Patent Application
20250179788
The disclosure relates to a method for monitoring a treatment structure for precipitation water, and a treatment structure for such precipitation water
From a water management perspective, it is currently deemed desirable to increasingly keep precipitation water in place instead of quickly bringing it into the drainage systems, for example after a downpour, and to discharge it. The known drainage systems comprise structures, which are provided for the absorption of water from precipitation and which help to keep sewage systems below their capacity limits in particular in the case of large quantities of precipitation and to relieve sewage treatment plants. For this purpose, structures for treating precipitation water, as decentralized systems, can also take into account that the precipitation or other sewage has to be purified for further use. This water can contain different sediments or can be contaminated with the following substances, respectively: organic or inorganic coarse substances, e.g., rocks, leaves, sand and other fine and superfine substances, particle-bound pollutants, e.g., PAK, dissolved pollutants, e.g., heavy metals (e.g., copper, zinc and lead) or also light liquids, such as gasoline and oil, can thus be present.
Treatment structures for precipitation water are known from the prior art, the core function of which is the purification of the precipitation water onsite and the subsequent seepage of the purified precipitation water into the ground. Here, “onsite” in particular refers to seepage next to or underneath buildings, roads or industrial plants. Such structures operate, for example, with sedimentation, adsorption or sieving (an oil separation can also be provided) and are constructed as follows: a vessel embedded in the ground, which can be cuboidal or also cylindrical, absorbs the precipitation water. In the case of a treatment structure, which is based on sedimentation, the water comes to rest in the vessel and existing sediment and solids deposit on the bottom of the vessel. Depending on the purification performance to be achieved, such structures are constructed differently and have different vessel lengths or nominal widths. The water, which is then purified of solids, is then drained off from the vessel via pipes or an outlet opening or is left to seep away directly. Structures of this type can be combined with different other upstream and downstream structures, for example with drain trenches (underground buffer tanks), into which the purified precipitation water is then introduced. From there, the water then seeps gradually into the subsoil and is supplied to the groundwater. In the case of treatment plants, which are based on adsorption, a filter element, which additionally or alternatively filters contaminations from the water, can additionally be introduced into the vessel.
The person of skill in the art refers to the deposition of the contaminations on the bottom of the vessel or the clogging of the filter, respectively, as silting. A progressing silting negatively influences the mode of operation of the plant because the silting can obstruct the runoff of the water. A maintenance of the plant thus becomes necessary at a certain level of silting.
The structures have to be aligned and formed so that, for example, legal requirements are complied with, in particular in the event of hydraulic overload, i.e., in the event of excessive precipitation. This defines the “need for maintenance”, which is a function of the amount of precipitation in each case, for each treatment structure: to be able to comply with the required purification performance, the structures have to be emptied or maintained, respectively, in due time, for example. The structures thus have to be monitored on a regular basis, which means high time and personnel costs because in particular weather events with high amounts of precipitation can also occur unexpectedly.
It is an object of the present disclosure to provide a method for monitoring a treatment structure for precipitation water, by means of which the need for maintenance can be determined in a time-and cost-efficient manner.
This object is solved by means of a method for monitoring a treatment structure for precipitation water as disclosed and claimed.
The further object of being able to monitor the need for maintenance of the treatment structure for precipitation water in a time-and cost-efficient manner is solved by means of a treatment structure for precipitation water as disclosed and claimed.
According to a first embodiment of the method for monitoring a treatment structure for precipitation water, the latter has at least one receiving vessel for precipitation water and an outlet for discharging treated precipitation water. The treatment vessel further comprises a monitoring device for monitoring a need for maintenance of the treatment structure. The monitoring device has at least one first sensor for detecting a fill level of precipitation water in the vessel and at least one second sensor for detecting an amount of precipitation in a predetermined area surrounding the treatment structure and at least one data processing unit, in which parameter values are stored, which comprise a predetermined target fill level and a predetermined target rate of decrease of the fill level of the precipitation water in the vessel. The first and the second sensor are thereby operatively coupled to the data processing unit via an electronic data line.
The method comprises the steps of:
It can be determined very quickly by means of the method, whether a treatment structure is in need of maintenance, when this state will likely occur or whether the level of silting of the structure or of the vessel, respectively, is still below a tolerance limit, which is typical for the respective treatment structure. In particular after weather events with high amounts of precipitation, the treatment structure can report its need for maintenance by means of the sensor-controlled monitoring. If no maintenance is necessary, a staff member also does not need to physically inspect the treatment structure but can perform other duties. The treatment structure can thus be monitored in a time-and cost-efficient manner. The target fill level can additionally be supplemented by a further parameter “target retention duration” (the so-called retention duration line) as monitoring parameter.
Here, “treatment structures” refers to structures, which serve the purpose of purifying precipitation water and which are also installed underground. Seepage devices are often connected downstream from or can even be integrated into these treatment structures. This further also includes rain gutters, which, in certain designs, have a substrate, which absorbs sediments or filters them out of the water and which has to likewise be purified.
Here, “precipitation water” refers to any water, which results from precipitation, be it rain, snow, sleet or hail. This also includes water, which reaches into the functional area of the described treatment structures due to flooding.
“Amount of precipitation” refers to a measurement of the precipitation intensity and specifies how much precipitation has fallen on a predetermined area within a certain time period.
“Need for maintenance” is understood to be a state of the treatment structure to be monitored, which requires, for example, a cleaning of the vessel and thus freeing it from accumulated solids and sediment. This is determined by a level of silting, i.e., how high the proportion of sediment is, which has accumulated in the vessel of the treatment structure. This sediment proportion is determined by the coarse substance retention or by the sludge level height, respectively, which develops due to the purification of the precipitation water over time. The treatment structure retains sediments in its receiving vessel, which can also be a buffer tank and has a certain volumetric capacity (“sludge chamber for coarse substances”, “sedimentation collector for fine substances”). If this is reached, the so-called hydraulic performance decreases. The need for maintenance exists when the hydraulic performance of the treatment structure no longer exists, for example, due to sedimentation and silting. The performance is measured by inflow volumes to be displayed, which the treatment structure has to be capable of treating. The hydraulic performance of the respective treatment structure is advantageously examined and monitored indirectly by means of the method.
According to a further embodiment of the method, the monitoring device has a local data processing unit and a central data processing unit. The method thereby comprises the following further steps:
The treatment structure can advantageously be monitored remotely by means of the monitoring device. The central data processing unit can be configured as “cloud” system, so that the data of the respective treatment structure to be monitored can be accessed location-independently. With this design, several treatment structures can also be connected to the same central data processing unit and can form a network in this way. Data from several treatment structures can be collected and can be evaluated with regard to different parameters or an interpretation of these parameters, for example derivation from these parameters. Further information, which makes it possible to make predictions about the effects of upcoming precipitation events on these treatment structures, can be gathered from the determination of the need of maintenance of several treatment structures.
According to yet a further embodiment of the method, the evaluation of the detected values of the first and of the second sensor (several sensors of each of the two types can in each case also be arranged on the structure) occurs in the local or in the central data processing unit by using a parameterized precipitation runoff model and by using artificial intelligence (AI), wherein the precipitation runoff model includes predetermined parameters of the treatment structure to be monitored. The parameters are structure-or also assembly-related and comprise, for example, dimensions of the water-bearing vessel or also the separation performance thereof. In a further embodiment of the method, an evaluation of the detected value of the first and of the second sensor is possibly solely by using the precipitation runoff model. Additionally or also alternatively to the precipitation runoff model, a parameterized hydraulic model can be used for evaluating the detected values of the first and of the second sensor. The hydraulic model describes the flows and the solids transport within the treatment structure and thereby orients itself on the parameters of the structure, such as, e.g., the dimensions thereof.
In a further embodiment of the method, the hydraulic model can likewise be supported by an AI, so that certain parameters can gradually be learned independently and future evaluations are available. Alternatively, a self-learning AI without an above-mentioned runoff model or a hydraulic model can also be used, depending on how the evaluation of the data is to take place.
The use of such a runoff model or of a hydraulic model in combination with an AI or also a purely AI-based model provides for a highly accurate determination of the need for maintenance of the monitored treatment structure after a training period of the AI. For example, statements can thus also be made about the approximate level of the solids feed per precipitation or maintenance cycle or when the performance of the treatment structure will no longer exist in light of expected solids feeds (prediction of the future) from different data sets collected over time relating to the degree of silting of the structure.
Depending on which model is used, thus precipitation runoff model, hydraulic model, a purely AI-based model or a combination of the afore-mentioned models, the geometry of the structure, the expected inflow and runoff as well as further boundary conditions are necessary for the evaluation of the detected sensor data.
According to yet a further embodiment of the method, the predetermined parameters of the treatment structure to be monitored, selected from the group comprising dimensions of the vessel, nominal width of the outlet, type of the treatment structure, separating performance and passage value of the treatment structure, plant dimensioning, such as drain trench width, height and storage coefficient, assembly positions and heights of the sensors within and outside of the treatment structure, connected (fastened) area, (GIS-based) information, such as geo position, are stored in the data processing unit. These parameters can also be used in the used precipitation runoff model or the hydraulic model or can be learned by the self-learning AI. The determination of the need for maintenance and of the hydraulic, technical level of the operational readiness of the structure can be further improved thereby.
This type of static, invariable parameters can advantageously also complete the determination of the need for maintenance. Parameters, which are structure-specific, can be used to make accurate predictions, for example, for the length of the next maintenance interval, namely specifically for the respective treatment structure.
A treatment structure for precipitation water for carrying out the method itself is a further subject matter. The treatment structure has at least one receiving vessel for precipitation water and an outlet for discharging treated precipitation water. The treatment structure has a monitoring device for monitoring the need for maintenance of the treatment structure, which has at least one first sensor, by means of which the fill level of the precipitation water in the vessel can be detected, and at least one second sensor, by means of which the amount of precipitation in a predetermined area surrounding the treatment structure can be detected, and at least one data processing unit, by means of which the values detected by means of the at least one first and the at least one second sensor can be evaluated with regard to a need for maintenance of the treatment structure. The at least one first and the at least one second sensor are thereby operatively coupled to the data processing unit via an electronic data line.
The sensor-controlled monitoring provides for a remote examination of the treatment structure, which saves personnel and costs. A staff member does not have to visit all existing treatment structures at regular time intervals, but a staff member can maintain the treatment structures, which do in fact require this, as needed.
According to a further embodiment of the treatment structure, the receiving vessel is designed differently, it can be cylindrical or cuboidal. The receiving vessel can also be formed as buffer tank.
According to yet a further embodiment of the treatment structure, the monitoring device has at least one further sensor, selected from the group, which comprises flow measurement sensors, load measurement sensors, further fill level sensors, temperature sensors pH measurement sensors and moisture sensors. Moisture sensors measure the moisture of the air or of the ground and can allow for further statements, for example, about the amount of fallen rain or precipitation, respectively, or about the seepage or absorption capacity, respectively, of the ground. In order to monitor a change of the ground, pH sensors can additionally be used. Further sensors provide for an even more accurate monitoring and accurate determination of the need for maintenance. Sensors, which are based on a different technology, such as, e.g., optical, acoustic, ultrasound-or also radar-based sensor technology can be used thereby. To actually determine the need for maintenance, the essential parameters are the fill level of the vessel and the amount of precipitation, which falls in the area around the treatment structure. However, each parameter, which has a connection to the determination of the solids feed into the vessel of the treatment structure, can be detected additionally and can be incorporated in the calculation of the need for maintenance, in order to be able to make even more accurate statements.
According to yet a further embodiment of the treatment structure, the monitoring device comprises the local data processing unit and the central data processing unit. The local data processing unit is thereby operatively coupled electronically to the at least one first and the at least one second sensor via a first data line. The central data processing unit is thereby operatively coupled electronically to the local data processing unit via a second data line. In a further embodiment, several local data processing units can also be provided, which are each assigned to the individual sensors or sensor groups. All of the precipitation amount sensors are thereby connected to a common local data processing unit and the fill level sensor is equipped with its own local data processing unit. These local data processing units do not communicate with one another but separately with the central data processing unit. Electronic data lines can thus be reduced directly on the treatment structure. The data lines can be wired or wireless and can be realized via radio or other wireless data connections. Different radio standards can be used thereby for the data transmission and communication. The local data processing unit can further be present directly in the treatment structure and the central data processing can be monitored at a different location, which is suitable for this purpose. Several treatment structures can be monitored by means of a central data processing unit in this way (cloud system) and a network of treatment structures for evaluating large precipitation events can optionally be formed.
According to yet a further embodiment of the treatment structure, the monitoring device has a self-sufficient energy supply. The at least one first and the at least one second sensor and the local data processing unit are preferably equipped with one or several rechargeable batteries. Other energy production mechanisms as well as a solar panel or a small wind power plant can further be used. They thus provide for an energy-efficient operation of the monitoring device.
Further embodiments of the treatment structure as well as some of the advantages, which are associated with these and further embodiments, become clear and more easily comprehensible from the following detailed description with reference to the accompanying figures. Objects or parts thereof, which are essentially identical or similar, can be provided with the same reference numerals. The figures are only a schematic illustration of an embodiment of the invention.
A treatment structure 1 for precipitation water, which operates on the basis of sedimentation, is illustrated in
The treatment structure 1 silts as times goes by and as precipitations occur. To be able to monitor the treatment structure 1 with regard to whether a cleaning of the vessel 2 is necessary, the treatment structure 1 is equipped with a monitoring device, which is essentially constructed of a data processing unit 10, which is electronically connected to the below-listed sensors: to determine the fill level of the precipitation water 3 in the vessel 2, the vessel 2 has a first sensor 11, which measures the fill level of the precipitation water in the vessel. So that an amount of precipitation can be detected, several second sensors 12 (figuratively illustrated by means of two sensors 12), which measure the precipitation intensity or the amount of precipitation, respectively, in a predetermined area surrounding the treatment structure 1, are arranged on an area around the vessel 2.
The sensors 11, 12 are connected to the data processing unit 10 via an electronic data line 13 (which can be realized in a wired or wireless manner via radio). The data processing unit 10 detects the values detected by the sensors 11, 12, processes them and sends them via an electronic data connection 21, which is illustrated as being wireless in the figure, to a central data processing unit 20, which takes over the evaluation of the data collected by the data processing unit 10. The actual data processing takes place in the central data processing 20, for example the precipitation intensity for the entire monitored area around the treatment structure 1 is thus determined there.
A completely underground treatment structure 1 is shown in
As components, the monitoring of the treatment structure 1 essentially requires a fill level measurement and a precipitation intensity measurement, which is supported via cloud platform (corresponding to the central data processing unit 20). On the cloud platform, the overall system of the treatment structure is managed, data is processed, statements are made and parameters are changed, calibrated or adapted, respectively, in the local data processing unit, also with regard to the sensors.
The fill level sensor (corresponding to the first sensor 11) or the measurement therewith, respectively, can then be designed as follows:
The fill level sensor or sensors are installed in the treatment structure, wherein at least one daily measurement of the water level status is provided. The fill level sensor can optionally be combined with or expanded by, respectively, a flow measurement, a dirt load measurement, a conductive measurement or other measurements by means of correspondingly suitable sensors. With a use of batteries, the fill level sensor can reach long service lives (of up to 5 years) and can be parameterized to structure-and assembly-related parameters, such as, for example, assembly position, overflow sill and structure-related fade-outs. Due to the fact that space is extremely limited in the receiving vessel or the buffer tank, such a parametrization is sensible, so that the sensor can fade out optionally predetermined false reports, which can result due to the structure-and assembly-related parameters. Fill level sensors can be used, which have self-learning functions and which adjust automatically to the structure after installation. Different parameters are detected thereby, which are provided by means of the local data processing unit. A state (good/bad) of the treatment structure or also of the dynamic thereof (for example, reachable maximum rate of decrease) can be learned by the sensor. The local data processing unit ensures that the fill level sensor operates in the respective correct measuring cycle and monitors whether the sensor provides data. The local data processing unit can adapt and change the measuring cycles of the fill level sensor for this purpose. The fill level sensor itself can be connected to a cloud or via the local data processing unit, respectively (realized by means of the central data processing unit), this takes place via a data transmission via different radio standards. The parameters for the fill level sensor can also be changed or adapted via this, respectively.
The used fill level measurement technology is variable. Non-contact technologies with, e.g., ultrasound, infrared or radar or technologies with contact with, e.g., conductive contacts or float switches can thus be used. The fill level sensor can be used with different measuring programs. In a “normal” program, a daily measurement of the fill level of the vessel can thus take place via the respectively used fill level measurement technology. A switch-over to an “event” program can be made, wherein the fill level sensor is read out as to whether there is threat of an inadmissible overflow of the treatment structure, i.e. that the structure discharges unpurified precipitation water because the degree of silting has become too high and the structure abates in the case of a rain yield factor, which is too low (evaluation in the central data processing unit). Measurements for this can take place at minute intervals. Depending on the rise and the fall of the water level in the treatment structure can be checked for target state. The rise and fall of the fill level as well as the retention duration in the structure, which can be determined therefrom, are indicators for the need for maintenance or also for the state of the structure in general, respectively. The data transmission can take place at different points in time in this program, thus, for example, at the beginning of the switch-over to this program and again when switching back into the “normal” program, for example when the target level (max. water level status) is reached. The fill level sensor can be triggered by means of an additional sensor within the structure, in order to prompt the fill level sensor to change the measuring program, for example via a conductive contact.
The precipitation intensity or precipitation amount sensor (corresponding to the second sensor 12) or the measurement therewith, respectively, can be designed as follows:
One or several such sensors are arranged in an area/a predetermined area of the property to be monitored (corresponding to a geographic area for determining the amount of precipitation or also referred to as rain yield factor). Used technologies are: analog ombrometers, communal rain gauges, digital rain meters, optical precipitation intensity meters, radar sensors, piezoelectric sensors. They can be retrofitted or integrate already existing measuring systems, such as communal rain gauges, respectively. By means of PV/battery operation or connection to local-position energy sources, such as lampposts, the sensors can be supplied with energy in a cost-efficient manner or also so as to be independent of external energy. Via their data connection to the local data processing unit, its measuring data, such as the data of the fill level sensor, are likewise provided to the central data processing unit. Its main functionality lies in the detection of the precipitation intensities, they further transmit changed values or absolute values or can reflect changes of the precipitation intensities and amounts of rain compared to old data. These systems do not have any measuring cycles but are in continuous operation.
The data processing unit, in particular the central data processing unit 20, which, as cloud platform, manages an overall system, processes data, makes statements and sets parameters on the measuring systems, can operate as follows:
The detected sensor values/data are/is processed collectively and a decision basis, thus the need for maintenance and statements about the performance, are generated there. The sensor values for property-or system-related rain yield factors, respectively, which are measured by means of the second sensor 12, and the fill level values, which are measured by means of the first sensor 11 (from normal and event program), are provided to a cloud software for the data analysis, evaluation and subsequent use.
With regard to the evaluation of the detected sensor values and determination of the need for maintenance, measured amounts of precipitation (rain yield factors) and fill level behavior (which corresponds to the purification behavior of the treatment structure) are correlated, wherein the entry of contamination per precipitation is an unknown variable. It is estimated. Fill level amount of the vessel and the precipitation intensity, which is measured on the surrounding area, correlate differently, depending on the monitored treatment structure: a distinction must be made that there are treatment structures, which allow purification and seepage, and those, which only purify. In any case, a portion of the treatment structure is always under water, holds back solids/particles from the precipitation water and allows the purified water to seep away. This purification and/or seepage performance correlates with the intensity of the rain or rain yield factor, respectively (amount of precipitation x drainage/precipitation area) and with regard to the fill level in the structure (actual state). The correlations of the behavior can be described in a deterministic manner and can be displayed with the help of an AI, so that not every parameter, which is incorporated in the calculation, has to be adjusted by hand.
All static parameters, thus parameters typical for the structure, are parameters, which can improve a statement about the need for maintenance. For a data-reduced monitoring with faster calculating time, they can be omitted. The rate of decrease of the water level/fill level to target level in the structure decreases with each precipitation event and a subsequently occurring silting of the structure. A state, at which the functionality does no longer exist sufficiently, occurs at some point. For a needs-based maintenance interval, it is then important to determine when the behavior of the amount of precipitation to purification rate (interpretation from fill level over time as well as ground moisture . . . ) changes. In the event that the vessel is full and the rate of decrease tends to zero, it can happen that the treatment structure abates unpurified water even though it should not do that. The overflow can then be identified by means of the monitoring device via the measured water level. In such cases, an optimization can be provided for how or when the fill level sensor switches into which measuring program, in particular with switchover from daily and minute-by-minute measurement and data transmission, wherein future overflow can be prevented.
The treatment structure with monitoring device advantageously provides for a functional monitoring of the structure itself, which can reflect performance promises from the manufacturer and which makes it possible to fulfill legal requirements with regard to maintenance and cleaning of the treatment structures. The exceeding of a precipitation amount threshold can further be documented and reports can be produced about the mode of operation of the treatment structure in general. These reports can comprise property-or system-related amounts of precipitation, respectively, points in time critical water level positions are exceeded and runoff/overflow calculated therefrom. It can further be documented by means of the data collected in the central data processing unit, how fast the water level in the treatment structure normalizes when precipitation has fallen. The need for cleaning in terms of a maintenance monitoring can likewise be recorded, so that it is documented, when an emptying/cleaning of the treatment structure is necessary in order to always or again, respectively, meet the manufacturer-specific and legal requirements of a correct mode of operation.
The software program, which is used for evaluating the detected sensor values, in particular includes system-related “digital twins” in the form of structure-related parameterizable precipitation runoff models, which reflect the behavior of the structure and thus the correlation between variable parameters (which are measured, such as, e.g., of the fill level of the vessel) and static parameters (such as, e.g., nominal width of the vessel). If-then simulations and predictions into the future can thus be generated with the help of this digital twin and actual measuring values, and a global optimum for managing (maintaining) these structures can be determined via a plurality of structures, such as, for example, a cost-, time-and ecology-efficient maintenance sequence and maintenance tour planning.
The overall system can further realize a so-called “SaaS” solution (Software as a Service) for sewer cleaning companies as operator of such treatment structures, wherein these companies can set up a cost-efficient and time-efficient monitoring of their treatment structures.
| Number | Date | Country | Kind |
|---|---|---|---|
| 10 2022 111 701.4 | May 2022 | DE | national |
This application is a national stage application, filed under 35 U.S.C. § 371, of International Patent Application PCT/EP2023/062314, filed on May 9, 2023, which claims the benefit of German Patent Application DE 10 2022 111 701.4, filed on May 10, 2022.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2023/062314 | 5/9/2023 | WO |
