WO2022111773A1

WO2022111773A1 - Monitoring device for a temperature-controlled storage device, monitoring device having a protective container and method for operation

Info

Publication number: WO2022111773A1
Application number: PCT/DE2021/200186
Authority: WO
Inventors: Amin ZAYANI
Original assignee: Zayani Amin
Priority date: 2020-11-26
Filing date: 2021-11-11
Publication date: 2022-06-02
Also published as: US20240003614A1; DE102020214846A1

Abstract

The invention relates to a monitoring device (1) for a temperature-controlled storage device (3), for example a refrigerator, comprising a first sensing device having a first sensor (4) for sensing the course of activity of a cooling or heating unit (3a); and a processing device (5) which determines at least one characteristic variable for the temperature course in the storage device (3) from the course of activity. The processing device can be in the form of a suitably trained learning system having artificial intelligence.

Description

description

Monitoring device for a temperature-controlled storage facility, monitoring device with a protective container and method of operation

The invention is in the field of electrical engineering and refrigeration or heating technology and is suitable, for example, for practical use in temperature-controlled storage devices, such as refrigerators or warming containers.

Many substances, such as special chemical or pharmaceutically active substances, but also food and substances or objects required for industrial processes, must be stored under certain temperature conditions. These include not only the storage temperature, but also, if applicable, temperature profiles, minimum and/or maximum temperatures or maximum times for which it is permissible to exceed or fall below certain specified temperatures.

Storage devices such as refrigerators usually have units for heating or cooling, whose activity, ie the operation or the power for heating or cooling, is controlled with a control device, with the actual temperature usually being measured for the control. The threshold temperatures for switching a unit on or off, as well as the heating or cooling capacity and the efficiency of the units can change over time and the temperature measurement can be faulty and have drifts. The hysteresis between the switch-off threshold of the unit and the switch-on threshold can if sway. In practice, for example, refrigerators used in households show surprisingly large temperature fluctuations, which often go unnoticed, since the cooled objects do not necessarily spoil if the temperature fluctuations are not too long. However, pharmaceutically sensitive substances can easily deteriorate or become ineffective if the temperature exceeds or falls below certain values, which is often not apparent or detectable for the end user. This applies, for example, to insulin, which diabetics often have to store in a refrigerator for a certain period of time. For example, insulin can quickly become ineffective if the temperature falls below 2 degrees Celsius or if it exceeds 8 degrees Celsius.

In this situation, the present invention is based on the task of creating a monitoring device that determines certain parameters of the temperature profile for the past and the present with the least possible effort and forecasts them for the future, so that certain temperature parameters can be easily determined.

The object is achieved according to the invention by a monitoring device for a temperature-controlled storage device with a first detection device with a first sensor for detecting the course of activity of a cooling or heating unit and with a processing device which, from the course of activity, generates at least one parameter for the Temperature profile determined in the storage device.

The first detection device uses the first sensor to detect a history of the activity of a unit over the Time. The sensor can record the intensity of the activity, i.e. a heating or cooling capacity, or just the information that the respective unit is in heating or cooling mode. Usually, in many storage facilities, only the unit is switched on and off for control purposes, so that the temperature reached is derived from the duration of operation or from the duty cycle, i.e. the ratio of the phase durations of operation and the phases of inactivity.

The first detection device can therefore also determine parameters of the temperature profile exclusively from the digital information as to whether and for how long the unit is switched on and off. For example, these variables can be used to determine how large the temperature differences are between the individual operating phases of the unit.

This depends, for example, on the absolute temperature in the storage facility, the outside temperature and the maximum period of inactivity of the unit and the contents of the refrigerator, e.g. B. if uncooled substances have just been stored. A cooling or heating unit can either consist of a compressor or a heating device, but it can also include means for distributing a heating or cooling medium as a sub-unit. Thus, additional fans are often provided in refrigerators, which are used for air distribution in the refrigerator. Similar Umwälzvorrich lines can be provided for heaters. In refrigerators, in which a liquid cooling medium is usually provided for the cooling circuit, a pump can also be provided for transporting this cooling liquid. The activity monitoring of a cooling unit can therefore, for example, monitor and record the activity of the compressor when the fan is switched off and/or the monitoring monitoring and recording the activity of the fan when the compressor is switched off and/or the joint recording of the activities of the compressor and fan during operation and additionally optionally also the monitoring and recording of the activity of a coolant pump.

For this purpose, a reference measurement with a direct temperature measurement can first take place in order to generate reference data for the activity combinations described above or just the activities of one or more of the elements mentioned, with which the activity profile of the unit can later be compared in order to obtain the temperature data from this derive. For example, reference measurements or training of the device can always take place with the fan switched off and later analyzes can focus solely on monitoring a compressor. Alternatively or additionally, the activity data of the fan can be recorded separately as reference data and later compared with operating data to determine an aging condition. Finally, fans and compressors can also be recorded to determine reference data or for training in joint operation.

For a reliable interpretation of measurement data, the monitoring device can receive and take into account information about certain exceptional states or normal states such as defrost phases. De-Frost phases are used for regular, temporary, targeted heating to remove icing. During such phases, the measurements of the monitor may be suspended or interpreted in a different way than during normal operation. These phases can also be taken into account when training the monitoring device and, for example, can be omitted for the acquisition of training data.

In addition to the activity data of the respective unit, the temperature curve can also depend on the condition, for example the aging condition of the unit or the system, for example also on the condition of a cooling or heating medium. As the system ages, the temperature control changes its behavior so that, for example, the respective unit is switched on more or less often or the respective activity durations until a temperature threshold is reached increase or decrease. This data can also be recorded by the recording device and taken into account by the processing device. In the monitoring device, for example in the processing device, predefined, static data can also be stored that influence the interpretation of continuously recorded data, such as a device type of the storage device, design, for example with or without ventilation, year of construction and mode of operation of the storage facility, for example a refrigerator, whether it is for daily use and is opened about 20 times a day, or whether it is a storage refrigerator that is only opened a few times a week, or a professional pharmacy refrigerator very frequently, but only within certain pharmacy opening times.

In this way, temperature curves can be determined both for the past unit and for the future during ongoing monitoring of the activities of a heating or cooling unit by the processing device. This can be done by directly comparing the measurement data with reference data, in particular special based on a similarity metric or also by a trained neural network or another automatic learning device or another device with artificial intelligence. For this purpose, the monitoring device receives data that shows whether there is a significant malfunction during operation. This can be done, for example, by signaling the monitoring device, for example entering it, when an error is detected during operation. This can be the case, for example, for repairs. During training, the monitoring device then learns about the activity patterns that lead to a repair. It can also be specified before the training that an error is assumed as soon as a specific threshold measured value of a detected variable is exceeded or fallen below. This can be, for example, the duration of an activity phase of the compressor and/or fan or the duration between two activity phases of the compressor and/or fan. The threshold reading may also be a loudness level of compressor and/or fan activity, or a loudness level in a particular frequency range. Ultimately, an error can also be defined by the fact that a certain temperature value, determined simultaneously at least during the training phase, is exceeded or fallen below at all or for a certain minimum duration.

Accordingly, in addition to the first detection device with the first sensor, a second detection device with a second sensor in the form of a temperature sensor can also be provided. In this case, the temperature is also recorded immediately, either only during a training phase or continuously during operation. The course of the temperature can also be predicted for the future, since the state of the System can be precisely determined by comparing it with reference data, so that both the aging condition of the aggregate and, if applicable, the condition of a heating or cooling medium and other boundary conditions can be determined and taken into account with or without direct measurement.

In order to implement the first detection device, it can be provided that the first sensor is an acoustic sensor, a vibration or acceleration sensor, a current or voltage sensor or a sensor for an electric or magnetic field.

In principle, each such sensor can detect the activity of a cooling or heating unit. For this purpose, either an operating noise or an electrical, magnetic or electromagnetic activity of a motor or a valve or switch is detected, for example. The efficiency can be determined from the running time of the unit per heating or cooling cycle, and a signature, for example an acoustic signature, of the unit can also represent its aging status. The acoustic signature can be in the form of the frequency spectrum of the operating noise of a compressor and/or fan or pump, which is reached, for example, at start-up or after a defined operating time, for example a few seconds, or before switching off in a cooling phase. The signature may also be the evolution of the frequency spectrum during a period between start-up and shutdown of an element of the unit. For example, it can be monitored whether certain frequency components appear with high intensity in the spectrum when starting and whether their intensity decreases towards the end, or vice versa. returns. However, it can also be decisive whether certain frequency components occur at all in the spectrum or not.

A sensor can also be used to detect the activity of a ventilator, which is used, for example, to distribute air or to transport air in the storage facility. For example, the noise of the air flow in the storage device and/or the running noise of the fan can be recorded. This means that both the quality of the air distribution and the aging status of the fan can be monitored, since it has an acoustic signature, for example, that reflects its aging status or damage or defects.

The monitoring device can advantageously have a self-sufficient energy supply device that is independent of the energy supply of the storage device. This self-sufficient energy supply can be provided by a battery or an accumulator, i.e. an electrochemical energy source, but also by an energy generating unit that, for example, generates electrical energy from temperature fluctuations, for example from material movements caused by temperature fluctuations or from thermal voltages or from light radiation. The monitoring device can thus be operated without a connection to the storage device, ie, for example, electrically isolated from it and without an electrical coupling to the storage device. Installation costs for the monitoring device are thus eliminated, as is susceptibility to errors due to errors in the storage device. The monitoring device can thus work without being connected to the storage device and can simply be inserted or placed into it for operation. It is also conceivable that a Coupling to the energy supply of the storage facility exists or is established exclusively for the regular charging of energy stores/batteries/rechargeable batteries. This ensures that the monitoring device is not connected to a 50 Hertz network during operation and the resulting disruptions are avoided. Alternatively, a DC power supply can be used for power supply, which is very well electrically shielded and decoupled and acoustically isolated in order to suppress the 50 hertz interference frequency and harmonics thereof.

The monitoring device can additionally have a third detection device with a third sensor, the third sensor detecting whether the storage device is in an open or closed state.

In this way, it can be monitored in a refrigerator whether and how long the refrigerator door is open and how often it is opened. This allows the actual temperature to be determined or predicted. For this, too, reference data can be used which can be obtained when the storage device is opened repeatedly. For example, by opening the refrigerator door, a location-dependent temperature distribution can be generated in a refrigerator, which affects the operating behavior of the refrigeration unit because the temperature sensor used to control the refrigerator is located either far away from the door or close to the door. A temperature change due to the door being open must therefore be evaluated differently and leads to a different behavior of the control system than a uniform increase in temperature when the cooling unit is inactive due to heat conduction. The monitoring of the door or other special events, such as loading or unloading the storage When training the monitoring device, this direction can also be used to obtain the training data predominantly or exclusively in periods in which the storage device is not opened or loaded and unloaded, in order to focus the monitoring on the functioning of the compressor and/or the fan .

It can basically be provided that the third sensor is a light sensor or a position sensor for detecting the position of a door or a locking element of the storage device. Further sensors can also be provided for monitoring purposes, for example a humidity sensor in the storage device or in a protective container in the storage device. Humidity can be monitored along with other parameters to provide a comprehensive data profile for stored materials or items over time, or to forecast. One or more weight sensors can also be provided on the shelves of the storage device for detecting a loading or unloading process.

In addition, it can be provided that the processing device has a device for Fourier transformation of the time-dependent data recorded by at least one of the sensors.

Since the undisturbed behavior of the temperature control basically has a periodic structure, it is advisable to compress and structure the operating data by determining the operating frequency and other periods. In addition, the measurement data is also anonymized, which makes sense, for example, when recording acoustic data. can be full, as these can also contain data subject to data protection, such as human communication. A Fourier transformation can be used to determine both the regularity of switching the unit on and off in the very low frequency range (cycle time e.g. 10 min or 20 min) and the acoustic signature or the frequency spectrum in the range from a few Hertz up to, for example, 16 kHz can be detected.

It can also be usefully provided that the processing device has a storage device for the recorded data and/or the Fourier-transformed data. This allows the data to be collected and evaluated over a longer period of time, which is particularly important when determining development trends over time.

In the case of the monitoring device, it can also be provided that the processing device has a device for comparing the recorded data or the Fourier-transformed data with reference data, which is set up, in particular trained, to derive from the comparison one or more parameters of the temperature profile in the storage device and /or to determine one or more parameters for the condition of the cooling or heating unit and/or the insulation condition of the storage facility or the condition of a liquid coolant.

The recorded data can on the one hand enable the behavior of the storage device and the temperature to be assessed for the past, in particular for the period in which the data was recorded. If necessary, parameters of the device, in particular the aging condition of the compressor, the fan, the Cooling medium or drifts in the regulation as well as the temperature or the temperature profile for the time before or after the collection of data - i.e. also for the future - are determined or forecast. After automatic assessment of the temperature profile and determination of whether temperature and/or time thresholds are exceeded or not reached, warning signals can be generated from this. These can signal to an operator or a user that conditions have occurred or will occur in the past, present or future which endanger the undisturbed state of substances or objects within the storage facility.

A simple implementation of such processing can provide for the processing device to determine the temperature profile in the storage device and in particular the temperature profile of a substance or object stored therein from the recorded data. The nature of the stored substance, its heat capacity and, if applicable, a heat transfer coefficient and/or an isolation can play a role here. This can be particularly important if the substance or object stored in the storage device also has a protective container or insulating container - possibly with its own considerable heat capacity - or is located in such an insulating container. In such cases, it is advisable to obtain corresponding reference data using a protective container of the same type, whereby the temperature of the stored substance can be measured inside the protective container for comparison. With such measurement data, an AI module, i.e. a module with artificial intelligence, such as a neural network, can be trained accordingly. Some of the sizes mentioned can can also be determined from measurements of the activity profiles and/or temperatures. For example, the load status can be determined by observing the duration of activity of the compressor and/or fan per cooling cycle set by the controller or the idle time between two operating cycles of the compressor based on data obtained during training.

In the monitoring device described, it can also be provided that it has a device for displaying or outputting the parameters determined and/or the course of activity of a cooling or heating unit and/or an alarm signal. This can, for example, be a conventional digital display or a simple illuminated display, which can also be designed as a color traffic light. A sound generator can also be provided for the output of acoustic warning signals.

The monitoring device can, for example, also have a transmitting and/or receiving device for wireless communication, in particular for the output of alarm signals or display data on a terminal device. The wireless communication can use, for example, Ethernet, Wifi, long-range radio or a mobile communication standard or NB-IoT. Since storage facilities often include metal housings, either an electrical feedthrough for an antenna wire or an opening in the metal housing, such as a slot antenna or a glass/non-metal window, should be provided for wireless communication. In many cases it will be sufficient to route a thin antenna line out of the housing of the storage device, for example through a door seal. In addition to a monitoring device of the type described above, the invention also relates to a protective device with a protective container for storing substances and/or objects and with a monitoring device of the type described above. The monitoring device can be integrated into the protective container, for example and furthermore, in addition to a temperature sensor in the storage device or instead of it, a sensor for monitoring the temperature inside the protective container can be provided and the measurement data from both temperature sensors can be processed by the processing device - both in the training phase and in normal conditions Operation. The protective container in particular can have a container wall which consists at least partially of a material which has a phase transition in a temperature range between 2 and 8 degrees Celsius. In addition, the material can be integrated into the container wall in such a way, in particular enclosed in it, that the phase transition can be repeated several times without generating a change in shape of the container wall. It can be considered that the container wall has one or more cavities in which the material that undergoes a phase transition in the temperature range mentioned is located. The phase transition can take place between a solid and a liquid phase. In this case, the material is held in a cavity in its liquid state.

However, a material can also be provided which undergoes a phase transition between two different solid modifications in the critical temperature range, so that there is no risk of a change in shape. The protective case may be made, at least in part, of a typical insulating material such as foam or natural insulating material such as cork or cork composite or it can have evacuated cavities for thermal insulation.

A substance with a large specific heat capacity can also be integrated into the protective container, for example inside the insulation, which has a storage capacity for a specific temperature and slows down temperature changes inside the protective container. The monitoring device and in particular the protective container with such a monitoring device can be connected to a power supply for the storage device, but it/he can particularly advantageously have a self-sufficient power supply device which is independent of the power supply for the storage device. This self-sufficient energy supply can be provided by a battery or an accumulator, i.e. an electrochemical energy source, but also by an energy generating unit that generates electrical energy, for example, from temperature fluctuations, for example from material movements caused by temperature fluctuations or from thermal voltages or from light radiation. For example, bimetal elements, Peltier elements or photo semiconductors/solar cells can be used for this. The Peltier element can, for example, be integrated into a wall of the protective container and convert the temperature differences between the interior and the outside of the protective container into electrical energy. In addition, it makes sense to monitor this self-sufficient energy supply, which emits alarm signals via a wireless connection if the energy supply to the monitoring device is not permanent or is likely to be at risk.

The invention also relates to a method for operating a monitoring device of the type described above Type in which it is provided that the measured temperature/time profiles and in particular also measured acoustic signals or measured signals of a vibration sensor are Fourier-transformed and compared in the Fourier-transformed form with reference data and that from the comparison at least one parameter for the temperature profile detected in the temperature-controlled storage facility. The parameter for the temperature profile can be, for example, a minimum or maximum temperature of a cooling cycle or a point in time in the past or future at which certain temperature threshold values are undershot or overshot or at which the duration of the undershooting or overshooting of a temperature threshold value is a certain one exceeds the specified duration.

A corresponding monitoring of a protective container located in the storage device and its interior can also be provided. When the protective container is in the storage device, its thermal properties can influence the temperature behavior of the storage device, for example because temperature changes in the storage device are slowed down by the thermal capacity of the protective container.

The same applies to the temperature prevailing in the protective container: the behavior of this temperature depends on the temperature in the storage facility as well as on the heat capacity and the insulating capacity of the protective container.

In order to be able to determine the temperature profile inside the protective container or outside the protective container in the storage facility, reference data for these variables should be available in conjunction with corresponding accumulators measured at the same time. Activity profiles of heating and/or cooling units are available, so that the temperature profile for the past, present or future can be determined using the comparison data depending on the actual activities of the unit(s) and the other currently measured sensor data.

Finally, the invention also relates to a method for training a monitoring device of the type described above for monitoring a storage device, in which at least the temperature in the storage device, in particular or additionally in a protective container within the storage device, and the course of activity are continuously monitored of a heating or cooling unit is measured and reference data is determined from this. In principle, the determination of reference data can also be understood within the scope of the invention as the training of a learning device, which, after the corresponding training, uses measured values of the activity profile of a heating and/or cooling unit and, if necessary, additionally continuously measured temperature data and, if necessary, other additionally measured data data can determine temperature profiles for the past or future. Other additionally measured data can be, for example, the opening hours of the storage facility. The learning device can have, for example, a neural network or a software module containing AI (artificial intelligence) and this can use machine learning (supervised or unsupervised).

The determination of reference data or the training of the learning device can take place in exactly the same storage device whose temperature curve is to be determined later or in a similar storage furnishings. The determination of reference data or the training can also take place in a different type of storage device and then the reference data or the learning state can be transferred by a transfer function if both the boundary conditions of the device on which the training is carried out or on which the reference data are determined and the boundary conditions are sufficiently known to the facility at which the monitoring equipment is used. The data on which the processing is based can be divided into static and dynamic, continuously recorded data. The static data are those that can be specified and are largely unchangeable. These include the design, year of construction and the device type of the storage facility, its size, type of ventilation and, for example, its geographic location, which is responsible for both the power supply (110 volt supply voltage or 220 volts) and for the usual temperature fluctuations outside the Storage facility, such as daily, weekly or seasonal fluctuations is relevant.

For example, the following 3 types of pattern recognition/classification/training are conceivable for training:

Fridge Profiling:

Classic unsupervised machine learning takes place, for which about a week should be sufficient (5 weekdays and nights + weekend) to establish a basis for a single refrigerator. After one year of operation, a "long-term profile" results, which also covers the seasonal variability).

Fault and defect detection: The aim here is to determine a fault diagnosis for refrigerators based on sensor data. This requires more extensive training, in which certain faults must be visible, brought about or simulated (e.g. fan faults, compressor faults, lack of refrigerant, etc.)

Event detection:

Extensive training is also necessary for this, with special conditions that are to be recognized later, e.g.

B: Introduction of larger uncooled masses, etc. can be brought about in a targeted manner.

The training can begin as Fridge Profiling and after a short time lead to the operational capability of the monitoring device. The training can later be extended to items 2 and 3 in order to enable the monitoring device to also detect more complex faults or general states. For training and/or for operation, the monitoring device can partially process data itself, but at least partially recorded data can also be transmitted via data communication to a server and processed there, possibly after preprocessing. Data recorded on the server from different monitoring devices can be compared or linked with one another, so that, for example, a broad base of training data is obtained, which accelerates the training processes of each individual monitoring device and also later operation and improves the quality of the processing of data, in particular the improve the quality of forecasts. The temperature can be continuously measured in the training phase and/or in the operating phase, i.e. exclusively in the training phase, at least in the storage device, when using a protective container outside of this protective container and/or inside the protective container. In a particularly advantageous embodiment, the temperature is measured at at least 2 points:

Inside the protective container, because it is about the quality assurance of medicines that are stored inside the protective container.

Outside the protective container in the storage facility/in the refrigerator): so that the temperature trends in the refrigerator can be recognized without distortion.

For example, the parameters of minimum and/or maximum temperature of a cycle in and outside of the protective container, cycle length and duration of operation of an unit and the time between two operating phases of the unit can be continuously determined. In addition, frequency spectra of a heating/cooling unit or a fan recorded by an acoustic sensor or vibration sensor can be determined and characterized by parameters such as peak heights at characteristic frequencies, total intensity, partial intensity in certain frequency ranges and the ratios/quotients or differences between these Partial intensities or Fourier transforms and their characterization parameters. In addition, air humidity values inside and/or outside the storage facility, their range of fluctuation, minimum, maximum and cycle times can be determined. All these quantities and, for example, their rate of change Speeds and possibly other variables can be used as a basis for training and later monitored and compared with the training data or further processed with the trained processing device to potentially generate signals.

It is thus possible to calculate the time over which the temperature remains below 8 degrees or above 2 degrees in the event of malfunctions in the storage facility in the protective container. A prognosis signal can then be output, e.g. B: "Caution, the refrigerator is no longer cooling properly and the temperature in the protective container will remain between 2 and 8 degrees for xx hours". Such a prognosis is particularly possible if the temperature inside and outside the protective container is recorded and It can also be advantageous if the thermal capacity of the protective container and the heat transfer values or thermal conductivity values are known.

The invention is shown below with reference to figures of a drawing and described below. while showing

Figure 1: a storage device in the form of a refrigerator,

Figure 2: a protective container in perspective view,

FIG. 3: a protective container in a plan view, FIG. 4: a schematic of a monitoring device, FIG. 5: first measurement data that serve as training data, FIG. 5a: a temperature profile with characteristic disturbances,

Figure 6: second measured data that are evaluated, FIG. 7: third measured data that are evaluated, as well as

Figure 8 schematically shows a flow chart of the operation of the

monitoring device.

FIG. 1 shows a refrigerator 3 as a typical application as a storage device, in which a protective container 2, for example with a drug such as insulin, is stored. Other possible storage facilities can be cold rooms, pharmacy refrigerators, but also warming containers, for example incubators or fermentation containers, for example for alcohol production. Such Einrichtun gene usually have a heating or cooling unit that works temperature-controlled in intermittent operation. In the figure 1, the cooling unit is denoted by 3a.

Finally, a refrigerator door is denoted by 3b. Opening the refrigerator door affects the temperature control in such a way that additional or more frequent operation of the cooling unit becomes necessary.

The invention is based at least in part on the fact that the operation of the cooling or heating unit and the opening or closing of a door/opening can be monitored non-invasively, ie without an electrical connection to the device.

For this purpose, the operation of the cooling unit 3a can be monitored acoustically by a microphone, for example. In extreme cases, only the operation itself, i.e. the beginning, end and duration of the individual operating phases, can be recorded. More revealing is the monitoring of noise and frequency spectra by one or more microphones, which mutually through the appropriate frequency characteristics he can complement. In this case, for example, condenser microphones can be used, which can be encapsulated particularly well. But it is also possible to use other types of microphones, such as MEMS microphones, which are used, for example, in mobile phones. Analyzing acoustic signatures picked up by microphones due to airborne sound has been shown to be more successful than analyzing structure-borne noise picked up by a microphone. For the analysis of structure-borne noise, a microphone can be brought into direct contact with a fixed component of the storage device. The structure-borne noise recorded in this way can be evaluated, for example, in addition to the analysis of the sound picked up through the air, and through the structure-borne noise recording, interference noises can be identified that have nothing primarily to do with a cooling or heating unit and for the analysis of the sound picked up through the air can be eliminated.

Alternatively, a sensor for detecting the power consumption of the unit, the voltage or an electrical, magnetic or electromagnetic field can be provided. A refrigeration unit can be designed as an electric compressor with a motor that, in addition to operating noise, i.e. acoustic signals, also consumes electricity and produces electrical, magnetic and electromagnetic fields. The Kühlag gregat can also have a fan whose operating noise can be monitored as well as the air flow noise generated by the ventilation.

FIG. 2 shows a protective container 2 in the form of a box with a lid, in which medicines are stored, for example can become. The protective container can have thermally insulating walls, for example with a foam/foam material, an insulating natural material such as cork or an aerogel. In addition, the protective container can also have an element with high thermal capacity, for example a gel or water container, which dampens the temperature fluctuations in the protective container in the event of external temperature fluctuations in the storage device, i.e. equalizes the temperature. Both the additional insulation and the element with a high heat capacity can be arranged in the area of the container walls, on the inside of the container walls or in the walls of the protective container.

FIG. 2 shows a monitoring device 1 installed in the protective container 2, which will be discussed in more detail below. Side walls of the protective container are denoted by 2a, 2b. Such a monitoring device 1 can also be used on its own without a protective container for monitoring a storage device.

3 shows a protective container 2 in an open view from above with side walls 2a, 2b and a phase change material 2c integrated into a side wall 2a as a heat accumulator with an object or substance 11 stored in it and with a monitoring device 1. The material 2c can have a Have phase transition in the range between 2 and 8 degrees Celsius, preferably between 2 and 4 degrees Celsius. The monitoring device 1 has a first sensor 4, which detects the activity of the cooling unit, for example a microphone, and a second sensor 6 for detecting the temperature in the vicinity of the protective container. This second sensor is arranged on the outside of the protective container 2 . In the case of the In the second construction, the monitoring device is integrated into the wall of the protective container in such a way that part of the monitoring device faces the outside of the protective container, in particular forms part of the outer wall, and another part communicates with the inside of the protective container. The monitoring device also has a third sensor 7, which monitors the opening status of a door of the refrigerator, i.e. it is designed as a light sensor, for example, in order to either detect ambient light entering the storage device from outside or the light of a lamp of the storage device itself, which is automatically switched on when it is opened capture. However, the sensor for the state of the door being open could also be formed, for example, by a position sensor on the door or by a sensor for a draft in the storage facility.

In addition, a further temperature sensor 60 can be provided in the monitoring device, which monitors the temperature inside the protective container and points towards the inside of the protective container.

A monitoring device 1 is shown schematically in FIG. 4 with a few additional elements. In addition to the first, second and third sensors 4, 6, 7 and the sensor 60 for the temperature in the protective container, the monitoring device has a processing device 5 for the sensor data, which is connected to the sensors via signal lines or wireless connections. The processing device has a device 5a for Fourier transformation of the essentially periodic data. The Fourier transformation compresses the data, which also ensures, for example, that acoustic data recorded via a microphone is sufficiently alienated so that, for example, randomly recorded human speech is only processed further in a highly alienated form. The processing device also has a memory device 5b in which training/reference data are stored, with which currently measured data are compared. The memory device can also be formed directly, in part, by a neural network in which data are stored by structuring the nodes and their connections through training. Results of the comparison and assessment of the condition of the storage device or its elements can also be stored in the storage device 5b. The processing device also has a module 5c, which can be in the form of a learning system if this is not already implemented by a neural network and which contains elements of artificial intelligence. This module can assign the recorded or Fourier-transformed data to various statuses of the storage facility or its elements, such as the heating/cooling unit or the insulation of the storage facility or a heat transport fluid/a cooling liquid, which can result in the output of an alarm signal . For this purpose, the processing device also has a display device 8 and/or a transceiver 9 for wireless communication according to a common standard. Alarm signals can then be received by a terminal 10, for example in the form of a smartphone or tablet computer or a wearable worn on the wrist, and signaled to a person optically, haptically or acoustically.

The individual sensors can generally record the following measured values or parameters: The temperature and/or humidity sensor in the protective container allows a log to be drawn up on the course of these variables and is therefore used, for example, for quality control of medicines.

The temperature and/or humidity sensor in the storage facility outside the containment vessel allows the performance of the facility to be monitored and together with the sensing of other variables, future predictions.

With the latter temperature sensor, the time cycles of the cooling, the cooling rate, maximum and minimum temperature of temperature control cycles can be recorded.

The compression cycles, the acoustic signature of heating and cooling units and fans, volume and operating time within a compression cycle can be recorded by an acoustic sensor. In addition, the switching of relays or on/off switches and the speed of fans can be acoustically recorded.

A vibration and/or acceleration sensor can be used to monitor vibrations and movements in the vicinity of the storage device, vibrations caused by the operation of aggregates, movements of the protective container and also the orientation of the protective container and the storage device. Thus, for example, incorrect positioning of the protective container or insufficient horizontal alignment of the storage device can be detected.

Overall, some variable sizes can be determined by using the sensors and the underlying structure can be learned in the training phase, such as the length and the profile of temperature cycles, the cooling/heating efficiency of a unit or the entire storage facility, the thermostat drift as a function of time, and the usage profile when loading and unloading goods to be temperature-controlled.

As a result of processing continuously recorded data on the basis of static, specified parameters, training processes and continuously recorded measurement data, the following 3 types of outputs/signals can be produced, for example:

Reports on the status of elements of the storage facility or substances/objects stored in it, such as medicines, alarm signals that provide information about malfunctions and are intended to initiate countermeasures, as well as tips and recommendations for optimization, e.g. warnings of imminent malfunctions, forecasts and tips optimized maintenance.

In FIG. 5, the time is plotted on the horizontal axis in a coordinate system and various measurable signals are plotted on the vertical axis. The step function 4a reflects the operating state of a refrigeration unit with the function values zero (switched off) and 1 (switched on). It turns out that the unit according to FIG. 5 is always switched on for a constant, short period of time.

With 7a the signal of the sensor for the door opening is designated net. There is only a single period of time seen in the chart when the storage facility/refrigerator door is open. The curve 6a shows the temperature profile in the storage device superimposed on the other signals. On the one hand, this is characterized by a slow rise in temperature inside the storage device as long as the cooling unit is switched off. This is due to the heat transport through the insulation of the storage device from the warmer outside to the cooler inside the case. During operation of the cooling unit, the temperature drops again, only to rise again slowly after the unit is switched off. Opening the refrigerator door usually results in an upward jump in temperature, denoted by 16 in the example shown, since warm air enters the refrigerator. If the refrigerator is only open for a short time, the temperature partially drops again after the door is closed, since the opening time is usually not long enough to warm up the solid parts of the refrigerator, so that they partially cool the air in the refrigerator again after the door is closed . With 17 a temperature rise is called, which is to lead back to the introduction of drugs that have a higher temperature than the refrigerator temperature. The temperature is lowered during the next operating phase of the refrigeration unit, but the heating effect of the medication can last for several more cycles.

FIG. 5a shows measurement data for the temperature over a few hours and a larger number of operating cycles of a refrigeration unit, with 17 again indicating a fault due to the storage of substances at a higher temperature and 18 indicating a fault in the control of the refrigerator. The processes described and their correspondence with the temperature profile can be recorded and analyzed over a longer period of time, for example over days and weeks. After a short time, the processing device can itself produce forecasts about a future temperature profile and compare these with the actual temperature profile. This trains the processing device to such an extent that the predictions about the temperature become reliable. It is then also conceivable that the temperature is no longer measured and the behavior of the storage device is determined solely from the behavior of the unit. Statuses from the past can also be determined by analyzing stored activity data, so that it can also be determined whether the temperature fell below or exceeded certain thresholds in the past.

Certain additional information can also be stored in the processing device before, during or after the training, which is helpful for the analysis and prognosis, for example how long a cooling unit of a certain model of a refrigerator should be in operation at most until the lower temperature threshold is reached, or how closely two activity/operational phases of a unit should be at least apart in time. These variables depend, among other things, on the quality of the insulation, the performance and efficiency of the unit, the age of the cooling medium and the load status of the refrigerator, with the structure of the dependencies being similar for a number of refrigerators or models. This significantly reduces the training time. The special cases mentioned, that the interval between two operating phases of the unit fluctuates and that an operating phase of a unit is longer than usual borrowed, are shown in the diagram of FIG. 6 by way of example.

FIG. 7 shows an example of the case in which the refrigerator door is open for a longer period of time after an activity phase 4a of the refrigeration unit (7a). This can, for example, lead to a rise in temperature that triggers an alarm signal.

Steps of the operating method of the monitoring device are shown schematically in FIG. In a first phase 12, the monitoring device is trained by continuous data acquisition of operating data and storage of any known additional data. In the following steps 13, 14 and 15, operating data is recorded and compared with the stored data structures. If a temperature threshold is exceeded for currently measured operating data, an alarm signal is output. If no temperature threshold is exceeded and this is also not foreseeable for imminent periods of time, no alarm signal is output and further operating data are measured in steps 14, 15. If a temperature is continuously measured in the storage device and/or in the protective container, the processing device can continue to learn and continuously improve its forecasts.

Longer-term trends can also be determined, such as an increase in the operating times of the unit, since this reduces its performance or the cooling liquid transports the heat less well. In this way, leaks in a compressor can also be detected or predicted at an early stage. Basically, in a first phase, the monitoring device can record the measurement data with the available sensors and allow remote monitoring via a radio link. At the same time, the measured values can be saved in order to create suitable logs that allow quality management for the goods stored in the storage facility. Also at this stage, temperatures within the storage facility inside and outside the containment can be directly compared to confirm the effectiveness of the containment's protection. Already in this phase, certain critical situations can be indicated by alarm signals, such as a power failure, a door that has been open for too long, an incorrect temperature setting. In addition, it can be shown how long an acceptable temperature in the protective container can be guaranteed if the temperature control fails.

In a second phase during and after a training phase, the following additional information or signals can be generated by a processing device or a server supplied with the data: suggestions for seasonal settings of the thermostat, information on predictive maintenance with this supporting information, for example about the cooling efficiency, showing the probability of failure of aggregates based on the acoustic signature, which depends on the degree of wear or damage that has occurred.

For example, “supervised machine learning” can be used as a training method in the laboratory, in which the system is specifically brought into special states, for example error states, and correct or desired reactions are specified will. Alternatively or additionally, in particular according to "supervised machine learning", training can be carried out on the basis of "deep learning" with a large number of situations that have actually occurred and the associated data. For this purpose, data can also be used that have not been processed by the individual processing device itself, but originate from other systems/storage devices, are stored on a server with which the processing device is connected, and which refer to the individual system at least in ge are applicable to some degree.

During operation, the monitoring device or a protective container with a monitoring device can be supplied with energy by means of a battery or an accumulator. This achieves complete decoupling from the power supply to the aggregates or other elements of the storage facility. Operation can only be interrupted to charge the batteries and a connection to an alternating current network can be established, for example also by means of the internal supply lines of the aggregates of the storage facility.

Claims

patent claims

1. Monitoring device (1) for a temperature-controlled storage device (3).

- A first detection device with a first sensor (4) for detecting the activity profile of a cooling or heating unit (3a) and with

- A processing device (5) which determines from the activity course at least one parameter for the temperature course in the storage device (3).

2. Monitoring device according to claim 1, characterized in that the first sensor (4) is an acoustic sensor, a vibration sensor, a current or voltage sensor or a sensor for an electric or magnetic field, in particular a second detection device with a second sensor (6, 60) is provided in the form of a temperature sensor.

3. Monitoring device according to claim 1 or 2, characterized by a third detection device with a third sensor (7) for detecting whether the storage device (3) is in an open or closed state.

4. Monitoring device according to claim 3, characterized in that the third sensor (7) is a light sensor or a position sensor for detecting the position of a door (3b) or a locking element of the storage device (3).

5. Monitoring device according to one of claims 1 to 4, characterized in that the processing device (5) has a device (5a) for Fourier transformation and/or other signal processing of the signals detected by at least one of the sensors (4, 6, 7, 60). has time-dependent data.

6. Monitoring device according to one of claims 1 to 5, characterized in that the processing device (5) has a storage device (5b) for the recorded data (4a, 6a, 7a) and/or the Fourier-transformed data.

7. Monitoring device according to one of Claims 1 to 6, characterized in that the processing device (5) has a device (5c) for comparing the recorded data (4a, 6a, 7a) or the Fourier-transformed data with reference data, which is set up there , in particular trained, from the comparison, one or more parameters of the temperature profile in the storage facility (1) and/or one or more parameters for the state of the cooling or heating unit (3a) and/or the insulation state of the storage facility (3) or to determine the condition of a liquid coolant.

8. Monitoring device according to one of claims 1 to 7, characterized in that the processing device (5) from the recorded data (4a, 6a, 7a) the temperature profile in the storage device (3) and in particular the profile of the temperature of a substance stored in this or object (11) determined.

9. Monitoring device according to one of claims 1 to 8, characterized in that it has a device (8) for displaying or outputting the determined parameters and/or the course of activity of a cooling or heating unit (3a) and/or an alarm signal.

10. Monitoring device according to one of claims 1 to 9, characterized in that it has a transmitting and/or receiving device (9) for wireless communication, in particular for the output of alarm signals or display data on a terminal (10).

11. Protective device with a protective container (2) for storing substances and/or objects and a monitoring device (1) according to one of claims 1 to 10, wherein in particular the monitoring device (1) is integrated into the protective container (2) and further in particular a sensor (60) for monitoring the temperature inside the protective container (2) is provided, with the protective container in particular also having a container wall (2a, 2b) which consists at least partially of a material (2c) which is used in a temperature range between 2 and 8 degrees Celsius has a phase transition and that in particular the material is integrated into the container wall (2a, 2b), in particular enclosed, in such a way that the phase transition can be run through several times without generating a change in shape of the container wall.

12. A method for operating a monitoring device according to any one of claims 1 to 10, characterized in that the measured data (4a, 6a, 7a), in particular in the form of activity and temperature/time profiles and in particular also measured acoustic signals or measured signals from a vibration sensor, are Fourier transformed and compared with reference data and that at least one parameter is derived from the comparison is determined for the temperature profile in the temperature-controlled storage device (3).

13. Method for training a monitoring device (1) according to one of claims 1 to 10 in a storage device (3), characterized in that at least the temperature in the storage device, in particular in a protective container (2) within the storage device, and the course of activity of a heating or cooling unit (3a) is measured and reference data are determined from this.