The data are then sent to a higher-level central server 3 by means of a transmitting / receiving unit 12. The data are transmitted bidirectionally to the higher-level server 3, for example, via the cellular network according to the GPRS / GSM standards or similar. The bidirectional data transmission also enables remote maintenance / remote programming (program update) and remote parameterization (data synchronization) to be implemented.

In this exemplary embodiment, the server 3 comprises two computer units 31, 32 which, depending on the complexity of the overall system, can also be implemented in one physical unit.

The server 3 receives the data via the radio interface 311 of the computer unit 31. The computer unit 31 processes data and forwards the processed data via an interface 312 to the computer unit 32 via its interface 321. The computer unit 32 serves as a master computer (deployment control).

In the following, the data processing is described in more detail in the individual process steps. In Figure 2 the initiating start-up routine of the microcontroller 10 is shown as a flow chart. The aim of this start-up routine is in particular to recognize which type of refrigerated cabinet is connected to the measuring box 11.

The first step is an automatic offset correction for the current and voltage measurement. The offset is determined and stored once by the microcontroller 10 during the initialization. The initial data are then saved.

The first measurement data are then recorded by the refrigeration cabinet 2. It can be useful here to carry out a large number of start cycles in order to determine the most precise information possible about the type of refrigerator 2. The data is then compressed, stored internally as characteristic values and finally sent to the higher-level server 3.

Figure 3 shows the sequence of data acquisition and processing by the locally installed measuring box. First, measurement data are recorded, this process being carried out either continuously or following a specific rule at time intervals. As soon as a sufficient amount of data has been recorded, the data is compressed and stored internally as normal values. The normal values are also sent to the higher-level server 3. The previous compression of the data minimizes the amount of data to be transferred. Once the normal values have been defined, the following recorded measurement data are compared with the normal values. If the measured values do not deviate from the normal value or are still within a predetermined tolerance band, the measured values are not processed further and the measured data continue to be recorded cyclically according to the predetermined rule.

If the measured values deviate from the normal value, this data is also compressed and stored internally and sent to the higher-level server.

Figure 4 shows a flow chart of the data reception and the data assignment in the higher-level server 3. After the data has been received, it is checked in a first step and then, if necessary, brought to the desired data format. The data is then saved internally. It is also checked whether the data transfer was complete. If the received data is not yet complete or incorrect data reception is continued. If necessary, the server 3 can also request the measuring box 10 to send further data or to send the data again.

Figure 5 shows the flow chart of the data analysis on the central higher-level server 3. Here, on the one hand, the data of a local measuring box 1 is processed and analyzed and, on the other hand, the data of all widely distributed measuring boxes 1 are cumulatively processed and analyzed.

When processing the data of all measuring boxes 1, data of the individual measuring boxes 1 are first categorized on the basis of their characteristic values. The data are therefore primarily divided into groups and / or classes of different types of refrigerated cabinets. However, further specifications are then formed from the data obtained in this way and the data assigned to the individual refrigeration units are divided into further specified clusters. For example, the installation site, the ambient temperature, the frequency of the defrosting processes and / or the type and quantity of typical goods can be included. The classification is carried out by an artificial intelligence, which is able to create patterns from the mass of accumulated data sets and to categorize data accordingly. Of course, it is also possible to manually update specific data if this appears beneficial. The data is then graphically processed and stored in a database.

If peculiarities arise, for example a new cluster that was formed by the artificial intelligence, or a data record does not appear plausible, a special report is created and stored in a database. The special reports can then be checked and examined manually and / or by the artificial intelligence directly or at regular intervals.

In the data analysis of a single local measuring box 1, the data are compared with those from the specific cluster to which the local measuring box 1 was previously assigned. It is therefore not a question of the static characteristics of the refrigerated cabinet type (cf. Fig. 2 ), but about the clusters formed by artificial intelligence. The data stored here are not purely static, but can also show tendencies with regard to the degree of wear and soiling of the refrigerated cabinet 2. For this purpose, the data are compared with one another. If the measurement data is within a tolerance band, nothing needs to be done. The routine maintenance cycle which is assigned to the refrigeration cabinet 2 in the respective cluster can be retained. If the data deviate from the tolerance band, a message is sent to the operational planning department so that the changed circumstances can be taken into account and, if necessary, earlier or later maintenance can be carried out. In particular, early detection is important here so that maintenance work is brought forward whenever possible and the refrigerated cabinet does not fail. Rather, in the case of the method according to the invention, maintenance can be carried out during routine use on site when a technician is already there (anyway on site) to troubleshoot another refrigeration unit. In addition, the provision and provision of spare parts for maintenance work can be optimized on the basis of the data obtained and the knowledge gained from it. The material and resource planning can be done manually, but also automatically, by the higher-level server 3.

In parallel to the condition monitoring described above, there is permanent device-specific energy consumption determination, so that comparative information for assessing energy consumption is possible by analyzing the incoming data. The evaluation of the absolute energy consumption is subject to the process-dependent accuracy and is of secondary importance. It essentially serves to reduce the energy consumption of the recorded devices through adapted (condition-dependent) maintenance cycles and is thus a component for implementing predictive maintenance.

Figure 6 and 7th show exemplary measurement curves, which were determined in extensive, weeks-long tests in which various failure, wear and pollution scenarios were simulated. In Figure 5 a pollution simulation was carried out by covering the ventilation slots on the refrigeration unit. After a routine defrosting period, the cover was removed from the ventilation slots. Accordingly, the power consumption of the refrigerated cabinet falls relatively abruptly. With the real one Application, this would correspond to the condition after cleaning. The real, i.e. not simulated, pollution occurs gradually and is also very location-dependent due to the pollution conditions in the area. For example, the ventilation slots of a refrigerated cabinet that is located in a fish department usually get dirty much more slowly than the ventilation slots of a refrigerated cabinet that is located in the fruit and vegetable department. The speed of the pollution process can be taken into account in the cluster formation described above.

Furthermore, in Figure 6 to see a change in performance in the load-bearing curve after overloading the goods was simulated by covering the air outlets in the storage space of the refrigerated cabinet.

This increases the load runtime significantly. However, the power peak drops slightly, as in particular Figure 7 can be seen.

If one compares the two failure scenarios "soiling" and "overloading of goods", it becomes clear that energy consumption monitoring is not sufficient because both cases lead to increased energy consumption. While maintenance work is necessary in the case of soiling, in the case of goods covering, an instruction to the operator is sufficient to load the refrigeration unit correctly. The type of malfunction can be easily determined on the basis of the performance curves.

In general, a detailed performance analysis can be used to draw very precise conclusions about the condition of the refrigerated cabinets from the individual parameters. On the basis of the amounts of data collected from thousands of refrigerated cabinets in the method according to the invention, these conclusions are made more precise, in particular through the use of artificial intelligence. This means that maintenance and repair can be planned and carried out much more efficiently.

Claims (9)

Method for condition monitoring, condition assessment and maintenance of locally widely distributed refrigeration units (2) with a measuring box (1) assigned to the respective refrigeration unit (2), which comprises a microcontroller (10) and a transmitter / receiver unit (12), in which - the measuring box is installed between the mains connection of a refrigerated cabinet (2) and the power connector of the refrigerated cabinet (2), - the measuring box records the electrical current and voltage characteristics of the refrigerator (2), - the recorded characteristic curves are further processed by the microcontroller (10) into compressed data packets, - the data packets are forwarded to a higher-level central server (3) via the transmitting / receiving unit (12), - the data packets provided are evaluated using software - And based on the evaluation, a condition assessment of the refrigerated cabinet (2) is carried out. Method according to Claim 1 or 2, characterized in that the measuring box (1) recognizes the model types of the refrigerated appliance (2) when it is switched on for the first time after installation based on stored sample characteristics and the characteristics recorded after switching on and transmits it to the server. Method according to one of the preceding claims, characterized in that the software determines the optimum time for the next maintenance on the basis of the status assessment, the location of the measuring box and a maintenance tour database. Method according to one of the preceding claims, characterized in that a timed and locally fixed material procurement is automatically initiated on the basis of the condition assessment, the model type of the refrigerated appliance and the location of the measuring box as well as a warehouse database. Method according to one of the preceding claims, characterized in that the characteristics stored on the server are evaluated by means of an artificial intelligence and the artificial intelligence is designed to be self-learning in such a way that patterns are formed and these patterns in connection with historical data draw conclusions about the state and the Enable the conditions of use of the refrigerated cabinet. Method according to one of the preceding claims, characterized in that the measuring box (1) also records the ambient temperature and makes it available to the higher-level server (3). Method according to one of the preceding claims, characterized in that the measuring box (1) also records the air humidity and makes it available to the higher-level server (3). Method according to one of the preceding claims, characterized in that the higher-order central server (3) accesses the measurement box (10) via the transmitter / receiver unit (12). Method according to one of the preceding claims, characterized in that the measuring box transmits its location to the server (3).

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